Biophysica doi: 10.3390/biophysica6020030

Authors: Shih-Chu Jeff Liao Beniamino Barbieri Gerd Baumann Zeno Földes-Papp

This article addresses a current point of contention in the field of single-molecule/single-particle tracking, as well as the relevant literature, and supplements it with some published cell-based experiments to illustrate our conclusions and known theorems. We attempt to explain the controversy surrounding the differing biophysical and cell biological results of studies on the individual molecule and those “at the single-molecule level” as well as at the level of many molecules in such a way that even readers who are unfamiliar with the subject can understand it without having to read all the mathematical, physical, and biophysical references. Given this abundance of studies in the literature, it is obvious that genuine single-molecule studies are urgently needed, i.e., single-molecule studies that focus on increasing the sensitivity of the temporal resolution of single-molecule measurements and not just on spatial resolution.

Biophysica doi: 10.3390/biophysica6020029

Authors: Wafa Hourani Balakumar Chandrasekaran Sankar Muthumanickam Pandi Boomi

Background/Objectives: Until now, there have been no suitable medicines to treat infections caused by the Ebola virus. Cistus incanus, a traditional medicinal plant, contains several phytocompounds exhibiting antioxidant and anti-inflammatory properties. Methods: In this research, the molecular level interactions of the phytocompounds of Cistus incanus were investigated for their antiviral potential against the active site of VP40 protein of Ebola virus using in silico molecular docking. Further, the potential compounds were assessed for their stability in the protein using molecular dynamics (MD) simulations. Results: Methyl gallate, catechin, and quercetin showed excellent docking scores of −9.8, −8.8, and −7.7 kcal/mol, respectively, and favorable interactions with the target protein. These complexes showed good stability over the 100 ns MD simulation time. In addition, the phytocompounds displayed favorable pharmacokinetics and drug-like properties. Conclusions: Our study offers the antiviral potential of phytocompounds (methyl gallate, catechin, and quercetin) of Cistus incanus, suggesting their suitability as lead candidates for the treatment of Ebola viral infection.

Biophysica doi: 10.3390/biophysica6020028

Authors: Viacheslav V. Krylov Daniil A. Sizov Anastasia A. Sizova

The biological effects of weak low-frequency magnetic fields (LFMFs) remain controversial, particularly regarding frequency-specific resonance-like responses. Many previous studies tested different frequencies sequentially, potentially introducing uncontrolled environmental variability. This study aimed to evaluate frequency-dependent effects of LFMFs on the growth of juvenile Daphnia magna under strictly synchronized and temperature-controlled conditions. Genetically identical neonates from a single parthenogenetic brood were simultaneously exposed to sinusoidal 50 μT magnetic fields at 20, 25, 30, 35, or 40 Hz using spatially separated Helmholtz coils integrated into a closed-loop thermal stabilization system. Body length was measured after 48, 96, and 144 h of exposure. No significant growth differences were detected after 48 h. After 96 h, a significant biological effect was observed only at 30 Hz. The most pronounced responses occurred after 144 h, with significant growth stimulation at 25, 30, and 35 Hz and a maximal effect at 30 Hz. The frequency–response relationship exhibited a dome-shaped pattern that became less sharply peaked with prolonged exposure. These findings demonstrate duration-dependent and frequency-specific stimulation of juvenile daphnid growth with weak LFMFs. It suggests that exposure time critically influences the manifestation and breadth of resonance-like magnetobiological effects.

Biophysica doi: 10.3390/biophysica6020027

Authors: Lucien Bettendorff

Electron transfer is one of the most essential processes in biological systems. Redox reactions, either directly or indirectly, drive the main ATP-synthesizing pathways, especially those relying on a chemiosmotic mechanism, and as such, they are fundamental to photosynthesis and respiration. During biochemical redox reactions, electrons are transferred from a low-potential donor to a high-potential acceptor, mainly affecting the oxidation state of carbon atoms. The mechanism of electron transfer remains an intriguing enigma because of the wave-particle duality of subatomic particles. According to the biophysical conditions, electrons can be transferred by quantum tunneling or hopping from one redox site to another. While the driving force is always the electrochemical potential, a particularly interesting case is reversible electron bifurcation, where downhill (exergonic) redox reactions are coupled with uphill (endergonic) reactions by splitting the electrons of a two-electron donor. Here, we aim to discuss these different mechanisms in a comprehensive review accessible to students, teachers, and researchers in biological sciences.

Biophysica doi: 10.3390/biophysica6020026

Authors: Ixchel Ramírez-Camacho Fernando León Cedeño José Germán Vázquez Cuevas Eva Florencia Lejarazo Gómez Ulises Martínez-Ortega Mirthala Flores-García Ana María Mejía-Domínguez Aurora de la Peña-Díaz Fausto Alejandro Jiménez-Orozco

Novel pharmacological approaches advocate developing multitarget drugs, that is, molecules capable of simultaneously acting on two or more pharmacological targets to produce synergistic effects from a single compound in each disease. This strategy may help reduce required doses and prevent drug–drug interactions typically associated with polypharmacy. Coumarins are natural products with diverse pharmacological activities, including antioxidant, anti-inflammatory, anticancer, neuroprotective, cardioprotective, and antithrombotic effects. The pleiotropic actions of these molecules suggest that modifying the coumarin structure could yield new multi-target antiplatelet agents with greater efficacy and safety than those currently available in clinical practice. In this work, we began with a theoretical approach using molecular docking and designed three coumarins that simultaneously inhibited platelet aggregation induced by epinephrine, collagen, and ADP. Experimentally, we evaluated the structure activity relationship of three coumarins: (A) 6,7-dimethoxy-3-(1H-pyrrol-1-yl)-2H-chromen-2-one, (B) 7,8-dimethoxy-3-(1H-pyrrol-1-yl)-2H-chromen-2-one, and (C) 3-(1H-imidazol-1-yl)-6,7-dimethoxy-2H-chromen-2-one. In silico studies suggest that compounds B and C may exhibit antagonistic interactions at the α2-adrenergic, GPVI collagen, and P2Y12 ADP receptors. Additionally, molecular docking indicates essential interactions between the compounds and the GPIIb/IIIa fibrinogen receptor.

Biophysica doi: 10.3390/biophysica6020025

Authors: Ahmed Shahat Belal Gabriel Tchuente Kamsu Ahmed A. Al-Kubaisi Cromwel Tepap Zemnou

The common metabolic disorder, lactose intolerance, is often treated with oral lactase enzyme supplements, which can frequently cause gastrointestinal instability. This work utilizes Malbranchea cinnamomea’s AA9 lytic polysaccharide monooxygenase (LPMO) to target β-lactose (β-lactose) in an investigation of a new enzymatic approach for lactose breakdown. Potential possibilities for lactose breakdown are AA9 LPMOs, copper-dependent enzymes that oxidatively cleave glycosidic bonds in polysaccharides. We employed a combined in silico method that incorporated molecular docking, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Docking studies revealed that β-lactose formed hydrogen bonds with key residues SER100, ASN54, and ARG56, exhibiting a greater binding affinity (−5.4 kcal/mol) toward LPMO compared to the control citric acid (−4.9 kcal/mol). Upon DFT analysis, (LPMO) showed excellent stability and appropriate reactivity for enzyme interaction. The higher stability of the LPMO-β-lactose complex was highlighted by MD simulation over 100 ns, which showed lower root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values, greater structural compactness, and reduced solvent accessibility when compared to the control. These collective findings suggest that β-lactose interacts efficiently with the AA9 LPMO active site, supporting its potential as a novel enzymatic target for lactose degradation. This computational study provides a theoretical foundation for developing alternative therapeutic strategies for lactose intolerance, though further in vitro and in vivo investigations are required to validate these findings.

Biophysica doi: 10.3390/biophysica6020024

Authors: Hong Luo Jie He Zhichao Liu Chen Zeng

Molecular representation learning (MRL) has garnered significant attention due to its pivotal role in downstream applications such as molecular property prediction and drug discovery. In most MRL approaches, molecules are encoded into 2D topological graphs via graph neural network (GNN), which suffers from over-smoothing issues and limited receptive fields. Furthermore, most GNN models fail to utilize the 3D spatial structural information that determines molecular physicochemical properties and biological activity. To this end, here we propose multimodal contrast-enhanced molecular representation learning (MCMRL). This approach utilizes both the 2D topological information and 3D structural information of molecules for contrastive learning to enhance molecular graph representations. Further, it integrates additional molecular fingerprint information and feature fusion techniques to incorporate multimodal knowledge, yielding more reliable and generalizable molecular representations. MCMRL is pre-trained on ~10 million unlabeled molecules from PubChem, followed by various downstream benchmark tasks. Experimental results demonstrate that MCMRL achieves superior performance in 9 out of 13 benchmark tests for molecular property prediction, validating its effectiveness in molecular representation learning. Furthermore, potential molecular drugs binding to biological target protein DRD2 screened by MCMRL representation show promising affinity score, which also demonstrates the efficacy of the proposed method.

Biophysica doi: 10.3390/biophysica6020023

Authors: Joachim Storsberg Sophia Rosencrantz Ruben R. Rosencrantz

The interface between biomaterials and biological systems is crucial for medical implants and tissue engineering. Surface modifications are a key strategy for controlling interactions. Synthetic glycopolymers offer a versatile toolbox, mimicking the structure and function of natural glycoconjugates like mucins. This review highlights the significance of glycopolymers for targeted surface modifications of established biomaterials, such as silicones and poly(meth)acrylates. Controlled polymerization techniques, like the reversible-addition-fragmentation chain-transfer (RAFT) polymerization, enable the synthesis of well-defined glycopolymer architectures. Glycopolymeric surface functionalization creates tailored interfaces for different biological responses, from preventing protein and cell adhesion to promoting specific cell-type binding. The focus lies on using single, well-characterized polymeric base materials and tuning their surface properties through glycopolymer coatings to achieve various and specific functions. This approach opens new dimensions in the development of advanced biomaterials for applications like contact lenses, drug delivery systems, and biosensors and also possesses potential regulatory advantages by leveraging the safety profiles of existing materials.

Biophysica doi: 10.3390/biophysica6020022

Authors: Mariia Riabova Kelly C. Grayson Samantha Y. A. Terry

The accurate measurement of spheroid area and morphology is critical for the progression of the integration of 3D models in in vitro cancer research and is increasingly used to measure effective therapeutic efficacy of X-ray radiation. Current methods of measuring spheroids require labour-intensive manual analysis or the use of complex software tools. SphereMetrics was created as a user-friendly Shiny app with a straightforward interface designed to streamline the process of measuring the area and eccentricity of spheroids. It allows the upload and automated detection of spheroids across multiple file formats and generates robust and objective area and eccentricity measurements. Area measurements derived from SphereMetrics were compared to manual quantification with ImageJ and AnaSP for untreated and irradiated (0–20 Gy) human neuroendocrine BON-1 cancer spheroids. When compared to ImageJ and AnaSP, SphereMetrics was shown to provide fast, accurate data (R2 = 0.87 and 0.83, respectively). Spheroid analysis took 19.92 ± 8 s/image with SphereMetrics, approximately four times faster than ImageJ analysis (89.81 ± 11.52 s/image) and nine times faster than AnaSP (183.36 ± 31.62 s/image). SphereMetrics represents an accessible and efficient tool for spheroid analysis, facilitating data collection and analysis for routine in vitro model research, ideal for non-programmers.

Biophysica doi: 10.3390/biophysica6020021

Authors: Mutlay Keskin

Testicular metabolism can be non-invasively assessed using FDG-PET/CT, which provides insights into physiological and age-related changes. Understanding normal testicular FDG uptake is essential to distinguish between benign variation and pathological findings. In this retrospective study, 80 men (mean age: 54.7 years, range: 26–79) who underwent PET/CT for lung nodule evaluation were analyzed, excluding individuals with testicular disease, prior surgery, or elevated blood glucose (>180 mg/dL). FDG uptake (SUV_mean) and testicular volume were measured for each testis, and correlations with age, blood glucose, and volume were assessed using standard statistical methods. The mean testicular SUV_mean was 2.62 ± 0.50, showing a significant negative correlation with age and a weak positive correlation with testicular volume. After adjusting for volume, the negative association with age persisted, while no significant relationship with blood glucose was observed. These findings indicate that physiological testicular FDG uptake gradually declines with age, reflecting both metabolic and structural alterations. Recognizing these normal patterns is critical for accurate PET/CT interpretation and reducing the risk of false-positive findings.

Biophysica doi: 10.3390/biophysica6020020

Authors: Muthamil Balakrishnan Janardanan Kumar Jaison Jacob Mathunny Varshini Karthik Ashok Kumar Devaraj

Sarcopenia is a degenerative musculoskeletal condition recognised as the age-related decline in skeletal muscle mass, strength, and function. Traditional diagnostic methods are limited by cost, accessibility, and subjectivity. This study aimed to develop a non-invasive, AI-driven, video-based framework for early Sarcopenia detection using functional movement analysis. Participants with and without Sarcopenia were recorded performing functional movements such as level walking, stair climbing, and ramp walking. Ten representative frames were extracted from each participant, resulting in 300 images (150 Sarcopenic, 150 non-Sarcopenic) utilised for the study. The DeepSarcAE model is an integrated framework of an autoencoder and a CNN-based classifier. Its performance was benchmarked against pretrained architectures such as EfficientNet, ResNet, MobileNet, Inception, VGG16 and four custom CNN models. Evaluation metrics such as sensitivity, specificity, precision, negative predictive value (NPV), accuracy, and AUC were used to analyse the models. DeepSarcAE outperformed all other models, attaining 100% sensitivity, 83.33% specificity, 85.71% precision, 100% NPV, 91.67% accuracy, and an AUC of 0.96. VGG16 and MobileNet followed the performance of DeepSarcAE closely, while the Inception network exhibited the weakest results due to poor generalisation. TheDeepSarcAE framework offers a scalable, cost-effective, and non-invasive approach for Sarcopenia screening from the input gait image frames. Its promising preliminary performance highlights the potential of deep learning in early diagnosis and clinical decision support in preventive healthcare.

Biophysica doi: 10.3390/biophysica6020019

Authors: Hari Krishnareddy Rachamala Sreya Roy Srujan Marepally

Lipid-based delivery systems (LDS), including lipid nanoparticles (LNPs) and liposomes, have become indispensable tools in modern biomedicine owing to their biocompatibility, capacity to encapsulate diverse therapeutic agents, and potential for targeted delivery. Despite their clinical success, conventional batch-based manufacturing methods are hindered by variability, limited scalability, and complex processing steps, slowing their broader translation. Microfluidic technologies offer a transformative solution by enabling precise fluid handling, rapid mixing, and reproducible production of LDS with tunable physicochemical attributes such as particle size, lamellarity, and drug-loading efficiency. This review highlights advances in microfluidic design strategies, including hydrodynamic flow focusing, staggered herringbone mixers, and toroidal micromixers, and evaluates how critical parameters such as flow rate, solvent composition, and lipid concentration influence LDS performance. Furthermore, we discuss the application of microfluidics in drug delivery, nucleic acid therapeutics, and vaccine platforms, underscoring its role in improving scalability, quality control, and clinical translation. Finally, we examine current challenges, including throughput limitations and solvent handling, while outlining future directions for integrating emerging materials and additive manufacturing to optimize LDS fabrication. Collectively, microfluidic platforms provide a promising pathway for next-generation lipid nanomedicines with enhanced precision, reproducibility, and therapeutic efficacy.

Biophysica doi: 10.3390/biophysica6020018

Authors: Baatarmanlai Dorjgochoo Delgernaran Gomboragchaa Odonchimeg Munkhjargal Baatarjargal Purevdorj Enkhgerel Baljinnyam Idertungalag Sambuu-Yondon Amgalanzaya Dorjgochoo Enkhtaivan Erdene

Antimicrobial resistance represents not only a biological challenge but also a physicochemical limitation associated with antibiotic transport, membrane interaction, and local availability. In this preliminary study, a liposome-encapsulated doxycycline delivery system was developed using egg yolk-derived phospholipids, and its biophysical properties and release behavior were investigated. Phospholipids were isolated from egg yolk and used to prepare doxycycline-loaded liposomes via a thin-film hydration method combined with freeze–thaw processing. Liposome morphology was characterized by atomic force microscopy (AFM), while encapsulation efficiency was quantified by reversed-phase high-performance liquid chromatography (RP-HPLC). In vitro release kinetics were evaluated using a dialysis diffusion method, and antibacterial activity was assessed as a functional indicator of drug availability using minimum inhibitory concentration (MIC) assays against Staphylococcus aureus and methicillin-resistant S. aureus (MRSA). The prepared liposomes exhibited morphology with diameters of approximately 153 nm (PDI = 0.223). The encapsulation efficiency of doxycycline hyclate was 8.41%, and complete drug release was achieved within 48 h. Liposome-encapsulated doxycycline demonstrated a two-fold reduction in MIC values compared with free doxycycline. These findings offer preliminary insight to support further optimization and expanded investigation of liposome-encapsulated antibiotic delivery systems.

