Search Results (140)

The deamidation rate is relatively high for Asn residues with Phe as the C-terminal adjacent residue in γS-crystallin, which is one of the human crystalline lens proteins. However, peptide-based experiments indicated that bulky amino acid residues on the C-terminal side impaired Asn deamination. In this study, we hypothesized that the side chain of Phe affects the Asn deamidation rate and investigated the succinimide formation process using quantum chemical calculations. The B3LYP density functional theory was used to obtain optimized geometries of energy minima and transition states, and MP2 and M06-2X calculations were used to obtain the single-point energy. Activation barriers and rate-determining step changed depending on the orientation of the Phe side chain. In pathways where an interaction occurred between the benzene ring and the amide group of the Asn residue, the activation barrier was lower than in pathways where this interaction did not occur. Since the aromatic ring is oriented toward the Asn side in experimentally determined structures of γS-crystallin, the above interaction is considered to enhance the Asn deamidation. Full article

Quantum Dots (QDs) are small semiconductor nanoparticles (<10 nm) with strong, relatively stable, and tunable luminescent properties, which are increasingly applied in the sensing and detection of various analytes, including metal ions, biomarkers, explosives, proteins, RNA/DNA fragments, pesticides, drugs, and pollutants. In this review, we critically assess recent developments and advancements in luminescent QD-based sensors from an analytical perspective. We collected, tabulated, and analyzed relevant data reported in 124 peer-reviewed articles. The key analytical figures of merit, including the limit of detection (LOD), excitation and emission wavelengths, and size of the particles were extracted, tabulated, and analyzed with graphical representations. We calculated the geometric mean and median LODs from those tabulated publications. We found the following geometric mean LODs: 38 nM for QD-fluorescent-based sensors, 26 nM for QD-phosphorescent-based sensors, and an impressively low 0.109 pM for QD-chemiluminescent-based sensors, which demonstrate by far the best sensitivity in QD-based detection. Moreover, AI-based sensing methods, including the ATTBeadNet model, optimized principal component analysis(OPCA) model, and Support Vector Machine (SVM)-based system, were reviewed as they enhance the analytical performance of the detection. Despite these advances, there are still challenges that include improvements in recovery values, biocompatibility, stability, and overall performance. This review highlights trends to guide the future design of robust, high-performance, QD-based luminescent sensors. Full article

This study focuses on exploring potential inhibitors of the Marburg virus interferon inhibitory domain protein (MARV-VP35), which is responsible for immune evasion and immunosuppression during viral manifestation. A combination of in silico techniques was applied, including structure-based pharmacophore virtual screening, molecular docking, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis, molecular dynamics (MD), and molecular stability assessment of the identified hits. The docking scores of the 14 selected ligands ranged between −6.88 kcal/mol and −5.28 kcal/mol, the latter being comparable to the control ligand. ADMET and drug likeness evaluation identified Mol_01 and Mol_09 as the most promising candidates, both demonstrating good predicted antiviral activity against viral targets. Density functional theory (DFT) calculations, along with relevant quantum chemical descriptors, correlated well with the docking score hierarchy, and molecular electrostatic potential (MEP) mapping confirmed favorable electronic distributions supporting the docking orientation. Molecular dynamics simulations further validated complex stability, with consistent root mean square deviation (RMSD), root mean square fluctuation (RMSF), and secondary structure element (SSE) profiles. These findings support Mol_01 and Mol_09 as viable candidates for experimental validation. Full article

Quantum mechanics (QM) revolutionizes drug discovery by providing precise molecular insights unattainable with classical methods. This review explores QM’s role in computational drug design, detailing key methods like density functional theory (DFT), Hartree–Fock (HF), quantum mechanics/molecular mechanics (QM/MM), and fragment molecular orbital (FMO). These methods model electronic structures, binding affinities, and reaction mechanisms, enhancing structure-based and fragment-based drug design. This article highlights the applicability of QM to various drug classes, including small-molecule kinase inhibitors, metalloenzyme inhibitors, covalent inhibitors, and fragment-based leads. Quantum computing’s potential to accelerate quantum mechanical (QM) calculations is discussed alongside novel applications in biological drugs (e.g., gene therapies, monoclonal antibodies, biosimilars), protein–receptor dynamics, and new therapeutic indications. A molecular dynamics (MD) simulation exercise is included to teach QM/MM applications. Future projections for 2030–2035 emphasize QM’s transformative impact on personalized medicine and undruggable targets. The qualifications and tools required for researchers, including advanced degrees, programming skills, and software such as Gaussian and Qiskit, are outlined, along with sources for training and resources. Specific publications on quantum mechanics (QM) in drug discovery relevant to QM and molecular dynamics (MD) studies are incorporated. Challenges, such as computational cost and expertise requirements, are addressed, offering a roadmap for educators and researchers to leverage quantum mechanics (QM) and molecular dynamics (MD) in drug discovery. Full article

