Biophysica, Volume 6, Issue 2 (April 2026) – 21 articles

One of the most puzzling and unsolved challenges in molecular biology is understanding how proteins fold. Despite having advanced predictive tools that can accurately estimate the native structures of proteins, we still lack a comprehensive model that explains how amino acid sequences dictate folding pathways and trajectories. This manuscript introduces a novel treatment for the issue by employing the “principle of least action.” This approach enables us to explore an intriguing question: how does a protein achieve its native state at a constant folding rate and within a biologically plausible time frame? A response to this inquiry will help us understand why proteins must fold along specific pathways and identify the boundary conditions that limit their availability. Furthermore, the principle of least action—together with the effective trajectory conjecture—enables us to explain why different proteins could exhibit the same folding rate. Finally, it will enable us to provide an in-depth description of the genesis and solution of Levinthal’s paradox. Our results are expected to pave the way for a more profound understanding of how proteins fold, shedding light on how the amino acid sequence and its surrounding environment encode the protein’s folding pathways and, consequently, the protein’s three-dimensional structure. Full article

Deubiquitinases, or DUBs, have emerged as pivotal regulators of cellular homeostasis, coordinating the delicate balance between protein ubiquitination and deubiquitination. Their versatile roles span from controlling protein turnover to modulating signal transduction pathways, thereby influencing diverse cellular processes, including DNA damage repair, apoptosis, and immune responses. This review comprehensively explores the current understanding of DUBs, elucidating their structural diversity, catalytic mechanisms, physiological functions, and implications in human diseases. Moreover, we discuss the therapeutic potential of targeting DUBs in various pathological conditions, highlighting recent advancements and challenges in developing DUB-specific inhibitors. Full article

Quality by design (QbD) is a systematic approach focused on achieving consistent, predictable quality based on predefined objectives. Unlike traditional methods, QbD prioritizes risk assessment and management, which significantly enhances the robustness of the analytical method. In this study, we initiated factor screening using a three-factor, two-level design to evaluate three independent variables: flow rate, pH, and mobile phase composition. To further investigate the interaction of these variables, we employed Central Composite Design (CCD). This allows us to apply response surface methodology to the Critical Analytical Attributes (CAAs), specifically retention time, peak area, and symmetry factor, by conforming to the method’s robustness. The combination of pregabalin and duloxetine hydrochloride (HCl) dosage form was determined using a straightforward, exact, specific, and accurate reverse-phase HPLC approach. The results showed retention times of 3.265 min and 4.318 min for duloxetine HCl and pregabalin, respectively. Pregabalin demonstrated linearity from 100 to 200 μg/mL (R² = 0.998), whilst duloxetine HCl demonstrated linearity between 20 and 120 μg/mL (R² = 0.997). Lower LOD values of 0.925 µg/mL and 0.853 μg/mL and LOQ values of 2.809 μg/mL and 2.587 μg/mL of pregabalin and duloxetine HCl, respectively, suggest good sensitivity for the technique. The drug content of the commercial formulation may thus be determined using the recommended method. This technique can be used for standard quality control studies to simultaneously estimate pregabalin and duloxetine HCl. The novelty of the present studies lies in the development of a robust RP-HPLC method for simultaneous estimation of pregabalin and duloxetine HCl using a systematic AQbD approach, enhancing robustness, reproducibility, and reliability, making it highly suitable for routine quality control and regulatory applications. Full article

Ischemic stroke induces complex molecular responses that disrupt subcellular organelles’ function and contribute to brain injury, yet the temporal changes of organelle-specific transcriptomic remodeling remain to be investigated. In this study, we performed in silico analysis of publicly available transcriptomic data from isolated brain microvessels of transient middle cerebral artery occlusion (tMCAO) mouse model. Using in silico approaches, we analyzed differential gene expression at 24 h (acute phase) and 7 d (intermediate phase) post-stroke, focusing on mitochondria, endoplasmic reticulum (ER), and Golgi apparatus. Functional enrichment (Gene Ontology, KEGG) and protein–protein interaction network analyses were performed. Our analysis of the data revealed that at 24 h post-stroke, all three organelles exhibited marked transcriptional remodeling, where mitochondrial pathways showed disrupted metabolic and redox regulation; ER pathways indicated activation of biosynthetic processes, stress signaling, and ferroptosis; and Golgi-related genes reflected altered vesicular trafficking and glycosylation. By 7 d, mitochondrial alterations subsided, whereas ER and Golgi pathways displayed downregulation of metabolic and neuronal signaling processes, indicating persistent dysfunction and incomplete microvascular recovery. Phase-specific drug–gene interaction analysis will be useful to understand temporal organelle-associated transcriptional organization and to guide future investigations of neurovascular remodeling after ischemic stroke. Full article

The effects of static magnetic fields (SMFs) on fibroblast proliferation and migration remain debated, largely due to variability in field intensity, orientation, and exposure duration, as well as the predominant use of endpoint-based assays that may not fully capture the temporal dynamics of cellular responses. Thus, it remains unclear whether reported SMF effects reflect changes in proliferation, migration, or both. Here, we examined how SMFs with different field configurations affect NIH3T3 fibroblast behavior. Three setups were tested: a field generated by two neodymium magnets arranged in a face-to-face configuration on opposite sides of the culture dish (SMF1) and single-magnet setups with either the north (SMF2 and SMF2a) or south poles (SMF3 and SMF3a) facing the cells. SMF1 was associated with a 41% increase in proliferation relative to control, while single-cell migration velocities, directional persistence, and collective wound closure showed no detectable changes. In contrast, SMF2 and SMF3, as well as their low-field variants SMF2a and SMF3a, did not produce significant effects. Our results suggest that a specific SMF configuration is associated with increased fibroblast proliferation without detectable changes in migration parameters under the tested conditions. This integrative approach helps contextualize prior divergent findings by suggesting that SMF effects may be configuration-dependent, thereby contributing to a more rational application of magnetic stimulation in cellular and tissue engineering contexts. Full article

Cellular protein quality control comprises the ubiquitin proteasome system, autophagy, and molecular chaperones, which maintain proteostasis in healthy tissues. The failure of these cellular and molecular pathways, which normally safeguard the proteome, can cause and even exacerbate amyloidoses, the abnormal accumulation of proteins into amyloid fibrils that drive neurodegeneration. Amyloidoses can also damage peripheral organs; examples include light chain amyloidosis, cardiac amyloidosis, and renal amyloidosis. Restoring proteostasis and preventing protein aggregation is therefore an active area of research, with several promising strategies under investigation. Among these approaches, small-molecule modulators that restore proteostasis are attractive candidates because they may simultaneously rescue multiple quality control mechanisms and remodel aggregates to improve their accessibility to endogenous degradation pathways. Here, we propose that amyloid pathology disrupts multiple proteostasis pathways simultaneously, creating a feedforward cascade in which the breakdown of interconnected proteostasis networks drives progressive protein aggregation, which in turn propels proteostasis collapse. Pharmacological interventions targeting protein aggregation offer opportunity to rescue interconnected proteostasis networks, which could, in turn, cooperatively manage or eliminate pathogenic amyloid burden. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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 (µ_k) 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. Full article