Biophysica doi: 10.3390/biophysica6020017

Authors: Héctor Enrique Trujillo-Ruiz Dania Guadalupe Leal-Rodríguez Hisila del Carmen Santacruz-Ortega Oliviert Martínez-Cruz Sandra Carolina De La Reé-Rodríguez Armando Burgos-Hernández Erika Silva-Campa Ángel Antonio Carbonell-Barrachina Carmen María López-Saiz

Cancer is the second leading cause of death worldwide, requiring more effective treatments. By-products from the white shrimp (Penaeus vannamei) are a promising source of bioactive compounds. Compounds with antiproliferative activity were isolated and identified in exoskeleton and cephalothorax extracts. The hexane extract of the exoskeleton reduced the viability of Human Prostate Carcinoma cell line (22Rv1) to 40.6% without toxicity in Adult Retinal Pigment Epithelium-19 (ARPE-19). Among the 19 fractions obtained, H3 reduced cell viability to 20.78%. Spectroscopic analysis identified bis(2-ethylhexyl) terephthalate, neoxanthin, and violaxanthin. Fluorescence microscopy showed morphological alterations. These findings demonstrate in vitro antiproliferative activity of compounds derived from shrimp by-products and support further studies to elucidate their mechanisms of action and evaluate their potential relevance in cancer prevention or therapeutic research.

Biophysica doi: 10.3390/biophysica6020016

Authors: Manuel Londa Vueba Ana Figueiras Luis Alberto Torres Goméz

Traditional drug design methods based on trial and error are costly and inefficient. The computational approach ToSS-MoDE (Topological Substructural Molecular Design) offers an alternative by linking molecular descriptors to biological activity. To develop a QSAR model to predict the anti-inflammatory activity of synthetic and natural compounds using weighted spectral moments. Spectral moments (µk) were calculated from the adjacency matrix between bonds for 410 compounds (180 active and 230 inactive). MODESLAB software (MICROSOFT OFFICE 365) was used to generate descriptors, and Linear Discriminant Analysis (LDA) was applied to classify activity. The model was validated with an external series of 62 compounds. Results. The model showed an overall classification of 91.59% in the training series and 90.2% in validation. The spectral moments µ0, µ3, µ4, and µ5 were the most significant. Diosgenin, a natural metabolite, showed potential anti-inflammatory activity (classification probability: 81%). The model showed strong training performance (91.7% accuracy) and promising external performance for confidently classified compounds. All datasets, descriptor-generation settings, coefficients, and posterior probabilities are fully described in the main text to ensure full reproducibility.

Biophysica doi: 10.3390/biophysica6010015

Authors: Ahlam Azalmad Mehdi El Ouartiti Mohamed Abour Mohamed Hilal

This retrospective planning study evaluated how arc number (AN) and control-point density (CP) affect VMAT quality, radiobiological endpoints, and workflow efficiency for locally advanced cervical cancer in a resource-conscious setting. Twenty-one patients (FIGO IIB–IIIB) were replanned in Monaco v5.51 (Monte Carlo) for 46 Gy using 6-MV beams (Elekta) with 1–4 coplanar arcs, and dual-arc plans were further analyzed using ≈250, 300, 350, and 400 CP per arc. Target coverage (D98/D95/V95/V98), conformity and homogeneity (CI, HI), and organs-at-risk (OARs) DVH metrics (including D2cc and Vx) were compared alongside monitor units, planning time, and delivery time. Increasing AN improved dose conformity and OAR sparing relative to single-arc plans, whereas increasing CP produced only modest dosimetric changes but substantially increased planning and treatment times. Radiobiological modeling using BED/EQD2 and EUD-based LKB NTCP indicated negligible bladder risk (<0.01%) and low rectal risk (<0.2%), but a higher small-bowel NTCP (~26%) driven by hotspot-sensitive descriptors; Niemierko TCP estimates were similar between leading dual-arc CP settings. Overall, a dual-arc strategy with ~250 CP per arc provided the most practical balance between plan quality, estimated biological effect, and deliverability.

Biophysica doi: 10.3390/biophysica6010014

Authors: Juan S. Jiménez

Protein folding displays a very narrow range of stability energy as measured by the ΔG° value associated with the process of protein folding from the unfolded sequence of amino acids defining a particular protein. We have recently reported the Gaussian distribution of ΔG° values obtained from a Data Base, constituted by more than five hundred data points from protein folding processes. An average value of ΔG° = −30.9 kJ/mol was obtained. Considering that a protein solution may include thousands of hydrogen bonds in water solution, this is an extremely low value, approximately equivalent to two hydrogen bonds. The enthalpy–entropy compensation has been repeatedly used as the main empirical mechanism, based in classical thermodynamics, to explain the low energy involved in stabilizing proteins. I present here a different approach, based on the thermodynamics of steady states in open systems, in an attempt to complement the achievements obtained through the EEC. The main conclusions explain the narrow range of ΔG° values reported previously as a consequence of environmental conditions, such as the protein solubility, and the plausible concentration, “in vivo,” of both protein forms, folded and unfolded. Particularly relevant is the condition of increasing the entropy of irreversible processes inside adiabatic systems. It is also worth noting the observation that, according to the results obtained from the theoretical model used, any protein could be folded with slightly different stability values of ΔG°, following the theorem of minimum entropy production rate.

Biophysica doi: 10.3390/biophysica6010013

Authors: Arturo Ponce

Ion channels are fundamental membrane proteins that mediate selective ion flow across biological membranes and thereby govern excitability, signaling, and homeostasis in virtually all cell types. Although channel function is determined by intrinsic structural features, the surrounding lipid milieu is now recognized as a decisive regulatory layer. Lipids tune ion channel activity through complementary mechanisms: they can bind directly to channel proteins, reshape bilayer physical properties, or act as signaling messengers that couple extracellular cues to channel gating. In addition, the organization of membranes into lipid microdomains such as rafts and caveolae can cluster channels with receptors and scaffolds, enhancing signaling specificity and efficiency. Recent advances in cryo-electron microscopy and molecular simulations have expanded our understanding of these lipid–channel interactions, revealing lipids as active modulators rather than passive structural components. This review provides a comprehensive overview of the principles by which lipids regulate ion channel function and highlights the biological and potential clinical significance of this fundamental interplay.

Biophysica doi: 10.3390/biophysica6010012

Authors: Indu Passi Nisha Bansal Thakur Gurjeet Singh Bhupinder Kumar

Neurodegenerative conditions such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis (ALS) are devastating disorders with the gradual loss of neurons and cognitive or motor disability. This is a review article that develops the crucial functions of autophagy and proteostasis within the scope of the neurodegenerative disease. Autophagy is a very well-conserved cell process that poses a quality control checkpoint that allows for the degradation and recycling of damaged organelles and misfolded proteins. Chaperones, the ubiquitin–proteasome complexes, and endoplasmic reticulum-associated degradation (ERAD) are also referred to as proteostasis, which plays a key role in ensuring the correct protein folding properties and the prevention of toxic protein accumulation. This article offers a detailed discussion of the relationship between autophagy and proteostasis, illustrating the mechanisms of mutual cooperation of these processes, ensuring cellular homeostasis and inhibiting the formation of pathogenic protein aggregates. In addition, this review includes experimental data during preclinical studies and clinical trials and expounds on the therapeutic opportunities that show the potential of targeting autophagy and proteostasis to counter neurodegenerative disorders. Although research progress creates potential for new indicators, the issues and difficulties relating to the effects of regulating such complex cellular pathways are also discussed in the article. Finally, the review can add to the research of neurodegenerative disease mechanisms of autophagy and proteostasis as well as provide insights about the future of treatment and its implementation.

Biophysica doi: 10.3390/biophysica6010011

Authors: Anju Kumari Kuldeep Singh Seemasundari Yumlembam Hamidur Rahaman Mohd Saquib Ansari Laishram Rajendrakumar Singh

Peroxiredoxin 6 (Prdx6) is a bifunctional antioxidant enzyme with glutathione peroxidase and phospholipase A2 activities that plays an essential role in cellular redox regulation. However, the modulation of Prdx6 activity by endogenous small metabolites remains poorly understood. In this study, we investigated the effect of β alanine on Prdx6 structure and function using biochemical, biophysical, computational, and cellular approaches. Enzymatic assays revealed that β alanine enhances the peroxidase activity of Prdx6 in a dose-dependent manner. Spectroscopic analyses demonstrated β alanine-induced conformational stabilization of Prdx6, which was further supported by increased thermal stability. Molecular docking and molecular dynamics simulations identified a stable interaction of β alanine at a distinct allosteric site on Prdx6, accompanied by reduced local flexibility. In a proof-of-concept cellular system, β alanine treatment resulted in a significant reduction in intracellular reactive oxygen species, consistent with enhanced Prdx6-associated antioxidant activity. Collectively, these findings identify β alanine as a biochemical modulator of Prdx6 activity. The study is limited to mechanistic and cellular redox regulation and does not address tissue- or disease-specific physiology.

Biophysica doi: 10.3390/biophysica6010010

Authors: Shujie Yang Shuangling Zhang Min Chen Dongxiao Ma Yuxuan Sun Xiao Zhang Jing Zhang Xiaohang Zheng Han Zheng

Fish collagen is derived from processing residues of marine and freshwater fish (such as fish skin, scales, and bones), primarily composed of amino acids including glycine, proline, and hydroxyproline. It functions include maintaining tissue integrity and promoting cell proliferation and repair. Extraction methods primarily include acid, alkali, enzymatic, and physical approaches, while purification techniques involve gel filtration chromatography, ultrafiltration, and precipitation. Furthermore, thermal instability, insufficient mechanical strength, immunological concerns, and biocompatibility limitations restrict its application across various fields. This review summarizes the composition, extraction, purification, and existing challenges of fish collagen, proposing improvement strategies. It systematically addresses issues related to fish collagen’s biocompatibility, filling a gap in the literature. However, effectively enhancing its biocompatibility remains an urgent priority. Approaches such as nanotechnology and composite material development offer novel avenues for improving biocompatibility and future applications.

Biophysica doi: 10.3390/biophysica6010009

Authors: Gabriel Gonzalo Taco-Gárate Sandra Esther Loa-Guizado Corina Vera-Gonzales Herly Fredy Zegarra-Aragon Juan Aquino-Puma Carlos Alberto Arenas-Chávez

Cancer is one of the leading causes of mortality worldwide, with breast and colon cancers being among the most common neoplasms in men and women, respectively. Despite significant advancements in treatment, there is a pressing need to enhance specificity and reduce systemic side effects. Importantly, a distinctive feature of cancer cells is their acidic extracellular environment, which profoundly influences cancer progression. In this study, we evaluated the anticancer activity of a pH-sensitive nanocomposite based on silver nanoparticles and pegylated carboxymethyl chitosan (AgNPs-CMC-PEG) in breast cancer (MCF-7) and colon cancer (HCT 116) cell lines. To achieve this, we synthesized and characterized the nanocomposite using UV-Vis spectroscopy, Dynamic Light Scattering (DLS), Fourier-Transform Infrared Spectroscopy (FT-IR), and Scanning Electron Microscopy (STEM-in-SEM). Furthermore, we assessed cytotoxic effects, apoptosis, and reactive oxygen species (ROS) generation using MTT, DAPI, and H2DCFDA assays. Additionally, we analyzed the expression of DNA methyltransferases (DNMT3a) and histone acetyltransferases (MYST4, GCN5) at the mRNA level using RT-qPCR, along with the acetylation and methylation of H3K9ac and H3K9me2 through Western blot analysis. The synthesized nanocomposite demonstrated an average hydrodynamic diameter of approximately 175.4 nm. In contrast, STEM-in-SEM analyses revealed well-dispersed nanoparticles with an average core size of about 14 nm. Additionally, Fourier-transform infrared (FTIR) spectroscopy verified the successful surface functionalization of the nanocomposite with polyethylene glycol (PEG), indicating effective conjugation and structural stability. The nanocomposite exhibited a pH and concentration dependent cytotoxic effect, with enhanced activity observed at an acidic pH 6.5 and at concentrations of 150 µg/ml, 75 µg/ml, and 37.5 µg/ml for both cell lines. Notably, the nanocomposite preferentially induced apoptosis accompanied by ROS generation. Moreover, expression analysis revealed a decrease in H3K9me2 and H3K9ac in both cell lines, with a more pronounced effect in MCF-7 at an acidic pH. Furthermore, the expression of DNMT3a at the mRNA level significantly decreased, particularly at acidic pH. Regarding histone acetyltransferases, GCN5 expression decreased in the HCT 116 line, while MYST4 expression increased in the MCF-7 line. These findings demonstrate that the AgNPs-CMC-PEG nanocomposite has therapeutic potential as a pH-responsive nanocomposite, capable of inducing significant cytotoxic effects and altering epigenetic markers, particularly under the acidic conditions of the tumor microenvironment. Overall, this study highlights the advantages of utilizing pH-sensitive materials in cancer therapy, paving the way for more effective and targeted treatment strategies.

Biophysica doi: 10.3390/biophysica6010008

Authors: Salvatore Passarella

Mitochondria serve as central hubs of cellular metabolism, integrating catabolic and anabolic pathways through the controlled exchange of metabolites across their membranes. Although mitochondrial transport of several metabolites has been well documented, the mechanisms underlying the trafficking of fumarate, glutamine, and phosphoenolpyruvate as well as the role of the mitochondrial pyruvate kinase remain insufficiently represented in modern biochemistry textbooks. Here, we revisit the biochemical evidence supporting specific transport activities for these metabolites, discuss their physiological roles in major metabolic pathways, and highlight how foundational experimental studies have been overlooked in contemporary literature. Re-examining these mechanisms provides new insight into the dynamic interplay between mitochondrial function, cytosolic metabolism, and overall cellular homeostasis.

Biophysica doi: 10.3390/biophysica6010007

Authors: Yanara Alessandra Santana Moura Andreza Pereira de Amorim Maria Carla Santana de Arruda Marllyn Marques da Silva Ana Lúcia Figueiredo Porto Vladimir N. Uversky Raquel Pedrosa Bezerra

Thrombosis is a cardiovascular disease characterized by the pathological formation of a fibrin clot in blood vessels. Currently available fibrinolytic enzymes have some limitations, including severe side effects, high cost, short half-life, and low fibrin specificity. Proteins from microalgae and cyanobacteria have various biological effects and are emerging as promising sources for fibrinolytic enzymes. In this study, bioinformatics tools were used to evaluate the intrinsic disorder predisposition of microalgal fibrinolytic proteins, their capability to undergo liquid–liquid phase separation (LLPS), and the presence of disorder-based functional regions, and short linear motifs (SLiMs). Analysis revealed that these proteins are predominantly hydrophilic and exhibit acidic (pI 3.96–6.49) or basic (pI 8.05–11.0) isoelectric points. Most of them are expected to be moderately (61.4%) or highly disordered proteins (6.8%) and associated with LLPS, with nine proteins being predicted to behave as droplet drivers (i.e., being capable of spontaneous LLPS), and twenty-five proteins being expected to be droplet clients. These observations suggest that LLPS may be related to the regulation of the functionality of microalgal fibrinolytic proteins. The majority of these proteins belong to the blood coagulation inhibitor (disintegrin) 1 hit superfamily, which can inhibit fibrinogen binding to integrin receptors, preventing platelet aggregation. Furthermore, the SLiM-centered analysis indicated that the main motifs found in these proteins are MOD_GlcNHglycan and CLV_PCSK_SKI1_1, which can also play different roles in thrombolytic activity. Finally, Fisher and conservation analysis indicated that CLV_NRD_NRD_1, CLV_PCSK_FUR_1, CLV_PCSK_PC7_1, and MOD_Cter_Amidation motifs are enriched in intrinsically disordered regions (IDRs) of these proteins, showing significant conservation and suggesting compatibility with proteolytic activation and post-translational processing. These data provide important information regarding microalgal proteins with potential thrombolytic effects, which can be realized through protein–protein interactions mediated by SLiMs present in intrinsically disordered regions (IDRs). Additional analyses should be conducted to confirm these observations using experimental in vitro and in vivo approaches.

Biophysica doi: 10.3390/biophysica6010006

Authors: Liqun Zhang

ORF8 is the second most mutated protein in SARS-CoV-2. It can form oligomers such as trimers and can bind to the IL-17RA/RC receptor. To understand the possible role of ORF8 in SARS-CoV-2, the first step of this study involved predicting the ORF8 trimer structure and the complex structure of the ORF8 monomer bound to the IL-17RA receptor using docking and molecular dynamics simulation methods. It was found that ORF8 molecules bound to the central ORF8 molecule through covalent and noncovalent interactions exhibit similar RMSD and RMSF values as the central ORF8 molecule and form a similar buried surface area, but display different numbers of hydrogen bonds and varying dynamic correlations. Additionally, trimer formation increases the dynamic correlation of the noncovalently bound ORF8 unit. ORF8 can bind with the IL-17RA receptor stably. Regions on ORF8, including C25–I47, L60–S67, T80–C90, and S103–E110, and regions on IL-17RA, including L1–H63 and D122–M165, are involved in the binding interface of the complex. ORF8 becomes less rigid when bound to IL-17RA than in its monomer, dimer, and trimer forms. Based on dihedral angle correlation predictions, binding of ORF8 to IL-17RA reduces internal correlations within ORF8 while strengthening correlations within IL-17RA. The G50–T80 region of ORF8 appears to be critical for interaction with IL-17RA, and the L1–V150 region of IL-17RA should be critical for its dynamics once bound to ORF8. These results help elucidate the structure and dynamics of ORF8 in SARS-CoV-2.

Biophysica doi: 10.3390/biophysica6010005

Authors: Melissa L. Knothe Tate Sara McBride-Gagyi Eric J. Anderson Lucy Ngo

Here we present a retrospective, integrative review of the approaches and discoveries of our “collaboratory”, a meta-laboratory comprising cross-disciplinary collaborations across laboratories at fourteen different universities and clinics in seven different countries with shared lead investigators. By tying together insights from four decades of research and discovery, applied across cell types, as well as different tissues, organ systems, and organisms, we have aimed to elucidate the interplay between organisms’ movement and the physiology of their tissues, organs, and organ systems’ resident cells. We highlight the potential of increasing imaging and computing power, as well as machine learning/artificial intelligence approaches, to delineate the Laws of Biology. Codifying these laws will provide a foundation for the future, to promote not only the discovery of underpinning mechanisms but also the sustainability of our natural resources, from our brains to our bones, which serve as veritable “hard drives”, physically rendering a lifetime of cellular experiences and millennia of evolution.

Biophysica doi: 10.3390/biophysica6010004

Authors: William P. Heaps Anne Elise Packard Kristina M. McCammon Tyler P. Green Joseph P. Talley Bradley C. Bundy Dennis Della Corte

The glomerular filtration barrier poses a significant challenge for circulating proteins, with molecules below ~60–70 kDa facing rapid renal clearance. Endogenous proteins have evolved sophisticated evasion mechanisms including oligomerization, carrier binding, electrostatic repulsion, and FcRn-mediated recycling. Understanding these natural strategies provides blueprints for engineering therapeutic proteins with improved pharmacokinetics. This review examines how endogenous proteins resist filtration, evaluates their application in protein engineering, and discusses clinical translation including established technologies (PEGylation, Fc-fusion) and emerging strategies (albumin-binding domains, glycoengineering). We address critical challenges of balancing half-life extension with tissue penetration, biological activity, and immunogenicity—essential considerations for the rational design of next-generation therapeutics with optimized dosing and enhanced efficacy.

Biophysica doi: 10.3390/biophysica6010003

Authors: Sadia Tina Oussama Khibech Ali Zourif Samy Iskandar Kettani Halabi Mohamed Martin Ndayambaje Balouch Lhousaine Meryem El Jemli

Cedrus atlantica wood tar (CAWT) is traditionally used as a medicinal product, especially in low- and middle-income countries. Despite its traditional use, scientific support for its efficacy remains limited. This study evaluated the biological properties of CAWT using an integrated approach that combined qualitative and quantitative phytochemical analysis, disc diffusion and microdilution tests for antimicrobial assays (disc diffusion and microdilution), antioxidant activity (DPPH and ferric-reducing power assays), in silico ADMET/toxicity, docking, and MD/MMGBSA and provided a balanced comparison with reference antioxidants. This study demonstrated that CAWT is rich in secondary metabolites linked to biological activity, including polyphenols (307.39 ± 58.45 mg GAE/g), tannins (124.42 ± 6.14 mg TAE/g), and flavonoids (15.62 ± 2.53 mg QE/g). For free radical scavenging, CAWT inhibited DPPH with an IC50 of 19.781 ± 2.51 µg/mL and showed ferric-reducing activity with an IC50 of 83.7 ± 2.88 µg/mL for its antimicrobial activity against Pseudomonas aeruginosa; inhibition zones reached 35.66 ± 0.58 mm. In silico analysis, Swiss ADMET and pkCSM predicted ≥94% intestinal absorption, no cytochrome P450 liabilities, and low acute toxicity for six dominant terpenoids. Docking pinpointed trans-cadina-1(6),4-diene and α/β-himachalene as high-affinity ligands of LasR and gyrase B (ΔG ≈ −8 kcal mol−1). A 100 ns GROMACS run confirmed stable hydrophobic locking of the lead LasR complex (RMSD 0.22 nm), while MM/GBSA calculated a dispersion-dominated binding free energy of −37 kcal mol−1. Overall, CAWT showed in vitro antioxidant activity (DPPH and ferric-reducing assays) and inhibitory effects in disc diffusion assays, while in silico predictions for major terpenoids suggested favorable oral absorption and low acute toxicity. However, chemical composition analysis and bio-guided fractionation are necessary to confirm the antimicrobial activity and to validate the compounds responsible for the observed effects.

Biophysica doi: 10.3390/biophysica6010002

Authors: Adhikarimayum Priya Devi Seemasundari Yumlembam Kuldeep Singh Akshita Gupta Kananbala Sarangthem Laishram Rajendrakumar Singh

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by memory loss, cognitive decline, and oxidative stress-driven neuronal damage. Catalase, a key antioxidant enzyme, plays a vital role in decomposing hydrogen peroxide (H2O2) into water and oxygen, thereby protecting neurons from reactive oxygen species (ROS)-mediated toxicity. In AD, the catalase function is compromised due to reduced enzymatic activity and aggregation, which not only diminishes its protective role but also contributes to amyloid plaque formation through catalase-Aβ co-oligomers. Hence, therapeutic strategies aimed at simultaneously preventing catalase aggregation and enhancing its enzymatic function are of great interest. In this study, we screened twelve naturally occurring metabolites for their ability to modulate catalase aggregation and activity. Among these, dimethylglycine (DMG) emerged as the most potent candidate. DMG significantly inhibited thermally induced aggregation of catalase and markedly enhanced its enzymatic activity in a concentration-dependent manner. Biophysical analyses revealed that DMG stabilizes catalase by promoting its native folded conformation, as evidenced by increased melting temperature (Tm), higher Gibbs free energy of unfolding (ΔG°), and reduced exposure of hydrophobic residues. TEM imaging and Thioflavin T assays further confirmed that DMG prevented amyloid-like fibril formation. Molecular docking and dynamics simulations indicated that DMG binds to an allosteric site on catalase, providing a structural basis for its dual role in stabilization and activation. These findings highlight DMG as a promising therapeutic molecule for restoring catalase function and mitigating oxidative stress in AD. By maintaining catalase stability and activity, DMG offers potential for slowing AD progression.

Biophysica doi: 10.3390/biophysica6010001

Authors: Ossama Daoui Achraf Daoui Mohamed Yamni Marouane Daoui Souad Elkhattabi Samir Chtita Chakir El-Kasri

Making advancements in Quantitative Structure-Activity Relationship (QSAR) modeling is crucial for predicting biological activities in new compounds. Traditional 2D-QSAR and 3D-QSAR methods often face challenges in terms of computational efficiency and predictive accuracy. This study introduces a machine learning approach using 3D Discrete Tchebichef Moments (3D-DTM) to address these issues. The 3D-DTM method offers efficient computation, robust descriptor generation, and improved interpretability, making it a promising alternative to conventional QSAR techniques. By capturing global 3D shape information, this method provides better representation of molecular interactions essential for biological activities. We applied the 3D-DTM model to a dataset of 46 molecules derived from the Dihydrophenanthrene scaffold, screened against the enzymatic activity of 3-chymotrypsin-like protease, a key antiviral target. Principal Component Analysis and k-means clustering refined descriptors, followed by stepwise Multiple Linear Regression (step-MLR), Partial Least Squares Regression (PLS-R), and Feed-Forward Neural Network (FFNN) techniques for 3DTMs-QSAR model development. The results showed high correlation and predictive accuracy, with significant validation from internal and external tests. The step-MLR model emerged as the optimal method due to its balance of predictive power and simplicity. Validation through y-Randomization and applicability domain analysis confirmed the model’s robustness. Virtual screening of 100 novel compounds identified 32 with improved pIC50 values. This study highlights the potential of 3D-DTMs in QSAR modeling, providing a scalable and reliable tool for computational chemistry and drug discovery. A user-friendly software tool was also developed to facilitate 3D-DTM extraction from input 3D molecular images.

Biophysica doi: 10.3390/biophysica5040063

Authors: Asmaa Al-Failakawi Aishah Al-Jarallah Muddanna Rao Islam Khan

We investigated the roles and regulation of contractile and sodium ion transporter proteins in the pathogenesis of diarrhea in the acute ulcerative colitis. Acute ulcerative colitis was induced in male Sprague-Dawley rats using dextran sulfate sodium (DSS) in drinking water for seven days. The effects of nobiletin, a citrus flavonoid, were also examined. Increased myeloperoxidase activity, colon mass, and inflammatory cell infiltration were associated with damage to goblet cells and the epithelial cell lining indicating the development of acute ulcerative colitis. SERCA-2 calcium pump expression remained unchanged, whereas the phospholamban (PLN) regulatory peptide was reduced and its phosphorylated form (PLN-P) increased, suggesting a post-translational increase in SERCA-2 activity in the inflamed colon. Higher levels of IP3 were associated with a decrease in the Gαq protein levels without altering phospholipase C expression, suggesting that IP3 regulation is independent of Gαq protein signaling. In addition, the expression of sodium/hydrogen exchanger isoforms NHE-1, NHE-3 and carbonic anhydrase-1 and sodium pump activity were decreased in the inflamed colon. Nobiletin treatment of colitis selectively reversed the inflammatory and oxidative stress markers, including superoxide dismutase and catalase without restoring the expression of ion transporters. This study highlights alterations in the expression of ion transporters and their regulatory proteins in acute ulcerative colitis. These changes in the ion transporters are likely to reduce NaCl absorption and alter contractility, thereby contributing to the pathogenesis of diarrhea in the present model of acute ulcerative colitis. Nobiletin selectively ameliorates acute colitis in this model.

Biophysica doi: 10.3390/biophysica5040062

Authors: Sakib Mohammad Md Sakhawat Hossain Sydney L. Sarver

Mechanobiology explores how physical forces and cellular mechanics influence biological processes. This field has experienced rapid growth, driven by advances in high-resolution imaging, micromechanical testing, and computational modeling. At the same time, the increasing complexity and volume of mechanobiological imaging and measurement data have made traditional analysis methods difficult to scale. Artificial intelligence (AI) has emerged as a practical tool to address these challenges by providing new methods for interpreting and predicting biological behavior. Recent studies have demonstrated potential in several areas, including image-based analysis of cell and nuclear morphology, traction force microscopy (TFM), cell segmentation, motility analysis, and the detection of cancer biomarkers. Within this context, we review AI applications that either incorporate mechanical inputs/outputs directly or infer mechanobiologically relevant information from cellular and nuclear structure. This study summarizes progress in four key domains: AI/ML-based cell morphology studies, cancer biomarker identification, cell segmentation, and prediction of traction forces and motility. We also discuss the advantages and limitations of integrating AI/ML into mechanobiological research. Finally, we highlight future directions, including physics-informed and hybrid AI approaches, multimodal data integration, generative strategies, and opportunities for computational biophysics-aligned applications.

Biophysica doi: 10.3390/biophysica5040061

Authors: Zaria Booth Mazen Mezher Rudra Patel Venkat Maruthamuthu

Forces exerted by cells due to their internal contractility play fundamental roles in a host of processes, including adhesion, migration, survival and differentiation. Traction force microscopy (TFM) enables the determination of forces exerted by cells or cell collectives on their environment, which is typically taken to be an extra-cellular matrix (ECM)-coated substrate. Sample preparation for TFM involves the plating of cells onto an environment embedded with fiducial markers. The imaging of these fiducial markers in the presence and absence of the cells then enables calculation of the displacement of localized regions of the environment, and, consequently, the spatial distribution of forces exerted by the cells on their environment. Here, we consider the most widely used implementation of TFM (two-dimensional or 2D TFM) which enables the determination of in-plane forces exerted by cells plated on top of an elastic soft substrate. We present streamlined methods for preparing TFM substrates, with special consideration towards experimental steps involved in implementing it using an epifluorescence microscope. We highlight considerations involved in substrate choice between polyacrylamide (PAA) gels and soft silicones, fiducial marker (microbead) choice and distribution as well as microbead and ECM coupling to the substrate. We also point out caveats related to sub-optimal choices in the methodology which can affect the resultant traction force distribution, as well as further derived quantities such as inter-cellular forces in cell pairs computed using the traction force imbalance method (TFIM).

Biophysica doi: 10.3390/biophysica5040060

Authors: Deyvis Cabrini Teixeira Delfino Danton Diego Ferreira Margarete Marin Lordelo Volpato Vânia Aparecida Silva Renan Teixeira Delfino Christiano Sousa Machado de Matos Meline de Oliveira Santos

Water potential is an important indicator used to study water relations in plants, as it reflects the level of hydration in their tissues. There are different numerical variables that describe plant properties and can be acquired from leaf reflectance. The objective of this study was to estimate water potential in coffee plants using spectral variables. For this, a range of wavelengths that provided analytical flexibility was used. After this, machine learning techniques were employed to build data-driven models. The dataset used presents spectral characteristics (wavelength) of coffee plants, collected through the CI-710 Mini-Leaf Spectrometer equipment and also the water potential of each coffee plant, measured by the Scholander Chamber equipment. The dataset was divided into two crop management groups: irrigated and rainfed. Four machine learning techniques were implemented: Multi-Layer Perceptron (MLP), Decision Tree, Random Forest and K-Nearest Neighbor (KNN). The implementation of machine learning techniques followed two distinct strategies: regression and classification. The results indicate that the decision tree-based model demonstrated superior performance under irrigated conditions for regression tasks. In contrast, the KNN technique achieved the best performance for classification. Under rainfed conditions, the MLP model outperformed the other techniques for regression, while the Random Forest method exhibited the highest accuracy in classification tasks. While no hardware prototype was developed, the machine learning-based methods presented here suggest a possible pathway toward future intelligent, user-friendly, and accessible sensing technologies for coffee plantations.

Biophysica doi: 10.3390/biophysica5040059

Authors: Satoshi Migita

A rapid, colorimetric sensor for histamine detection is presented using citrate-stabilized gold nanoparticles enhanced with Cu2+ coordination. The sensing mechanism involves dual recognition: protonated histamine first adsorbs electrostatically onto AuNP surfaces at pH 5.5, followed by Cu2+-mediated coordination between imidazole rings that induces interparticle coupling, resulting in a characteristic shift of the localized surface plasmon resonance from 520 to 620 nm. The optical response, measured as the absorbance ratio A620/A520, exhibits excellent linearity over the range of 1.25–10 μM with a detection limit of 0.95 μM and total assay time under 30 min. The dual-recognition mechanism provides high selectivity for histamine over structural analogs, including L-histidine, imidazole, and L-lysine. The metal ion-mediated colorimetric approach described here achieves sub-micromolar sensitivity in simple buffer solutions, which is comparable to the histamine level used in in vitro cell assays and food-related studies. Thus, the present system is best viewed as a mechanistic model that can inform the design of future biosensing and analytical methods, rather than as a fully optimized sensor for direct clinical measurements in complex biofluids.

Biophysica doi: 10.3390/biophysica5040058

Authors: Andrew K. Morris Robert M. McCarrick Gary A. Lorigan

A topological analysis was performed by taking ESEEM measurements of site-specifically labeled E protein from SARS-CoV-2. The intensity of deuterium modulation arising from either deuterated solvent or deuterated lipid acyl chains revealed exposure to solvent or the bilayer hydrophobic region. Spin-labeled lipids and soluble spin labels were used as points of comparison. The data indicate that spin labels placed along the transmembrane helix of the E protein showed close contact with lipid acyl chains, but also substantial contact with solvent, while those placed on the C-terminal domain showed substantial but lower exposure to lipid acyl chains, with comparable solvent exposure. The results support the view that the C-terminal domain is in contact with the bilayer surface.

Biophysica doi: 10.3390/biophysica5040057

Authors: Xuanyi Zhang Zehua Wang Chenyang Wu Dongdong Lin

Protein droplets exhibit complex self-assembly and deposition behaviors driven by evaporation, which has attracted increasing attention in recent years. Under evaporation, limited volume and locally concentrated protein solutions can undergo liquid–liquid phase separation (LLPS) and liquid–liquid crystalline phase separation (LLCPS), inducing the formation of concentrated droplets and anisotropic structures. The combined effects of interfacial tension and internal flow field induce a variety of deposition patterns on the substrate, providing great significance for the development of functional biomaterials. This paper reviews the physical processes experienced by protein/fibril droplets during evaporation, focusing on the formation mechanism of evaporation and their phase separation behaviors. At the same time, the review systematically summarized the key factors affecting the deposition patterns, and a variety of methods were introduced to pattern deposition, such as external electric field and micro-structured substrates. Furthermore, the potential applications of proteins/fibrils droplet deposition were discussed in multiple fields. This review aims to provide systematic theoretical support and experimental reference for understanding and controlling the deposition behavior of proteins/fibrils droplets, and to promote their further application in functional materials and biomedical engineering.

Biophysica doi: 10.3390/biophysica5040056

Authors: Endris M. Endris Deresse A. Adem Horace T. Crogman Daniel B. Erenso

We present a proof-of-concept study using a laser trapping (LT) approach to characterize hemoglobin variants through controlled dielectric breakdown of red blood cell membranes. Using a 1064 nm infrared laser, we analyzed 62 cells from each of four hemoglobin types (Hb AS, Hb FA, Hb FSC, Hb AC), measuring the ionization time, cell area, and trap displacement to calculate the apparent threshold ionization energy (TIE*) and apparent threshold radiation dose (TRD*). Post-ionization trajectories and radiation intensity measurements provided charge distribution profiles for each variant. Our results indicate variant-specific differences in TRD* and charge-to-volume ratios across adults and infants (p < 0.05), while the TIE* values remained largely consistent. Charge analysis revealed statistically significant variation between some groups, suggesting that TRD* and charge-based parameters may offer sensitive markers of hemoglobin heterogeneity. This work demonstrates the feasibility of laser trapping as a complementary single-cell method for hemoglobin analysis. While limited in sample size, the approach highlights the potential of TIE* and TRD* measurements for differentiating hemoglobin variants and suggests future applications in hemoglobinopathy screening and diagnostic research.

Biophysica doi: 10.3390/biophysica5040055

Authors: Lyubov Filatova

The combination of antimicrobial agents with different mechanisms of action is an important step in the fight against drug-resistant microorganisms. In this study, the interaction of the lysozyme enzyme with ampicillin and colistin was investigated. These antibiotics are highly effective against Gram-positive (ampicillin) and Gram-negative (colistin) pathogenic microorganisms. Spectroscopic and kinetic methods and molecular docking were used in the research. The results of the spectroscopic analysis confirmed the intermolecular interaction of lysozyme with ampicillin or colistin. The formation of the lysozyme complex with ampicillin was accompanied by mixed quenching of the enzyme fluorescence and changes in its secondary structure (a slight decrease in the content of α-helices). The interaction of lysozyme with colistin was complemented by dynamic quenching of the enzyme fluorescence. The method of molecular docking established that the interactions of lysozyme with colistin were predominantly van der Waals, while hydrogen bonds predominated in the lysozyme complex with ampicillin. Despite the presence of interactions of ampicillin and colistin with amino acid residues from the active site of lysozyme, this did not affect its ability to cause destruction of bacterial cell walls. The results obtained can be used in the development of antibacterial drugs.

Biophysica doi: 10.3390/biophysica5040054

Authors: Chih-Hao Huang Feras A. Batarseh Aman Ullah

Early and accurate diagnosis of Alzheimer’s disease (AD) is critical for patient outcomes yet presents a significant clinical challenge. This study evaluates the effectiveness of four machine learning models—Logistic Regression, Random Forest, Support Vector Machine, and a Feed-Forward Neural Network—for the five-class classification of AD stages. We systematically compare model performance under two conditions, one including cognitive assessment data and one without, to quantify the diagnostic value of these functional tests. To ensure transparency, we use SHapley Additive exPlanations (SHAPs) to interpret the model predictions. Results show that the inclusion of cognitive data is paramount for accuracy. The RF model performed best, achieving an accuracy of 84.4% with cognitive data included. Without this, performance for all models dropped significantly. SHAP analysis revealed that in the presence of cognitive data, models primarily rely on functional scores like the Clinical Dementia Rating—Sum of Boxes. In their absence, models correctly identify key biological markers, including PET (positron emission tomography) imaging of amyloid burden (FBB, AV45) and hippocampal atrophy, as the next-best predictors. This work underscores the indispensable role of cognitive assessments in AD classification and demonstrates that explainable AI can validate model behavior against clinical knowledge, fostering trust in computational diagnostic tools.

Biophysica doi: 10.3390/biophysica5040053

Authors: Vladimir B. Krapivin Roman A. Stepanyuk Maria G. Khrenova

Fluorescent proteins find application as biocompatible, genetically encoded labels for visualization of living organisms tissues. Green fluorescent proteins (GFPs) are the most diverse, but proteins with red fluorescence have advantages, such as lower phototoxicity and better penetration into biological tissues. A promising approach is to obtain red fluorescent proteins (RFPs) from GFPs by introducing mutations that stabilize the oxidized chromophore state with an extended conjugated π-system. However, to date this remains a non-trivial task and experimental developments are carried out mainly by random mutagenesis. Development of descriptors obtained in molecular modeling can rationalize this field. Herein, we rely on experimental data on the AzamiGreen fluorescent protein and its variants that are oxidized to the red form. We perform classical molecular dynamics (MD) and combined quantum mechanics/molecular mechanics (QM/MM) simulations to determine structural and dynamic features that govern oxidation. We demonstrate that the red state is predominantly stabilized by interactions of polar lysine residues with chromophore oxygen atoms. Dynamic network analysis demonstrates that in red fluorescent proteins the chromophore motions are correlated with the movement of surrounding protein side chains to a higher extent than in green variants. The presence of different resonance forms of the chromophore determines the fluorescence band maximum value: a decrease in the phenolate form population leads to the red shift.

Biophysica doi: 10.3390/biophysica5040052

Authors: Kunal Bhattacharya Pukar Khanal Jagdish Chand Nongmaithem Randhoni Chanu Dibyajyoti Das Atanu Bhattacharjee

Alzheimer’s disease is driven by multiple molecular drivers, including the pathological behavior of two intrinsically disordered proteins, amyloid-β (Aβ) and tau, whose aggregation is regulated by sequence-encoded ensembles and liquid–liquid phase separation (LLPS). This review integrates recent advances in biophysics, structural biology, and computational modeling to provide a multiscale perspective on how sequence determinants, post-translational modifications, and protein dynamics regulate the conformational landscapes of Aβ and tau. We discuss sequence-to-ensemble principles, from charge patterning and aromatic binders to familial mutations that reprogram structural ensembles and modulate LLPS. Structural studies, including NMR, SAXS, cryo-EM, and cryo-electron tomography, trace transitions from disordered monomers to fibrils and tissue-level structures. We highlight experimental challenges in LLPS assays, emerging standards for reproducibility, e.g., LLPSDB, PhaSePro, and FUS benchmarks, and computational strategies to refine and condensate modeling. Finally, we explore the therapeutic implications, including condensate-aware medicinal chemistry, ensemble-driven docking, and novel insights from clinical trials of anti-Aβ antibodies. Together, these perspectives underscore a paradigm shift toward environment- and ensemble-aware therapeutic design for Alzheimer’s and related protein condensation disorders.

Biophysica doi: 10.3390/biophysica5040051

Authors: Arpan Roy Sydney Sarver Jarod Beights Sean Brennan Sazid Noor Rabi Sakib Mohammad Kyu Young Han Sabrina Nilufar Farhan Chowdhury

Innate immunity is the body’s first line of defense for mounting robust antiviral signaling. However, the role of cytoskeletal prestress, a hallmark of cellular mechanotransduction, in regulating innate immune pathways such as retinoic acid-inducible gene I (RIG-I) signaling remains poorly understood. Herein, we show that cells on soft vs. rigid substrates elicit cytoskeletal prestress-dependent activation of RIG-I signaling, leading to differential type-I interferon (IFN) gene expression. Cells were cultured on soft (0.6 kPa) and stiff (8.5 kPa) substrates to modulate cellular traction and prestress, followed by transfection of Poly(I:C), a synthetic viral dsRNA mimic, to measure the RIG-I-mediated innate immune response. Cells on soft substrates show minimal activation of RIG-I signaling, resulting in low expression of IFN-β1 and other IFN-stimulated genes (ISGs), compared to cells on stiff substrates. We further demonstrate that activation of TANK Binding Kinase 1 (TBK1), a downstream effector of the RIG-I pathway, is inhibited in cells on soft substrates due to the cytoplasmic sequestration of the Yes-associated protein (YAP), a HIPPO pathway effector protein. In contrast, cells on stiffer substrates experienced decreased TBK1 inhibition due to the nuclear localization of YAP and exhibited elevated TBK1 activation and heightened IFN and ISG expressions. Together, we demonstrate that cytoskeletal prestress represents a key biophysical regulator of innate immune signaling.

Biophysica doi: 10.3390/biophysica5040050

Authors: Pornthep Sompornpisut Linh Truong Hoai Panisak Boonamnaj Brian G. Olson Ras B. Pandey

Large-scale computer simulations were employed to investigate the conformational response of the spike protein components S1 and S2 using a coarse-grained model. Temperature was systematically varied to assess the balance between stabilizing residue–residue interactions and thermal fluctuations. The resulting contact profiles reveal distinct segmental reorganization and self-assembly behaviors between S1 and S2. At lower, thermoresponsive temperatures, pronounced segmental globularization occurs in the N-terminal domain (NTD; M153–K202) and receptor-binding domain (RBD; E406–E471) of S1, whereas S2 exhibits alternating regions of high and low contact density. Increasing temperature reduces this segmental globularization, leaving only minor persistence at elevated temperatures. The temperature dependence of the radius of gyration (Rg) further demonstrates the contrasting thermal behaviors of S1 and S2. For S1, Rg increases continuously and monotonically with temperature, reaching a steady-state value approximately 50% higher than that at low temperature. In contrast, S2 displays a non-monotonic response: Rg initially rises to a maximum nearly sevenfold higher than its low-temperature value, then decreases with further temperature increase. Scaling analysis of the structure factor reveals that the globularity of S1 diminishes significantly upon heating, while S2 becomes modestly more compact yet retains its predominantly fibrous character.

Biophysica doi: 10.3390/biophysica5040048

Authors: Daria Kondrakhova Vladimíra Tomečková Oleksandr Dobrozhan Ondrej Milkovič Hoydoo You Tatiana Kimáková Vladimír Komanický

This study explored the use of physical methods, namely X-ray diffraction, atomic force microscopy, and energy-dispersive X-ray spectroscopy, to analyze the structure and composition of tear fluid desiccates. Tear samples were collected from patients with dry eye syndrome, glaucoma, and multiple sclerosis. Our results revealed significant differences in the crystallization patterns, chemical composition, and morphology of tear fluid among the disease groups compared to healthy individuals. XRD analysis identified variations in salt crystallization within tear fluid desiccates. AFM provided nanoscale morphological visualization. EDX determined the presence of key chemical elements. Our findings showed that changes in crystallization and unbalance of ionic composition in tear fluid may serve as potential markers for diagnosing ocular diseases. This study highlights the potential of these techniques for non-invasive diagnostics and contributes to the development of innovative strategies for monitoring structural properties in tear fluid desiccates of analyzed inflammatory, and neurodegenerative diseases.

Biophysica doi: 10.3390/biophysica5040049

Authors: Karen Isela Vargas-Rubio Efrén Delgado Cristian Patricia Cabrales-Arellano Claudia Ivette Gamboa-Gómez Damián Reyes-Jáquez

Microencapsulation is a fundamental technology for protecting active compounds from environmental degradation by factors such as light, heat, and oxygen. This process significantly improves their stability, bioavailability, and shelf life by entrapping an active core within a protective matrix. Therefore, a thorough understanding of the physicochemical interactions between these components is essential for developing stable and efficient delivery systems. The composition of the microcapsule and the encapsulation method are key determinants of system stability and the retention of encapsulated materials. Recently, the application of computational tools to predict and optimize microencapsulation processes has emerged as a promising area of research. In this context, molecular dynamics (MD) simulation has become an indispensable computational technique. By solving Newton’s equations of motion, MD simulations enable a detailed study of the dynamic behavior of atoms and molecules in a simulated environment. For example, MD-based analyses have quantitatively demonstrated that optimizing polymer–core interaction energies can enhance encapsulation efficiency by over 20% and improve the thermal stability of active compounds. This approach provides invaluable insights into the molecular interactions between the core material and the matrix, ultimately facilitating the rational design of optimized microstructures for diverse applications, including pharmaceuticals, thereby opening new avenues for innovation in the field. Ultimately, the integration of computational modeling into microencapsulation research not only represents a methodological advancement but also pivotal opportunity to accelerate innovation, optimize processes, and develop more effective and sustainable therapeutic systems.

Biophysica doi: 10.3390/biophysica5040047

Authors: Qiang Ma Liuqiang Zhu Xiang Li Dening Pei Lei Yu Xinchang Shi Yong Zhou Zhihao Fu Chenggang Liang Xi Qin Junzhi Wang

Human granulocyte colony-stimulating factor (hG-CSF) is primarily used to treat neutropenia induced by cancer chemotherapy and bone marrow transplantation. The current identification test for hG-CSF relies on Western blot (WB), a labor-intensive and technically demanding method. This study aimed to screen and prepare an anti-hG-CSF nanobody to identify and quantify hG-CSF, with the ultimate goal of developing colloidal gold-labeled nanobody test strips for rapid identification. An alpaca was immunized with hG-CSF, and the VHH gene sequence encoding the anti-hG-CSF nanobody was obtained through sequencing following phage display library construction and multiple rounds of biopanning. The nanobody C68, obtained from screening, was expressed by E. coli, and its physicochemical properties such as molecular weight, isoelectric point, and affinity were characterized after purification. WB analysis demonstrated excellent performance of the nanobody in identification tests in terms of specificity, limit of detection (LOD), applicability with products from various manufacturers, and thermal stability. Additionally, we established an ELISA method for hG-CSF quantification utilizing the nanobody C68 and conducted methodological validation. Finally, colloidal gold-based test strips were constructed using the nanobody C68, with a LOD of 30 μg/mL, achieving rapid identification for hG-CSF. This study represents a novel application of nanobodies in pharmaceutical testing and offers valuable insights for developing identification tests for other recombinant protein drugs.

Biophysica doi: 10.3390/biophysica5040046

Authors: Cornelius Rosenkranz Marianna Lucio Marion Ganslmayer Thomas Harrer Jakob Hoffmanns Charlotte Szewczykowski Thora Schröder Franziska Raith Stephanie Zellinger Denzel Abelardo Jule Schumacher Merle Flecks Petra Lakatos Christian Mardin Bettina Hohberger

Post-COVID-19 syndrome (PCS) is a multifactorial disorder comprising different subgroups. Our study aimed to investigate the longitudinal changes in retinal microcirculation in PCS patients. Eighty PCS patients were recruited at the Department of Ophthalmology at the Friedrich-Alexander University of Erlangen-Nürnberg. Retinal microcirculation was measured twice using optical coherence tomography angiography (OCT-A) within the superficial vascular plexus (SVP), intermediate capillary plexus (ICP), deep capillary plexus (DCP), and peripapillary region. Vessel density (VD) was calculated using the Erlangen Angio Tool with an APSified and Bruch’s membrane opening-based analyses. The least-squares means (LS-Means) of VD were 30.4 (SE = 0.168) vs. 30.3 (SE = 0.166) (SVP), 22.4 (SE = 0.143) vs. 22.2 (SE = 0.141) (ICP), 23.9 (SE = 0.186) vs. 23.8 (SE = 0.185) (DCP), and 27.4 (SE = 0.226) vs. 27.0 (SE = 0.224) (peripapillary) in patients with PCS at visits 1 and 2, respectively. The study cohort showed physically stable PCS symptoms with PEM/fatigue and concentration disorders as major symptoms and only a slight, clinically irrelevant improvement of the Bell Score. The multivariate longitudinal model confirmed the clinical observations by showing that VD did not change significantly during follow-up (p = 0.46). Strong interdependencies between the macular layers (p < 0.001) were observed. The data of the present study suggests that while overall APSified macular VD and BMO-based APSified peripapillary VD were stable within a PCS cohort of physically stable PCS symptoms, individual patients may experience coordinated microvascular changes, particularly within the macular plexuses. Together, the results support a model of heterogeneous yet biologically consistent microvascular response in PCS pathophysiology.

Biophysica doi: 10.3390/biophysica5040045

Authors: Shahnawaz Khijmatgar Matteo Pellegrini Martina Ghizzoni Massimo Del Fabbro

A systematic review was conducted to assess the effects of microgravity and space radiation on astronauts’ oral health. This review aimed to determine if these conditions increase the risk of dental and periodontal diseases, identify pre-mission dental care strategies, and specify relevant dental emergencies for astronauts to manage during missions. Following PRISMA guidelines, the review was registered on PROSPERO (CRD42023472765). Databases including PubMed, Scopus, Web of Science, Cochrane Library, and OVID Medline were searched. Of the 13 studies identified, 7 were eligible for qualitative synthesis. The included studies revealed that space conditions compromise oral health. Findings indicate changes in saliva composition, with a significant decline in salivary lysozyme levels during missions lasting 28 to 84 days. Salivary IgA levels also increased before and peaked after flights (microgravity alters fluid shear and protein folding). Viral reactivation was a key finding, with latent viruses such as Epstein–Barr virus (EBV), cytomegalovirus (CMV), and varicella zoster virus (VZV) being reactivated during missions (immune suppression and gene expression shifts under spaceflight stress). Data from a study found that 50% of crew members shed viruses in their saliva or urine, and 38% tested positive for herpesviruses. The included studies also documented alterations in the oral microbiome, including increased gastrointestinal and decreased nasal microbial diversity. This suggests alterations in salivary biomarkers, viral shedding, and microbiome changes in astronauts during long-duration missions. These changes appear associated with immune dysregulation and stress, but causality remains uncertain due to observational designs, small heterogeneous samples, and confounding factors. Although current evidence is indicative rather than definitive, these findings highlight the need for preventive dental measures prior to missions and preparedness for managing oral emergencies in-flight. Future studies should address the mechanistic separation of microgravity and radiation effects, with implications for upcoming Moon and Mars missions.

Biophysica doi: 10.3390/biophysica5040044

Authors: Marcela Ana Morini Viviana Isabel Pedroni

Myelin is a membranous structure critically important for human health. Historically, it was believed that myelin remained largely unchanged in the adult brain. However, recent research has shown that myelin is remarkably dynamic, capable of adjusting axonal conduction velocity and playing a role in learning, memory, and recovery from injury, in response to both physiological and pathological signals. Axons are more efficiently insulated in myelinated fibers, where segments of the axonal membrane are wrapped by the myelin sheath. Although extensive data are available on the electrical properties of myelin, its structural and mechanical characteristics—as well as the role of its lipid composition—are also relevant, although much less explored. The objective of our review is derived from this point since alterations in lipid components can lead to axonal dysfunction, giving rise to neurological disorders such as multiple sclerosis and other demyelinating conditions. In this review, concerning the lipid composition of myelin, we focus on two distinct classes of lipids: sphingolipids and long-chain fatty acids, emphasizing the differential contributions of saturated versus polyunsaturated species. We analyze studies that correlate the mechanical vulnerability of myelin with its lipid composition, particularly sphingomyelin, thereby underscoring its role in protecting neurons against physical stress and providing a robust microstructural network that reinforces the white matter as a whole. From a biochemical perspective, we examine the susceptibility of myelin to oxidative stress, metabolic disorders, and extreme nutritional deficiencies in relation to the role of long-chain fatty acids. Both perspectives highlight that the aforementioned lipids participate in a complex biomechanical balance that is essential for maintaining the stability of myelin and, consequently, the integrity of the central and peripheral nervous systems.

Biophysica doi: 10.3390/biophysica5040043

Authors: Asim Muhammad Xin-Yu Zheng Hui-Lin Gan Yu-Xin Guo Jia-Hong Xie Yan-Jun Chen Jin-Jun Chen

Humanized mouse models offer human-specific platforms for investigating complex host–pathogen interactions, addressing shortcomings of conventional preclinical models that often fail to replicate human immune responses accurately. This integrative review examines the intersection of advanced morphological phenotyping and artificial intelligence (AI) to enhance predictive capacity and translational relevance in infectious disease research. A structured literature search was conducted across PubMed, Scopus, and Web of Science (2010–2025), applying defined inclusion and exclusion criteria. Evidence synthesis highlights imaging modalities, AI-driven phenotyping, and standardization strategies, supported by comparative analyses and quality considerations. Persistent challenges include variability in engraftment, lack of harmonized scoring systems, and ethical governance. We propose recommendations for standardized protocols, risk-of-bias mitigation, and collaborative training frameworks to accelerate adoption of these technologies in translational medicine.

Biophysica doi: 10.3390/biophysica5030042

Authors: Giuseppe Maulucci

Metabolic imaging is undergoing a fundamental transformation. Traditionally confined to static representations of metabolite distribution through modalities such as PET, MRS, and MSOT, imaging has offered only partial glimpses into the dynamic and systemic nature of metabolism. This Perspective envisions a shift toward dynamic metabolic intelligence—an integrated framework where real-time imaging is fused with physics-informed models, artificial intelligence, and wearable data to create adaptive, predictive representations of metabolic function. We explore how novel technologies like hyperpolarized MRI and time-resolved optoacoustics can serve as dynamic inputs into digital twin systems, enabling closed-loop feedback that not only visualizes but actively guides clinical decisions. From early detection of metabolic drift to in silico therapy simulation, we highlight translational pathways across oncology, cardiology, neurology, and space medicine. Finally, we call for a cross-disciplinary effort to standardize, validate, and ethically implement these systems, marking the emergence of a new paradigm: metabolism as a navigable, model-informed space of precision medicine.

Biophysica doi: 10.3390/biophysica5030041

Authors: Paul R. Gardner

Heme enzymes that bind and reduce O2 are susceptible to poisoning by NO. The high reactivity and affinity of NO for ferrous heme produces stable ferrous-NO complexes, which in theory should preclude O2 binding and turnover. However, NO inhibition is often competitive with respect to O2 and rapidly reversible, thus providing cellular and organismal survival advantages. This kinetic paradox has prompted a search for mechanisms for reversal and hence resistance. Here, I critically review proposed resistance mechanisms for NO dioxygenase (NOD) and cytochrome c oxidase (CcO), which substantiate reduction or oxidation of the tightly bound NO but nevertheless fail to provide kinetically viable solutions. A ferrous heme intermediate is clearly not available during rapid steady-state turnover. Reversible inhibition can be attributed to NO competing with O2 in transient low-affinity interactions with either the ferric heme in NOD or the ferric heme-cupric center in CcO. Toward resolution, I review the underlying principles and evidence for kinetic control of ferric heme reduction via an O2-triggered ferric heme spin crossover and an electronically-forced motion of the heme and structurally-linked protein side chains that elicit electron transfer and activate O2 in the flavohemoglobin-type NOD. For CcO, kinetics, structures, and density functional theory point to the existence of an analogous O2 and reduced oxygen intermediate-controlled electron-transfer gate with a linked proton pump function. A catalytic cycle and mechanism for CcO is finally at hand that links each of the four O2-reducing electrons to each of the four pumped protons in time and space. A novel proton-conducting tunnel and channel, electron path, and pump mechanism, most notably first hypothesized by Mårten Wikström in 1977 and pursued since, are laid out for further scrutiny. In both models, low-energy spin-orbit couplings or ‘spintronic’ interactions with O2 and NO or copper trigger the electronic motions within heme that activate electron transfer to O2, and the exergonic reactions of transient reactive oxygen intermediates ultimately drive all enzyme, electron, and proton motions.

Biophysica doi: 10.3390/biophysica5030040

Authors: Constantinos Koutsojannis Athanasios Fouras Dionysia Chrysanthakopoulou

Medical physicists are transforming physiological measurements and electrophysiological applications by addressing challenges like motion artifacts and regulatory compliance through advanced signal processing, artificial intelligence (AI), and statistical rigor. Their innovations in wearable electrophysiology achieve 8–12 dB signal-to-noise ratio (SNR) improvements in EEG, 60% motion artifact reduction, and 94.2% accurate AI-driven arrhythmia detection at 12 μW power. In precision neurology, machine learning (ML) with evoked potentials (EPs) predicts spinal cord injury (SCI) recovery and multiple sclerosis (MS) progression with 79.2% accuracy based on retrospective data from 560 SCI/MS patients. By integrating multimodal data (EPs, MRI), developing quantum sensors, and employing federated learning, these can enhance diagnostic precision and prognostic accuracy. Clinical applications span epilepsy, stroke, cardiac monitoring, and chronic pain management, reducing diagnostic errors by 28% and optimizing treatments like deep brain stimulation (DBS). In this paper, we review the current state of wearable devices and provide some insight into possible future directions. Embedding medical physicists into standardization efforts is critical to overcoming barriers like quantum sensor power consumption, advancing personalized, evidence-based healthcare.

Biophysica doi: 10.3390/biophysica5030039

Authors: Sen Zheng

Cryo-electron microscopy single-particle analysis (cryo-EM SPA) has advanced three-dimensional protein structure determination, yet resolving intrinsically disordered proteins and regions (IDPs/IDRs) remains challenging due to conformational heterogeneity. This research evaluates cryo-EM’s capacity to map dynamic regions, assesses the adaptability of disorder prediction tools, and explores optimization strategies for dynamic structure prediction. Cryo-EM SPA datasets from 2000 to 2024 were categorized into different periods, forming a database integrating sequence data and disorder indices. Established prediction tools—AlphaFold2 (pLDDT), flDPnn, and IUPred—were evaluated for transferability, while a multi-level CLTC hybrid model (combining CNN, LSTM, Transformer, and CRF architectures) was developed to link local conformational fluctuations with global sequence contexts. Analyses revealed consistent advancements in average resolution and model counts over the past decade, although mapping disordered regions remained technically demanding. Both the adapted AlphaFold pLDDT and the CLTC model demonstrated efficacy in predicting structurally variable and poorly resolved regions. A subset of the cryo-EM missing residues exhibited intermediate conformational features, suggesting classification ambiguities potentially influenced by experimental conditions. These findings systematically outline the evolving capabilities of cryo-EM in resolving dynamic regions, benchmark the adaptability of computational tools, and introduce a hybrid model to enhance prediction accuracy. This study provides a framework for addressing conformational heterogeneity, contributing to methodological advancements in structural biology.

Biophysica doi: 10.3390/biophysica5030038

Authors: Ankit Monga Khush Jain Harvinder Popli Prashik Telgote Ginpreet Kaur Fariah Rizwani Ritu Chauhan Damandeep Kaur Abhishek Chauhan Hardeep Singh Tuli

Organs-on-Chips (OoC) technology has begun to be considered a pragmatic tool for drug evaluation, offering researchers an opportunity to move beyond the less physiologically relevant animal models. OoCs are microfluidic structures that imitate the functionalities of individual human organs, serving as mimicry tools for drug response and reproducibility studies. On the one hand, companies producing OoCs find managing and analyzing the large amounts of data generated challenging. This is where artificial intelligence (AI) can be deployed to address such problems. This paper will present the state-of-the-art of current OoC technology and AI, discussing the benefits and threats of combining these approaches. AI can be applied to optimize the process of OoC fabrication and operation, as well as for the big data analysis of OoC devices. By combining these technologies, scientists gain a powerful tool for drug development that is more efficient and accurate. However, processing the vast datasets generated by OoC systems often requires specialized AI expertise and computational resources. Despite the numerous possible benefits of amalgamating OoC technology with AI, several challenges and limitations need to be addressed. The large datasets generated by OoC systems can be difficult to process and analyze, which is a task that may require specialized AI expertise. Additionally, limitations of OoC systems include issues with reproducibility, as the devices are sensitive to perturbations in experimental conditions. Furthermore, the development and implementation of AI algorithms require significant computational resources and expertise, which may not be readily available to all research institutions. To overcome these challenges, interdisciplinary collaboration between biologists, engineers, data scientists, and AI experts is essential. Continued advancements in both OoC technology and AI will likely lead to more robust and versatile platforms for biomedical research and drug development, ultimately contributing to the advancement of personalized medicine and the reduction of reliance on animal testing.

Biophysica doi: 10.3390/biophysica5030037

Authors: Alireza Mirzaee Shantia Yarahmadian

Type 2 diabetes (T2D) is a chronic metabolic disorder requiring effective management to avoid complications. Metformin is a first-line drug agent and is routinely prescribed for the control of glycemia, but its underlying dynamics are complicated and not fully quantified. This paper formulates a control-oriented and interpretable mathematical model that integrates metformin dynamics into a classic beta-cell–insulin–glucose (BIG) regulation system. The paper’s applicability to theoretical and clinical settings is enhanced by rigorous mathematical analysis, which guarantees the model is globally bounded, well-posed, and biologically meaningful. One of the key features of the study is its global stability analysis using Lyapunov functions, which demonstrates the asymptotic stability of critical equilibrium points under realistic physiological constraints. These findings support the predictive reliability of the model in explaining long-term glycemic regulation. Bifurcation analysis also clarifies the dynamic interplay between glucose production and utilization by identifying parameter thresholds that signify transitions between homeostasis and pathological states. Residual analysis, which detects Gaussian-distributed errors, underlines the robustness of the fitting process and suggests possible refinements by including temporal effects. Sensitivity analysis highlights the predominant effect of the initial dose of metformin on long-term glucose regulation and provides practical guidance for optimizing individual treatment. Furthermore, changing the two considered metformin parameters from their optimal values—altering the dose by ±50% and the decay rate by ±20%—demonstrates the flexibility of the model in simulating glycemic responses, confirming its adaptability and its potential for optimizing personalized treatment strategies.

Biophysica doi: 10.3390/biophysica5030036

Authors: Radwan Ebna Noor Shahedul Islam Tracess Smalley Katarzyna Mizgalska Mark Eschenfelder Dimitra Keramisanou Aaron Joshua Astalos James William Leahy Wayne Charles Guida Aleksandra Karolak Ioannis Gelis Mildred Acevedo-Duncan

The overexpression of atypical protein kinase C-iota (PKC-ι) is a biomarker for carcinogenesis in various cell types, such as glioma, ovarian, renal, etc., manifesting as a potential drug target. In previous in vitro studies, ICA-1S and ICA-1T, experimental candidates for inhibiting PKC-ι, have demonstrated their specificity and promising efficacy against various cancers. Moreover, the in vivo studies have demonstrated low toxicity levels in acute and chronic murine models. Despite these prior developments, the binding affinities of the inhibitors were never thoroughly explored from a biophysical perspective. Here, we present the biophysical characterizations of PKC-ι in combination with ICA-1S/1T. Various methods based on molecular docking, light scattering, intrinsic fluorescence, thermal denaturation, and heat exchange were applied. The biophysical characteristics including particle sizing, thermal unfolding, aggregation profiles, enthalpy, entropy, free energy changes, and binding affinity (Kd) of the PKC-ι in the presence of ICA-1S were observed. The studies indicate the presence of domain-specific stabilities in the protein–ligand complex. Moreover, the results indicate a spontaneous reaction with an entropic gain, resulting in a possible entropy-driven hydrophobic interaction and hydrogen bonds in the binding pocket. Altogether, these biophysical studies reveal important insights into the binding interactions of PKC-ι and its inhibitors ICA-1S/1T.

Biophysica doi: 10.3390/biophysica5030035

Authors: Juan Antonio Noriega-Rodríguez Armando Tejeda-Mansir Hugo Sergio García

Protein purification is often performed for various applications. However, enzyme purification processes typically involve multiple steps that reduce yield and increase production costs. To overcome these challenges, we developed a novel three-step process to purify a lipase from whole sardine viscera (WSV), leveraging protein properties and the structural affinity of lipases for dye ligands. A crude extract of the viscera (CEV) was obtained by grinding the whole viscera in 50 mM phosphate buffer (pH 7.0, Solution B) followed by centrifugation (6000× g; 30 min, 0 °C). Lipolytic activity (3.3 U/mg) was recorded only in the supernatant. The purification process began with ammonium sulfate fractionation (30–50% saturation), increasing lipolytic activity in the precipitate (PF30-50) to 32.9 U/mg. PF30-50 was then ultrafiltered using a 30 KDa MWCO membrane, where 5% of semi-purified lipases (SPLSV) was retained with an activity of 156.5 U/mg (UF30). Finally, the SPLSV was injected into a column packed with dye ligand affinity adsorbent, pre-equilibrated with 1.0 M ammonium sulfate in buffer A. The WSV lipase was eluted using a step gradient to progressively reduce salt concentration. SDS-PAGE analysis revealed a single band of purified lipase from sardine viscera (PLSV) corresponding to a molecular weight of 123.4 kDa, with a specific activity of 266.4 U/mg. The combination of ammonium sulfate precipitation, ultrafiltration, and dye-ligand affinity chromatography provides a scalable and reproducible approach with potential industrial relevance, particularly in biocatalysis and waste valorization contexts.

Biophysica doi: 10.3390/biophysica5030034

Authors: Lisa Riedlsperger Heinz Anderle Andreas Schwaighofer Martin Lemmerer

Protein polarimetry has been evaluated as a simple and straightforward technique to detect the cryptic denaturation of exemplary proteins. The general rules of rotation vs. amino acid and structural composition and the respective knowledge gaps were reviewed, and the specific rotation of cystine was determined in 4 M NaCl solution as [α]D20 = –302.5°. The specific rotations at 589 nm and 436 nm and the ratio were measured for several model proteins, some purified plasma-derived proteins and for three monoclonal antibodies. The immunoglobulin G concentrates all showed a narrow ratio range likely characteristic for this protein class. Heat denaturation experiments were conducted at temperatures between 50 and 85 °C both for short-time (10 min) and for prolonged periods of heat exposure (up to 210 min). Denaturation by heat resulted not only in the known levorotatory shift, but also in a shift in the specific rotation ratio. The stabilizing effect of fatty acids in bovine serum could be demonstrated by this parameter. Polarimetry thus appears to be a particularly sensitive and simple method for the characterization of the identity and the thermal stability of proteins and should therefore be added again as a complimentary method to the toolbox of protein chemistry.

Biophysica doi: 10.3390/biophysica5030033

Authors: Pedro Ojeda-May

Protein enzymes are highly efficient catalysts that exhibit adaptability and selectivity under diverse biological conditions. In some organisms, such as bacteria, structurally similar enzymes, for instance, shikimate kinase (SK) and adenylate kinase (AK), coexist and act on chemically related ligands. This raises the question of whether these enzymes can accommodate and potentially react with each other’s ligands. In this study, we investigate the stability of non-cognate ligand binding in SK and explore whether external electric fields (EFs) can modulate this interaction, leading to cross-reactivity in SK. Using molecular dynamics simulations, we assess the structural integrity of SK and the binding behavior of ATP and AMP under EF-off and EF-on cases. Our results show that EFs enhance protein structure stability, stabilize non-cognate ligands in the binding pocket, and reduce local energetic frustration near the R116 residue located in the binding site. In addition to this, dimensionality reduction analyses reveal that EFs induce more coherent protein motions and reduce the number of metastable states. Together, these findings suggest that external EFs can reshape enzyme–ligand interactions and may serve as a tool to modulate enzymatic specificity and functional promiscuity. Thus, we provide computational evidence that supports the concept of using an EF as a tunable parameter in enzyme engineering and synthetic biology. However, further experimental investigation would be valuable to assess the reliability of our computational predictions.

Biophysica doi: 10.3390/biophysica5030032

Authors: Zhongbao Han Huizi Zheng Yimeng Qi Dilshadbek T. Usmanov Liyan Liu Zhan Yu

Icariin (ICA) is widely recognized for its health benefits. In this work, we examined the intermolecular interactions between ICA and proteinase K (PK) via multi-spectroscopic techniques and molecular simulations. The experimental findings revealed that ICA quenched the fluorescence emission of PK by forming a noncovalent complex. Both hydrogen bonding and van der Waals interactions are essential for the complex’s formation. Then Förster resonance energy transfer (FRET), competitive experiments, and synchronous fluorescence spectroscopy were adopted to verify the formation of the complex. Molecular docking studies demonstrated that ICA could spontaneously bind to PK by hydrogen bonding and hydrophobic interactions, which is consistent with the spectroscopic results. The PK-ICA complex’s dynamic stability was evaluated using a 50 ns molecular dynamics (MD) simulation. The simulation results revealed no significant structural deformation or positional changes throughout the entire simulation period. The complex appears to be rather stable, as seen by the average root-mean-square deviation (RMSD) fluctuations for the host protein in the PK-ICA complex of 1.08 Å and 3.09 Å. These outcomes of molecular simulations suggest that ICA interacts spontaneously and tightly with PK, consistent with the spectroscopic findings. The approach employed in this research presents a pragmatic and advantageous method for examining protein–ligand interactions, as evidenced by the concordance between empirical and theoretical findings.

Biophysica doi: 10.3390/biophysica5030031

Authors: Jack Pelzel Reese Anderson Darin J. Ulness Krys Strand

This study extends the application of photothermal spectroscopy to explore heat transfer dynamics in biological fluids, focusing on the examination of artificial vitreous humor (VH) models of human VH and an endogenous sample of cervine (deer) VH. The research integrates previously established methods for analyzing thermal lensing through photothermal deflection. By visualizing convective and conductive heat transfer processes in the artificial components of human VH, one gains insights into the dynamic behavior of heat transfer in the VH. Relevance extends to clinical cases where pathology requires replacement of endogenous VH with an artificial VH substitute. Several VH substitutes identified in the literature were chosen for this study based on their physical properties and relative abundance in the VH. Individual component fluids, and mixtures of these components, were analyzed at various concentrations based on their physiological concentration ranges in the human VH as they varied with age, sex, and certain disease states. By way of comparison to endogenous biological VH, a sample of VH obtained from a female white-tailed deer eye was analyzed, enhancing the understanding of heat transfer in artificial components of the VH compared to endogenous VH. There is a vast array of ophthalmological procedures that utilize an external heat source interacting with endogenous or artificial VH. The data found in this study will progress the understanding of heat transfer within artificial VH components in comparison to endogenous VH and contribute to the advancement of certain ophthalmological procedures.

Biophysica doi: 10.3390/biophysica5030030

Authors: Myeong Seon Jeong Han-ul Kim Mi Young An Yoon Ho Park Sun Hee Park Sang J. Chung Yoon-Sun Yi Sangmi Jun Young Kwan Kim Hyun Suk Jung

Recent major advancements in cryo-electron microscopy (cryo-EM) have enabled high-resolution structural analysis, accompanied by developments in image processing software packages for single-particle analysis (SPA). SPA facilitates the 3D reconstruction of proteins and macromolecular complexes from numerous individual particles. In this study, we systematically evaluated the impact of symmetry parameters and particle quantity on the 3D reconstruction efficiency using the dihydrolipoyl acetyltransferase (E2) inner core of the pyruvate dehydrogenase complex (PDC). We specifically examined how inappropriate symmetry constraints can introduce structural artifacts and distortions, underscoring the necessity for accurate symmetry determination through rigorous validation methods such as directional Fourier shell correlation (FSC) and local-resolution mapping. Additionally, our analysis demonstrates that efficient reconstructions can be achieved with a moderate particle number, significantly reducing computational costs without compromising structural accuracy. We further contextualize these results by discussing recent developments in SPA workflows and hardware optimization, highlighting their roles in enhancing reconstruction accuracy and computational efficiency. Overall, our comprehensive benchmarking provides strategic insights that will facilitate the optimization of SPA experiments, particularly in resource-limited settings, and offers practical guidelines for accurately determining symmetry and particle quantity during cryo-EM data processing.

Biophysica doi: 10.3390/biophysica5030029

Authors: Marie-Valérie Moreno Sid Ahmed Ben Mansour Frédéric Roscop

This study represents a first step toward improving the repeatability, reproducibility, and accuracy of a process designed to enhance dynamic water structuring. We aim is to investigate the optical reflectivity of a watery magnesium chloride solution treated with electromagnetic waves, we employ a novel methodology derived from human plethysmography (PPG) with three wavelengths spanning the visible and infrared spectra. We measured the reflectance of 17 flasks at 536 nm, 660 nm, and 940 nm before and after treatment, first using the succussion method (control) and second using a 50 Hz signal. The observed variability was acceptable, with repeatability errors below 0.15% and reproducibility errors below 3.5% across all wavelengths before and after treatment. Out of 51 samples dynamically structured using the succussion method, we obtained two false negatives, while one false negative was recorded out of 51 samples dynamically structured using the electromagnetic (EM) method. PPG appears to be a relevant sensor, as it correctly detected dynamically structured water in 99 out of 102 cases, using either the succussion or electromagnetic method. Our results show significant differences in reflectance (supposedly correlated with water’s structured status) at 536 nm between dynamically structured and dynamic non-structured samples (p < 0.001). Future improvements will include a validation protocol against gold-standard spectrophotometry with a larger sample size.

Biophysica doi: 10.3390/biophysica5030028

Authors: Dragan Nikolić Xu Zhang

We present a corrosion-resistant quadrupole ion trap mass spectrometer (QIT-MS) designed for trace detection of volatiles in sulfuric acid aerosols, with a specific focus on phosphine (PH3). Here, we detail the gas calibration methodology using permeation tube technology for generating certified ppb-level PH3/H2S/CO2 mixtures, and report results from mass spectra with sufficient resolution to distinguish isotopic envelopes that validate the detection of PH3 at a concentration of 62 ppb. Fragmentation patterns for PH3 and H2S agree with NIST data, and signal-to-noise performance confirms ppb sensitivity over 2.6 h acquisition periods. We further assess spectral interferences from oxygen isotopes and propose a detection scheme based on isolated phosphorus ions (P+) to enable specific and interference-resistant identification of PH3 and other reduced phosphorus species of astrobiological interest in Venus-like environments. This work extends the capabilities of QIT-MS for trace gas analysis in chemically aggressive atmospheric conditions.

Biophysica doi: 10.3390/biophysica5030027

Authors: Carmen Regina de Souza Maurício Ikeda Yoguim Nathalia Mariana Pavan Nelson Henrique Morgon Valdecir Farias Ximenes Aguinaldo Robinson de Souza

Coumarins are known for interacting with proteins and exhibiting diverse biological activities. This study investigates the interaction between coumarin-343 (C343) and human (HSA) and bovine (BSA) serum albumins. Fluorescence spectroscopy and theoretical simulations, including density functional theory (DFT) and molecular docking, were used to analyze the ligand–protein complex formation. The fluorescence quenching data revealed that C343 binds to both proteins, with binding constants of 2.1 × 105 mol·L−1 (HSA) and 6.5 × 105 mol·L−1 (BSA), following a 1:1 stoichiometry. Binding site markers identified drug site I (DS1), located in subdomain IIA, as the preferential binding region for both proteins. Computational results supported these findings, showing high affinity for DS1, with binding energies of −69.02 kcal·mol−1 (HSA) and −67.22 kcal·mol−1 (BSA). While complex formation was confirmed for both proteins, differences emerged in the induced circular dichroism (ICD) signals. HSA displayed a distinct ICD profile compared to BSA in both intensity and absorption maximum. Molecular Docking revealed that the C343 conformation differed between HSA and BSA, explaining the variation in ICD signals. These results highlight the importance of protein structure in modulating ligand interactions and spectral responses.

Biophysica doi: 10.3390/biophysica5030026

Authors: Ping Xie

An engineered molecular motor composed of an ATP-dependent kinesin-1 monomer and an ATP-independent diffusing microtubule-associated protein is proposed, and its dynamics are studied theoretically. It is shown that the engineered motor can move directionally on microtubules towards the plus end, bearing great potential for applications in therapeutics or nanorobotics. The engineered motor can have an unloaded velocity similar to the wild-type kinesin-1 dimer, can take a mechanical (either forward or backward) step by hydrolyzing an ATP molecule under any load, and can generate the maximum force that is about half of that generated by the wild-type kinesin-1 dimer.

Biophysica doi: 10.3390/biophysica5030025

Authors: Allen P. Minton

A brief summary of the effect of nonspecific interactions upon chemical equilibria in solutions containing a high total concentration of macromolecular solutes comparable to that found in biological fluid media is presented. Analyses of experimental measurements permitting relatively direct quantitation of the free energy of nonspecific intermolecular interaction in solutions of one or two macrosolutes are described, and a table listing published experimental studies of both homo- and hetero-interactions is provided. Methods for calculating the free energy of nonspecific interaction via theory and computer simulation are described. Recommendations for further progress in both measurement and calculation of interaction free energies are presented.

Biophysica doi: 10.3390/biophysica5030024

Authors: Jolanta Fertala Andrzej Steplewski Andrzej Fertala

Collagen II is a vital structural component in developing bones and mature cartilage. Mutations in this protein cause spondyloepiphyseal dysplasia, a disease characterized primarily by altered skeletal growth and manifesting with a range of phenotypes, from lethal to mild. This study examined transgenic mice harboring the R992C (p.R1124C) substitution in collagen II. Previous research demonstrated significant growth abnormalities and disorganized growth plate structure in these mice, and histological signs of osteoarthritic changes in the knee joints of 9-month-old mice with the R992C mutation. Our study focuses on detecting early structural changes in the articular cartilage that occur before histological signs become apparent. Through microscopic and spectroscopic analyses, we observed significant alterations in the distribution gradients of collagenous proteins and proteoglycans in the cartilage of R992C mutant mice. We propose that these early changes, eventually leading to articular cartilage degeneration in older mice, underscore the progressive nature of osteoarthritic changes linked to collagen II mutations. By identifying these early structural aberrations, our findings emphasize the importance of early detection of osteoarthritic changes, potentially facilitating timely, non-surgical interventions.

Biophysica doi: 10.3390/biophysica5020023

Authors: Aleksandar Simeonov Karo Michaelian

An ancient repertoire of ultraviolet (UV)-absorbing pigments which survive today in the phylogenetically oldest extant photosynthetic organisms, the cyanobacteria, point to a direction in evolutionary adaptation of the pigments and their associated biota; from largely UV-C absorbing pigments in the Archean to pigments covering ever more of the longer wavelength UV and visible regions in the Phanerozoic. Since photoprotection is not dependent on absorption, such a scenario could imply selection of photon dissipation rather than photoprotection over the evolutionary history of life, consistent with the thermodynamic dissipation theory of the origin and evolution of life which suggests that the most important hallmark of biological evolution has been the covering of Earth’s surface with organic pigment molecules and water to absorb and dissipate ever more completely the prevailing surface solar spectrum. In this article we compare a set of photophysical, photochemical, biosynthetic, and other inherent properties of the two dominant classes of cyanobacterial UV-absorbing pigments, the mycosporine-like amino acids (MAAs) and scytonemins. We show that the many anomalies and paradoxes related to these biological pigments, for example, their exudation into the environment, spectral coverage of the entire high-energy part of surface solar spectrum, their little or null photoprotective effect, their origination at UV-C wavelengths and then spreading to cover the prevailing Earth surface solar spectrum, can be better understood once photodissipation, and not photosynthesis or photoprotection, is considered as being the important variable optimized by nature.

Biophysica doi: 10.3390/biophysica5020022

Authors: Man Song Xiao Liu Jie Zhang Wuping Li Jingfen Pan Yanglei Jia

Ark shells are a group of bivalves that exhibit extraordinary adaptability to the dual environmental pressures of low oxygen and osmotic imbalance. These challenges are particularly pronounced in intertidal zones, where organisms are subjected to rapid and drastic changes in their surroundings. This research investigated the molecular mechanisms that underpin their survival and adaptive strategies, with particular focused on sodium–potassium ATPase (NKA), a pivotal enzyme responsible for maintaining cellular ion transmembrane gradients and ensuring cellular homeostasis under stress conditions. By utilizing genome assemblies and transcriptomics datasets from multiple ark shell species, we successfully identified two distinct NKA-α subunits and two NKA-β subunits, which are essential components of the NKA complex. Moreover, the discovery of a conserved NKA-interacting protein (NKAIN) highlights the complexity and evolutionary significance of the NKA-NKAIN system in ark shells. Phylogenetic analysis revealed a high degree of conservation in the NKA-α and NKA-β subunits across ark shells, suggesting strong selective pressures to preserve their functionality. However, the marked divergence observed between the two NKA-β subunits suggests that they may serve distinct roles in ion transport, potentially specialized for specific environmental conditions or stress responses. Comparative transcriptomic analysis further revealed the regulatory roles of NKA and NKAIN in the adaptive responses to hypoxia and osmotic stress, showing that these genes are dynamically modulated at the transcriptional level in response to environmental challenges. These findings provide a molecular foundation for understanding the osmotic adaptation mechanisms in ark shells and offer novel insights into their ability to thrive in mudflat habitats. This comprehensive exploration of the NKA-NKAIN system not only enhances our understanding of the resilience of ark shells but also provides valuable insights into the molecular and physiological strategies employed by bivalves in intertidal environments.

Biophysica doi: 10.3390/biophysica5020021

Authors: Shuping Chen Weiyuan Zhu Sai Huang Baoling Zheng

The system suitability testing of chromatography is an indispensable procedure in pharmaceutical analysis, and it must comply with rules in related pharmacopoeias. An inverse Fourier transform algorithm was developed to accurately evaluate chromatographic features versus a standard Gaussian peak shape. The regular chromatogram is considered a pseudo-frequency spectrum and can be converted to a nominal time signal via inverse Fourier transformation. The system suitability parameters of peak width, theoretical plate number, tailing factor, and noise testing were evaluated using linear regressions directly and compared with the compendial rules. This novel method is simple, accurate, robust, reliable, and efficient for the evaluation of chromatographic peak features.

Biophysica doi: 10.3390/biophysica5020020

Authors: Abanob Hanna Anthony Casper Roi Dagan Hardev S. Grewal Jiyeon Park Eric D. Brooks Erik Traneus Lars Glimelius Perry B. Johnson Mohammad Saki Yawei Zhang Twyla R. Willoughby Julie A. Bradley Jackson Browne Mark E. Artz

Proton beam therapy for head and neck cancers traditionally employs a fixed relative biological effectiveness (RBE) of 1.1, which may underestimate actual biological effects in critical structures. This study evaluates how Linear Energy Transfer (LET) optimization could potentially prevent radiation-induced brachial plexopathy (RIBP). (1) Case presentation: A 65-year-old male with stage IVA p16-positive oropharyngeal squamous cell carcinoma received pencil-beam-scanning intensity-modulated proton therapy with concurrent cisplatin. Due to a right level 4 neck node, the high-risk target volume overlapped with the brachial plexus, resulting in a D0.1cc of 70.3 Gy (RBE = 1.1). Four years post-treatment, the patient developed progressive right upper extremity paresthesia, weakness, and dysesthesia. Electromyography revealed myokymia consistent with brachial plexopathy, while MRI showed hyperintensity of the right brachial plexus corresponding to the radiation field. Conservative treatment with pentoxifylline, gabapentin, and physical therapy improved his symptoms. (2) Methods: The original treatment plan was retrospectively analyzed using Monte Carlo dose algorithms and LET-dependent RBE models from McMahon and McNamara. An LET-optimized plan was created to limit LETd to 2.0 keV/µm in the brachial plexus. (3) Results: The relative biological equivalent (RBE) dose to 0.1cc of the brachial plexus was 77.8 Gy (CGE RBE), exceeding tolerance. The LET-optimized plan reduced the brachial plexus D0.1cc to 59.4 Gy (RBE = 1.1) and 63.2 Gy (CGE RBE), an 18.8% decrease, while maintaining target coverage. LETd, within the brachial plexus enhancement, decreased from 5.3 to 2.6 keV/μm. (4) Conclusion: This case highlights the potential clinical importance of LET optimization in proton therapy planning, particularly when organs-at-risk overlap with target volumes. By reducing LETd from 5.3 to 2.6 keV/μm and biological equivalent dose by 18.8%, LET optimization could potentially prevent late toxicities, like RIBP, while maintaining target coverage.

Biophysica doi: 10.3390/biophysica5020019

Authors: Marko E. Popović Marta Popović Dong Pei

Caenorhabditis elegans is among the most important model organisms. It has been extensively studied from the perspective of life and biomedical sciences. However, no model of growth and metabolism of C. elegans is available in the literature that is based on biothermodynamics and bioenergetics. Such a model would provide insight into growth and metabolism of C. elegans from the perspective of the fundamental laws of nature. In this research, a chemical and thermodynamic characterization of C. elegans is performed, with the determination of empirical formulas, thermodynamic properties of living matter, reactions of biosynthesis, catabolism and metabolism, thermodynamic properties of biosynthesis, catabolism and metabolism, and phenomenological coefficients. Based on the determined properties, a model of the growth and metabolism of C. elegans is developed. The model is used to discuss the metabolism of C. elegans from the aspect of physical chemistry.

Biophysica doi: 10.3390/biophysica5020018

Authors: Maria S. Lavlinskaya Andrey V. Sorokin Anastasia N. Dubovitskaya Anastasia I. Yutkina Maxim S. Kondratyev Marina G. Holyavka Yuriy F. Zuev Valeriy G. Artyukhov

The investigation of structure–function relationships in enzyme polysaccharide complexes provides a theoretical foundation for modulating enzyme properties and expanding their industrial applications. In this study, the interaction of cysteine proteases—bromelain, ficin, and papain—with a grafted chitosan–poly(N-vinylpyrrolidone) copolymers, Cs-g-PVP, was examined, and its effect on the catalytic and stability properties of the enzymes was assessed. Molecular docking and Fourier-transform infrared spectroscopy were used to analyze the topology of the resulting complexes and identify macromolecular fragments involved in binding. Based on the obtained results, it was hypothesized that complex formation would lead to a slight reduction in the catalytic activity of cysteine proteases. In vitro studies of the complexes confirmed this hypothesis, showing that the enzymes retained more than 63% of their proteolytic activity while their half-inactivation time during storage increased by up to ~12-fold. The investigated Cs-g-PVP copolymers demonstrated high efficiency as supports for the studied enzymes, capable of retaining up to 100% of the added enzymes.

Biophysica doi: 10.3390/biophysica5020017

Authors: Dragan Nikolić Stojan M. Madzunkov

We present a corrosion-resistant quadrupole ion trap mass spectrometer (QIT-MS) for the direct detection of biosignature gasses in chemically reactive planetary atmospheres, such as Venusian clouds. The system employs a Paul trap with hyperbolic titanium alloy electrodes and alumina spacers for chemical durability and precise ion confinement. An yttria-coated iridium filament serves as the thermionic emitter within a modular electron gun capable of axial and radial ionization. Analytes are introduced through fused silica capillaries and crescent inlets into a miniature pressure cell. The testbed integrates high-voltage RF electronics, pressure-regulated sample delivery, and FPGA-based control for real-time tuning. Continuous operation in 98% sulfuric acid vapor for over three months demonstrated no degradation in emitter or sensor performance. Mass spectra revealed H2SO4 fragmentation and thermally induced decomposition up to 425 K. Spectral variations with filament current and electron energy highlight thermal and electron-induced dissociation dynamics. Operational modes include high-resolution scans and selective ion ejection (e.g., CO2+, N2+) to enhance the detection of PH3+, H2S+, and daughter ions. The compact QIT-MS platform is validated for future missions targeting corrosive atmospheres, enabling in situ astrobiological investigations through the detection of biosignature gasses such as phosphine and hydrogen sulfide.

Biophysica doi: 10.3390/biophysica5020016

Authors: Kevin Morris John DeSalvo Iman Deanparvar Lucus Schneider Kaleigh Leach Matthew George Yayin Fang

The tetrameric protein transthyretin (TTR) transports the hormone thyroxine in plasma and cerebrospinal fluid. Certain point mutations of TTR, including the Val122Ile mutation investigated here, destabilize the tetramer leading to its dissociation, misfolding, aggregation, and the eventual buildup of amyloid fibrils in the myocardium. Cioffi et al. reported the design and synthesis of a novel TTR kinetic stabilizing ligand, referred to here as TKS14, that inhibited TTR dissociation and amyloid fibril formation. In this study, molecular dynamics simulations were used to investigate the binding of TKS14 and eight TSK14 derivatives to the Val122Ile TTR mutant. For each complex, the ligand’s solvent accessible surface area (SASA), ligand–receptor hydrogen-bonding interactions, and the free energy of ligand-binding to TTR were investigated. The goal of this study was to identify the TSK14 functional groups that contributed to TTR stabilization. TKS14 was found to form a stable, two-point interaction with TTR by hydrogen bonding to Ser-117 residues in the inner receptor binding pocket and interacting through hydrogen bonds and electrostatically with Lys-15 residues near the receptor’s surface. The free energy of TKS14-TTR binding was −18.0 kcal mol−1 and the ligand’s average SASA value decreased by over 80% upon binding to the receptor. The thermodynamic favorability of TTR binding decreased when TKS14 derivatives contained either methyl ester, amide, tetrazole, or N-methyl functional groups that disrupted the above two-point interaction. One derivative in which a tetrazole ring was added to TKS14 was found to form hydrogen bonds with Thr-106, Thr-119, Ser-117, and Lys-15 residues. This derivative had a free energy of TTR binding of −21.4 kcal mol−1. Overall, the molecular dynamics simulations showed that the functional groups within the TKS14 structural template can be tuned to optimize the thermodynamic favorability of ligand binding.

Biophysica doi: 10.3390/biophysica5020015

Authors: José Sebastian Dávila Costa Cintia Mariana Romero

Fungal diseases represent a significant threat to global agriculture, leading to substantial crop losses and endangering food security worldwide. Conventional chemical fungicides, while effective, are increasingly criticized for their detrimental environmental impacts, including soil degradation, water contamination, and the disruption of non-target organisms. Additionally, the overuse of these fungicides has accelerated the emergence of resistant fungal strains, further challenging disease management strategies. In response to these issues, bio-nanofungicides and nano-biofungicides have emerged as a cutting-edge solution, combining biocompatibility, environmental safety, and enhanced efficacy. These advanced formulations integrate bio-based agents, such as microbial metabolites or plant extracts, with nanotechnology to improve their stability, controlled release, and targeted delivery. Chitosan, silica, and silver nanoparticles were extensively studied for their ability to encapsulate bioactive compounds or because of their outstanding antifungal activity, while minimizing environmental residues. Recent studies demonstrated the potential of nano-based fungicides to address critical gaps in sustainable agriculture, with promising applications in integrated pest management systems. Here, we summarize the last advances in the development of bio-nanofungicides and nano-biofungicides and analyze the main differences between them. In addition, challenges such as large-scale production, regulatory approval, and comprehensive risk assessments are discussed.

Biophysica doi: 10.3390/biophysica5020014

Authors: Elena Don Sabina Yaroshenko Svetlana Zakharova Evgenia Nechaeva Alexander Kovalchuk Anastasia Petrova Sergey Tarasov Oleg Epstein

Cell-based therapy is a promising direction for the treatment of various diseases. However, it is associated with several problems, primarily related to reproducibility and standardization. In this context, the development of new methods for the production of cell-based preparations is of particular relevance. Recently, a novel technology named ‘crossing’ has been developed. It comprises the multi-stage vibrational processing of two closely spaced test tubes containing the initial substance and a neutral carrier (water or lactose). As a result, the neutral carrier acquires some properties of the initial substance, and artificial products, vibrational iterations, are obtained. Some vibrational iterations are also capable of exerting a modifying effect on the initial substance (or its target in the body), changing its physico-chemical/biological properties. Earlier, we demonstrated the possibility of obtaining vibrational iterations from biological molecules (antibodies). In this study, we evaluated the biological effects of vibrational iterations obtained by the crossing technology using cells grown in culture. This work shows that vibrational iterations obtained from CHO-S cell culture affect the ability of CHO-S cells to utilize glucose in the presence of insulin. The data demonstrate the prospect of developing fundamentally new biological drugs based on vibrational iterations, including for the treatment of diabetes mellitus.

Biophysica doi: 10.3390/biophysica5020013

Authors: Sameer Patil Ami Thakkar Ginpreet Kaur Amisha Vora Ritu Chauhan Seema Ramniwas Abhishek Chauhan Damandeep Kaur Hardeep Singh Tuli

Neurodegenerative disorders include Alzheimer’s and Parkinson’s, both of which lead to progressive loss of neurons resulting in the severe loss of cognitive and motor functions. These diseases are among the heavy burdens on global healthcare systems largely because there is no cure, and current treatments apply almost entirely to controlling symptoms rather than disease progression. Recent advances in 3D printing and bioprinting technologies now open the way to overcome these challenges and form patient-specific models and therapeutical tools closely simulating the complex environment of the human brain. It then further illustrates how this technological integration with the aid of 3D printing, coupled with microfabrication and biosensing technologies, transforms drug-screening platforms as well as develops customization in medicine. For example, one can form highly intricate and multi-materially composed structures to better facilitate one’s study or test into some new therapeutic possibilities using methodologies of stereolithography and selective laser sintering. Moreover, 3D printing allows the creation of organ-on-a-chip models that simulate brain-like conditions, which may help identify specific biomarkers and evaluate new options of therapy. On the other hand, bioprinting methods based on neural cells combined with scaffolds mimicking native tissue dramatically transform regenerative medicine. New pathways in neural tissue development and implantable devices are now being brought forth, which can be tailored to the needs of individual patients. These advances bring not only greater precision in terms of the therapy that can be delivered but also 3D printing of implantable microelectrodes able to determine real-time biomarkers responsible for neurodegenerative diseases. Thus, this review highlights the robust impact that might be brought forth on the diagnosis and treatment of these neurodegenerative diseases via 3D printing technologies toward more effective management and personal solutions for healthcare.

Biophysica doi: 10.3390/biophysica5020012

Authors: Eleonora Alfinito Matteo Beccaria

The description of the organization of microorganisms in terms of emergent “social” interactions has long been a fascinating and challenging subject, in both biology and sociology. In these organisms, the role of the individual is far less dominant than that of the community, which operates as a sort of superorganism. The coordination is achieved through a communication mechanism known as quorum sensing. Quorum sensing coordinates and regulates various biological aspects of a microbial community, such as the expression of pathogenicity factors, biofilm formation, and the production of secondary metabolites, among others. These processes rely on the coordinated behavior of the entire bacterial population, enabling them to adapt and thrive withing a specific ecological niche under its unique biological, physical and chemical conditions. Finally, quorum sensing also allows the community to control the development of potentially harmful individuals, thus preserving the cooperativeness of the community. This study uses an agent-based quorum sensing model to explore the relationship between metabolic functions and social behavior in bacteria. In particular, we identify two metabolic parameters whose variations provide a broad panorama of possible social characteristics. Furthermore, the proposed QS model allows us to reproduce, at least qualitatively, some experimental results regarding the competition between some strains with different social characteristics. Finally, we examine how an ideal polyculture responds to variations in the metabolic characteristics of its components. Specifically, we identify a particularly stable condition in which the components cooperate to maximize the overall health of the colony. We refer to this state as resonance for life.

Biophysica doi: 10.3390/biophysica5020011

Authors: Tatiana V. Koshlan Kirill G. Kulikov

This study focuses on biochemical pathways of complex biochemical formation, taking into account various thermodynamic parameters that change as the complexity and molecular weight of complex molecules increase. We conducted a study of the co-direction of changes in thermodynamic quantities such as lg[Kd], TΔS, Δ(ΔW), and lg(cond(W)) during the transition from a monomer to a dimer and then to a trimer and tetramer. In this work, we assume that the co-direction of changes in thermodynamic quantities as the final molecular formation being achieved signals a higher affinity of molecules among themselves than there is for a biochemical formation, which is characterized by the lack of coordination of the biochemical pathway directions of the final molecular compound. As the studied molecular complexes, we took [LGP2-8dsRNA-LGP2], [VP35]2-dsRNA-[VP35]2, and MARV NPcore proteins with peptides and the complex of MJ20 with antigens from the Bundibugyo strain of Ebola virus. Calculations of biochemical reaction paths were conducted.

Biophysica doi: 10.3390/biophysica5020010

Authors: Hirohisa Tamagawa Iori Kojima Anh Lan Duong Bernard Delalande

Within the field of physiology, it is widely recognized that the constant flow of mobile ions across the plasma membrane generates membrane potential in living cells. This understanding is a part of the membrane theory. Despite this, membrane theory does not account for the role of ion adsorption (or desorption) processes in generating membrane potential, even though ion adsorption is a key concept in basic thermodynamics. Presently, the study of physiology lacks integration with thermodynamic principles. The membrane theory posits that living cells can differentiate between Na+ and K+ by means of channels and pumps. Thus, Na+ and K+ differentially impact the membrane potential. On the other hand, the Hofmeister effect, an older and less prominent thermodynamic theory, proposes that Na+ and K+ have varying adsorption levels to biomolecules, potentially accounting for their distinct effects on membrane potential even without the involvement of channels and pumps. This concept, distinct from the traditional membrane theory and grounded in ion adsorption (desorption) alongside the Hofmeister effect, might elucidate the process of membrane potential formation. This ion adsorption (desorption) and Hofmeister effect-based idea relates to the previously overlooked Association-Induction Hypothesis (AIH). Our experimental measurements of membrane potentials using artificial cell models highlight that ion adsorption activity and the Hofmeister effect have a comparable impact on the generation of membrane potential as ion flow in the conventional physiological model, assisted by channels and pumps.

Biophysica doi: 10.3390/biophysica5010009

Authors: Maxim A. Droemer Mikhail Shein Anne K. Schütz

ATP analogues are essential tools in enzymology and structural biology, but the structural and functional implications of their chemical modifications on nucleotide-binding proteins are often underappreciated. To address this, we evaluated a panel of ATP analogues, focusing on thiosubstituted and fluorinated molecules, using the AAA+ ATPase p97 as a benchmark system. Hydrolysis stability and impact on protein conformation, binding modes, and kinetics of enzymatic catalysis were assessed by protein-detected methyl NMR and ligand-detected 19F NMR in solution, as well as 31P solid-state NMR of nucleotides within protein sediments. ATPγS and AMP-PNP emerged as the most suitable analogues for preserving pre-hydrolysis states over extended periods, despite undergoing gradual hydrolysis. In contrast, both AMP-PCP and α/β-thiosubstituted analogues failed to induce native protein conformations in p97. Notably, we demonstrate a novel real-time NMR setup to explore the effect of nucleotide mixtures on cooperativity and the regulation of enzymes. Additionally, aromatic fluorine TROSY-based 19F NMR shows promise for direct ligand detection in solution, even in the context of large macromolecular complexes. These findings provide critical guidance for selecting ATP analogues in functional and structural studies of nucleotide-binding proteins.

Biophysica doi: 10.3390/biophysica5010008

Authors: Ikhlas Hani Chennoufi Chorouk Zanane Taoufik Hakim Hafida Zahir Fatima Hamadi Abderrahmene El Ghmari Mostafa El Louali Hassan Latrache

Electrostatic charge significantly influences microorganism–surface interactions, including viral adhesion and transmission. While bacterial surface charges are well characterized using electrophoretic mobility and X-ray photoelectron spectroscopy (XPS), similar studies for viruses are limited. This work bridges the gap by estimating the negative surface charge of the Phi6 bacteriophage using XPS data. A novel approach is applied, combining chemical functionalities derived from XPS with a system of equations to quantify surface polysaccharides, proteins, hydrocarbons, and negatively charged groups (RCOO− and R2PO4−). The results indicate a predominance of proteins on the viral surface and a pH-dependent negative charge: phosphate groups dominate at low pH (1–3), while both groups contribute equally at pH 4–9. These findings provide a deeper understanding of virus–surface interactions and underscore the importance of pH in modulating viral surface charge. This method, which surpasses traditional electrophoretic mobility techniques, offers new perspectives for studying viral adhesion and developing improved antiviral materials and disinfection strategies.

Biophysica doi: 10.3390/biophysica5010006

Authors: Bleddyn Jones

Purpose: The purpose of this study is to analyze the relationship between nuclear charge (Z), atomic mass (A), LET (linear energy transfer for maximal relative biological effectiveness (RBE)) for accelerated ions based on the hypothesis that for each ion, LETU is related to their nuclear radius. Methods: Published LETU data for proton, helium, carbon, neon, silicon, argon, and iron ions and their Z and A numbers are fitted by a power law function (PLF) and compared with PLF based on atomic cross-sections and nuclear dimensions for spherical or spheroidal atomic nuclei. The PLF allows for isoeffective RBE estimations for different ions at any value of LET based on the LETU estimations. For any two ions, A and B, and a specified bioeffect obtained at LETA, the equivalent isoeffective LETB, is estimated using LETB=LETA.LETU[B]LETU[A]. Results: The data-fitting program provided the following results: LETU=78.1.A0.26, and LETU=86.6.Z0.29, where 78.1 and 86.6 keV.μm−1 are the proton LETU values (i.e., without proton cellular range limit considerations). Goodness-of-fit tests are similar for each model, but the proton estimations differ. These exponents are lower than 0.66 and 0.33 (those for nuclear cross-sections and spherical nuclear radii, respectively), but suggest prolate nuclear shapes in most of the ions studied. Worked examples of estimating isoeffective LET values for two different ions are provided. Conclusions: The fitted power law relationships between LETU and Z or A are broadly equivalent and compatible with prolate nuclear shapes. These models may offer a more rational basis for future ion-beam radiobiology research.

Biophysica doi: 10.3390/biophysica5010007

Authors: Luca Manciocchi Alexandre Bianchi Valérie Mazan Mark Potapov Katharina M. Fromm Martin Spichty

Silver(I) ions and organometallic complexes thereof are well-established antimicrobial agents. They have been employed in medical applications for centuries. It is also known that some bacteria can resist silver(I) treatments through an efflux mechanism. However, the exact mechanism of action remains unclear. All-atom force-field simulations can provide valuable structural and thermodynamic insights into the molecular processes of the underlying mechanism. Lennard-Jones parameters of silver(I) have been available for quite some time; their applicability to properly describing the binding properties (affinity, binding distance) between silver(I) and peptide-based binding motifs is, however, still an open question. Here, we demonstrate that the standard 12-6 Lennard-Jones parameters (previously developed to describe the hydration free energy with the TIP3P water model) significantly underestimate the interaction strength between silver(I) and both methionine and histidine. These are two key amino-acid residues in silver(I)-binding motifs of proteins involved in the efflux process. Using free-energy calculations, we calibrated non-bonded fix (NBFIX) parameters for the CHARMM36m force field to reproduce the experimental binding constant between amino acid sidechain fragments and silver(I) ions. We then successfully validated the new parameters on a set of small silver-binding peptides with experimentally known binding constants. In addition, we monitored how silver(I) ions increased the α-helical content of the LP1 oligopeptide, in agreement with previously reported Circular Dichroism (CD) experiments. Future improvements are outlined. The implementation of these new parameters is straightforward in all simulation packages that can use the CHARMM36m force field. It sets the stage for the modeling community to study more complex silver(I)-binding processes such as the interaction with silver(I)-binding-transporter proteins.

Biophysica doi: 10.3390/biophysica5010005

Authors: Sergio Alonso Enrique Alvarez-Lacalle Jean Bragard Blas Echebarria

Cardiovascular diseases have become the leading cause of death in developed countries. Among these, some are related to disruptions in the electrical synchronization of cardiac tissue leading to arrhythmias such as atrial flutter, ventricular tachycardia, or ventricular fibrillation. Their origin is diverse and involves several spatial and temporal scales, ranging from nanoscale ion channel dysfunctions to tissue-level fibrosis and ischemia. Mathematical models play a crucial role in elucidating the mechanisms underlying cardiac arrhythmias by simulating the electrical and physiological properties of cardiac tissue across different spatial scales. These models investigate the effects of genetic mutations, pathological conditions, and anti-arrhythmic interventions on heart dynamics. Despite their varying levels of complexity, they have proven to be important in understanding the triggers of arrhythmia, optimizing defibrillation protocols, and exploring the nonlinear dynamics of cardiac electrophysiology. In this work, we present diverse modeling approaches to the electrophysiology of cardiac cells and share examples from our own research where these approaches have significantly contributed to understanding cardiac arrhythmias. Although computational modeling of the electrical properties of cardiac tissue faces challenges in integrating data across multiple spatial and temporal scales, it remains an indispensable tool for advancing knowledge in cardiac biophysics and improving therapeutic strategies.

Biophysica doi: 10.3390/biophysica5010004

Authors: Camila A. Tavares Eduardo F. Benedito Taináh M. R. Santos Rodrigo M. Santos Teodorico C. Ramalho

Since 2020, the attention of the scientific community has been focused on the overwhelming COVID-19 pandemic, the infectious disease caused by the coronavirus that has affected populations worldwide. The alarming number of deaths and the severity of the symptoms have driven studies aimed at combating this disease. One of the key components in the development of this disease is the protein MPro, responsible for the replication and transcription of the virus, making it an excellent biological target in research efforts seeking an effective treatment for the disease. Furthermore, studies have shown that vanadium complexes, such as bis(N′,N′-dimethylbiguanide)oxovanadium (IV), VO(metf)2∙H2O, exhibit highly promising effects for the treatment of COVID-19. This molecule contains a ligand known as metformin, which also holds a prominent place as a potential agent in the treatment of this disease due to its antiviral properties. Therefore, an investigation into the interactions between these two systems (MPro+Vanadium Complex and MPro+Metformin) is pertinent given the significance of these two molecules. Thus, computational studies such as molecular docking and classical molecular dynamics are considered advantageous, assisting in this comparative study, as well as providing a deeper understanding of the interactions that occur within each of them.

Biophysica doi: 10.3390/biophysica5010003

Authors: Ursula Windberger Andreas Sparer

Nature equipped red blood cells (RBCs) with diverse mechanical properties, which makes it possible to examine blood with different RBC properties (size, shape, aggregability, deformability). We investigated whether the shelf life of cow blood (stiff RBCs, low aggregability) is longer compared with pig blood (deformability/aggregability comparable to human) due to a delay in RBC clustering and decomposition. Blood was drawn from conscious pigs and cows in their familiar environment to reduce stress and stored 30 days at +7 °C. RBCs remained intact in cow samples whereas pig samples became hemolytic after day 20. White blood cells and platelets decreased with similar percentages in both species. Hematocrit (HCT) decreased due to RBC shrinking in bovine samples and due to RBC decay in porcine samples. Blood viscosity increased in both species although HCT decreased. In porcine samples, shear thinning decreased progressively, indicating a gradual loss of sample cohesion with storage. Yield stress and storage modulus decreased with hemolysis. In HCT-native cow samples, shear thinning, yield stress, and storage modulus showed high intraindividual variability, but the mean values did not change over the time course. In HCT-adjusted (38%) cow samples, solidification occurred after day 7, followed by a reduction in cohesion and shear thinning until the end of storage.

Biophysica doi: 10.3390/biophysica5010002

Authors: María J. Benítez Juan S. Jiménez

The thermodynamic study of protein folding shows the generation of a narrow range of ΔG° values, as a net result of large changes in the ΔH° and TΔS° values of the folding process. The obvious consequence of this narrow range of values is that a linear enthalpy–entropy relationship, showing apparent enthalpy–entropy compensation (EEC), is clearly observed to be associated with the study of protein folding. Herein, we show the ΔH°, TΔS°, and ΔG° values for a set of 583 data from protein folding processes, at various temperatures, as calculated by using the Gibbs–Helmholtz equations. This set of thermodynamic data was calculated from the melting temperature (Tm), the melting enthalpy (ΔHm), and the change in heat capacity (ΔCp°) values, all of them associated with the heat-induced protein unfolding processes and included in the ProTherm Data Base. The average values of enthalpy (ΔH°av), entropy (TΔS°av), and free energy (ΔG°av) for the folding process were calculated within the range of temperature from 0 °C to the average value of Tm. The values and temperature dependency of TΔS°av within this temperature range are practically equal to those corresponding to ΔH°av, while ΔG°av remains small and displaying a curve with a minimum at about 10 °C and a value of ΔG° = −30.9 kJ/mol at the particular temperature of 25 °C. The large negative value of TΔS°av, together with the also large and negative value of ΔCp°av, suggests large conformational changes and important EEC, thus causing the small average value of ΔG° for protein folding, which is enough to guarantee both protein stability and molecular flexibility to allow for adaptation to the chemical potentials of the environment. Our analysis suggests that EEC may be the quantum-mechanical evolutive mechanism to make functional proteins adaptative to environmental temperature and metabolite concentrations. The analysis of protein folding data, compared with those of protein–ligand interaction, allows us to suggest strategies to overcome EEC in the design of new drugs.

Biophysica doi: 10.3390/biophysica5010001

Authors: Herbert Schneckenburger Christoph Cremer

Light microscopy has emerged as one of the fundamental methods to analyze biological systems; novel techniques of 3D microscopy and super-resolution microscopy (SRM) with an optical resolution down to the sub-nanometer range have recently been realized. However, most of these achievements have been made with fixed specimens, i.e., direct information about the dynamics of the biosystem studied was not possible. This stimulated the development of live cell microscopy imaging approaches, including Low Illumination Fluorescence Microscopy, Light Sheet (Fluorescence) Microscopy (LSFM), or Structured Illumination Microscopy (SIM). Here, we discuss perspectives, methods, and relevant light doses of advanced fluorescence microscopy imaging to keep the cells alive at low levels of phototoxicity.

Biophysica doi: 10.3390/biophysica4040047

Authors: Eleonora Calzoni Nicolò Montegiove Alessio Cesaretti Agnese Bertoldi Gaia Cusumano Giovanni Gigliotti Carla Emiliani

Microplastics (MPs) are widespread environmental pollutants that have drawn significant attention due to their possible health risks to humans and animals, as well as their extensive presence in ecosystems. Recent growing evidence highlights a remarkable relationship between MPs and extracellular vesicles (EVs), nanoscale particles involved in intercellular communication. The purpose of this review was to investigate how the relationships between MPs and EVs can affect cellular functions and how this interaction could impact environmental conditions leading to broader ecological risks. The interaction patterns and bioactivity of both MPs and EVs are strongly influenced by biophysical characteristics such as hydrophobicity, surface charge, and particle size, which have received particular attention from the scientific community. Recent studies indicate that MPs affect EV distribution and their capacity to function appropriately in biological systems. Additionally, MPs can modify the molecular cargo of EVs, which may result in alterations of cell signaling pathways. Understanding the interactions between MPs and EVs could provide important opportunities to comprehend their potential effects on human health and environmental systems, especially when it comes to cancer development, endocrine, metabolic, and inflammatory disorders, and ecological disruptions. This review emphasizes the necessity of multidisciplinary research to clarify the molecular and biophysical mechanisms regulating the interaction between MPs and EVs.

Biophysica doi: 10.3390/biophysica4040046

Authors: Conor M. J. Buchanan Eric O. Aboagye Lee J. Evitts Michael J. D. Rushton Tim A. D. Smith

Targeted Auger emitters are being considered as a cancer treatment owing to the high linear energy transfer of Auger electrons. When targeted to cancers, this allows for a highly efficient treatment with a low risk of damage to surrounding healthy tissue. The purpose of this study was to determine the most DNA-damaging Auger emitters from a range of radionuclides, some of which are clinically utilised. A Monte Carlo method-based software (Geant4-DNA version 10.7) was used to determine the energy deposition and number of DNA double-strand breaks from Auger (and internal conversion) electrons imposed on a tetranucleosome. The Auger emitters, 119Sb and 103Pd, have similar or slightly greater damaging properties compared to 123I, 111In, and 89Zr. 193mPt demonstrated the greatest therapeutic potency. Whilst 125I was highly damaging, its relatively long half-life (60 days) makes it less desirable for clinical use. Geant4-DNA modelling identified the radionuclide 193mPt as being highly favourable for use in radiotherapy.

Biophysica doi: 10.3390/biophysica4040045

Authors: Emmanuel Egun Tia Wilson Zuri A. Rashad Rominna Valentine Tayloria N. G. Adams

Cellular heterogeneity, an inherent feature of biological systems, plays a critical role in processes such as development, immune response, and disease progression. Human mesenchymal stem cells (hMSCs) exemplify this heterogeneity due to their multi-lineage differentiation potential. However, their inherent variability complicates clinical use, and there is no universally accepted method for detecting and quantifying cell population heterogeneity. Dielectrophoresis (DEP) has emerged as a powerful electrokinetic technique for characterizing and manipulating cells based on their dielectric properties, offering label-free analysis capabilities. Quantitative information from the DEP spectrum, such as transient slope, measure cells’ transition between negative and positive DEP behaviors. In this study, we employed DEP to estimate transient slope of various cell populations, including relatively homogeneous HEK-293 cells, heterogeneous hMSCs, and cancer cells (PC3 and DU145). Our analysis encompassed hMSCs derived from bone marrow, adipose, and umbilical cord tissue, to capture tissue-specific heterogeneity. Transient slope was assessed using two methods, involving linear trendline fitting to different low-frequency regions of the DEP spectrum. We found that transient slope serves as a reliable indicator of cell population heterogeneity, with more heterogeneous populations exhibiting lower transient slopes and higher standard deviations. Validation using cell morphology, size, and stemness further supported the utility of transient slope as a heterogeneity metric. This label-free approach holds promise for advancing cell sorting, biomanufacturing, and personalized medicine.

Biophysica doi: 10.3390/biophysica4040044

Authors: Igor D. Zlotnikov Sergey S. Krylov Natalya G. Belogurova Alexander N. Blinnikov Victor E. Kalugin Elena V. Kudryashova

Cyclodextrins (CDs) are natural cyclic oligosaccharides with the ability to form inclusion complexes with various organic substances. In this paper, we investigate the potential of CD complex formation to enhance the antibacterial activity and antioxidant properties of poorly soluble bioactive agents, such as chalcones, chromenes, stilbenoids and xanthylium derivatives, serving as potential adjuvants, in comparison with standard antiseptics. The interaction of these bioactive agents with the hydrophobic pocket of methyl-β-cyclodextrin (MCD) was confirmed using spectroscopic methods such as UV-vis, FTIR, 1H and 13C NMR, mass-spectrometry. CD-based delivery system allows for combining multiple active agents, improving solubility, antibacterial efficacy by enhancing penetration into target bacterial cells (E. coli selectivity demonstrated via confocal microscopy). Novel compounds of chalcones and stilbenoids derivatives additionally enhance efficacy by inhibiting bacterial efflux pumps, increasing membrane permeability, and inhibiting bacterial enzymes, and showed a synergy when used in combination with metronidazole. The intricate relationship between the structural characteristics and functional properties of chalcones and stilbenoids in terms of their antibacterial and antioxidative capabilities is revealed. The substituents within aromatic rings significantly influence this activity, where position of electron-donating methoxy groups playing a crucial role. Among chalcones, stilbenoids, ana xanthyliums, the compounds caring a benzodioxol ring, analogous to natural bioactive compounds like apiol, dillapiol, and myristicin, emerge as prominent antibacterial activity. To explore the possibility to create theranostic formulations, we used fluorescent markers to visualize target cells, antiseptics to provide antibacterial activity, and bioactive agents as chalcones acting as adjuvants. Additionally, new antioxidant compounds were found such as Xanthylium derivative (R351) and chromene derivative: 1-methyl-3-(2-amino-3-cyano-7-methoxychromene-4-yl)-pyridinium methanesulfate: the pronounced antioxidant properties of these substances are observed comparable to quercetin in the efficiency. Rhodamine 6G, gentian violet, and Congo Red exhibit good antioxidant properties, although their activity is an order of magnitude lower than that of quercetin. However, they have remarkable potential due to their multifaceted nature, including the ability to visualize target cells. The most effective theranostic formulation is the combination of the antibiotic (metronidazole) + dye/fluorophore (methylene blue/rhodamine 6G) for visualization of target cells + adjuvant (chalcones or xanthylium derivatives) for antiinflammation effect. This synergistic combination, results in a promising theranostic formulation for treating bacterial infections, with enhanced efficiency, selectivity and minimizing side effects.

Biophysica doi: 10.3390/biophysica4040043

Authors: Diliara R. Khaibrakhmanova Polina R. Kuzivanova Bulat R. Gainutdinov Timur I. Magsumov Alena A. Nikiforova Igor A. Sedov

The effect of sodium alginate on the denaturation and aggregation behavior of bovine serum albumin and hen egg-white lysozyme was studied. Large amounts of polysaccharide increase the thermal stability of albumin due to the weak binding interactions. At the same time, sodium alginate can reduce the quantity of amyloid fibrils formed by albumin under denaturing conditions, which is a consequence of the stabilization of the native protein form by glycan binding. In the case of lysozyme, the polysaccharide has no influence on the thermal stability of the protein in 2 M guanidinium hydrochloride. However, the inhibition of fibril formation with an increase in the lag time was observed, which is explained by the binding of sodium alginate to lysozyme fibrils, but not to the protein monomer. The molecular nature of the binding interactions between alginate and the studied proteins was elucidated using molecular docking and known experimental structures of glycan–protein complexes.

Biophysica doi: 10.3390/biophysica4040042

Authors: Ahmed N. Fayad Diego Mazo-Durán David G. Míguez

Cells compartmentalize biochemical processes using physical barriers in the form of membranes. Eukaryotes have a wide diversity of membrane-based compartments that can be used in this context, with the main ones being the extracellular membrane, which separates the inside from the outside of the cell, and the nuclear membrane, which separates the nucleus from the cytoplasm. The nuclear membrane not only isolates and protects the DNA and the transcription and replication processes from the other processes that are occurring in the cytoplasm but also has an active role in the regulation of cellular signaling. The TGF-β pathway is one of the most important and conserved signaling cascades, and it achieves compartmentalization using a well-tuned balance between the import and export rates of the active and inactive forms of key proteins. Thus, compartmentalization serves as an additional regulatory mechanism, physically isolating transcription factors from their targets, influencing the dynamics and strength of signal transduction. This contribution focuses on this biophysical layer of regulation, using the TGF-β pathway to illustrate the molecular mechanisms underlying this process, as well as the biological consequences of this compartmentalization. We also introduce a simplified mathematical formulation for studying the dynamics of this process using a generalized approach.

Biophysica doi: 10.3390/biophysica4040041

Authors: Giuseppe De Luca Vittorio Ferrara Bruno Pignataro Valeria Vetri Giuseppe Sancataldo

The interactions and structural organization of water molecules play a crucial role in a wide range of physical, chemical, and biological processes. The ability of water to form hydrogen bonds (H-bonds) underpins its unique properties and enables it to respond dynamically to various environmental factors. These interactions at the molecular level may affect vital processes like protein folding, enzyme activity, and cellular organization. The presence of solutes and spatial constraints can alter the H-bonding network of water, and these effects are ubiquitous in the biological environment. In this study, we analyzed the fluorescence of 2-acetyl-6-(dimethylamino)naphthalene (ACDAN) fluorescence emission in water solutions containing kosmotropic and chaotropic salts and in agar hydrogels. Recently, this dye has proven invaluable in studying water network structure and dynamics, as its fluorescence signal changes based on the local dielectric environment, revealing variations in the dipolar relaxation of water. Our results show that ACDAN spectral response correlates with the degree of water ordering, providing important insights into solute–water interactions and water dynamics in free and confined environments.