For the interaction of angiotensin II (AngII) with AngII type 1 receptors (AT₁R), two potential proton hopping pathways have been identified, each associated with distinct physiological outcomes. The octapeptide AngII (Asp¹-Arg²-Val³-Tyr⁴-Ile⁵-His⁶-Pro⁷-Phe⁸) appears to form a charge relay system (CRS) in solution in which the C-terminal carboxylate abstracts a proton from the His⁶ imidazole group, which, in turn, abstracts a proton from the Tyr⁴ hydroxyl (OH) group, creating a tyrosinate anion. When AngII binds to the AT₁R, the CRS can be reconstituted with D281 of the receptor taking up the role of the Phe⁸ carboxylate in the tripartite interaction, whilst the Phe⁸ carboxylate forms a salt bridge with K199 of the receptor. As a consequence, the Tyr⁴ OH of AngII is positioned with accessibility to either the Phe⁸ carboxylate (bound to K199) or the His⁶ imidazole (activated by D281), thereby creating a potential gating mechanism for AT₁R receptor signaling. This study summarizes evidence based on structure activity data for various analogs wherein Tyr⁴ OH interaction with His⁶ imidazole (CRS formation) leads to G protein sequestration and vasoconstriction, whereas Tyr⁴ OH interaction with Phe⁸ carboxylate (bound to K199) engenders arrestin-mediated vasodilation and receptor desensitization. These findings, combined with quantum mechanical (semiempirical) calculations of CRS proton transfer presented herein, provide insights for the therapeutic targeting of angiotensin receptor blockers (sartans) and the development of second-generation drugs (bisartans). Full article

The SARS-CoV-2 main protease (Mpro), essential for viral replication, remains a prime target for antiviral drug design against COVID-19 and related coronaviruses. In this study, we present a systematic investigation into the molecular determinants of Mpro inhibition using an integrated approach combining large-scale data mining, cheminformatics, and quantum chemical calculations. A curated dataset comprising 963 high-resolution structures of Mpro–ligand complexes—348 covalent and 615 non-covalent inhibitors—was mined from the Protein Data Bank. Cheminformatics analysis revealed distinct physicochemical profiles for each inhibitor class: covalent inhibitors tend to exhibit higher hydrogen bonding capacity and sp³ character, while non-covalent inhibitors are enriched in aromatic rings and exhibit greater aromaticity and lipophilicity. A novel descriptor, Weighted Hydrogen Bond Count (WHBC), normalized for molecular size, revealed a notable inverse correlation with aromatic ring count, suggesting a compensatory relationship between hydrogen bonding and π-mediated interactions. To elucidate the energetic underpinnings of molecular recognition, 40 representative inhibitors (20 covalent, 20 non-covalent) were selected based on principal component analysis and aromatic ring content. Quantum mechanical calculations at the double-hybrid B2PLYP/def2-QZVP level quantified non-bonded interaction energies, revealing that covalent inhibitors derive binding strength primarily through hydrogen bonding (~63.8%), whereas non-covalent inhibitors depend predominantly on π–π stacking and CH–π interactions (~62.8%). Representative binding pocket analyses further substantiate these findings: the covalent inhibitor F2F-2020198-00X exhibited strong hydrogen bonds with residues such as Glu166 and His163, while the non-covalent inhibitor EDG-MED-10fcb19e-1 engaged in extensive π-mediated interactions with residues like His41, Met49, and Met165. The distinct interaction patterns led to the establishment of pharmacophore models, highlighting key recognition motifs for both covalent and non-covalent inhibitors. Our findings underscore the critical role of aromaticity and non-bonded π interactions in driving binding affinity, complementing or, in some cases, substituting for hydrogen bonding, and offer a robust framework for the rational design of next-generation Mpro inhibitors with improved selectivity and resistance profiles. Full article

New ways of ensuring sustainable development in various areas of life are being intensively researched. One of the key priorities is to maximize the use of invaluable natural ingredients in cosmetic products while minimizing the negative impact on the environment. In this study, a three-component natural composite based on amber, diatomite, and Phytokeratin^TM (hydrolyzed plant protein) was developed using mechanochemical synthesis. The goal was to maximize the release of biologically active substances, such as succinic acid and Phytokeratin^TM, in aqueous solution. The physicochemical properties of the materials were characterized using Scanning Electron Microscopy (SEM), thermogravimetric (TG) and differential thermogravimetric (DTG) analysis, Fourier Transform Infrared (FTIR) spectroscopy, and Ultraviolet–Visible (UV-Vis) spectrophotometry. Additionally, Density Functional Theory (DFT) was used to perform quantum chemical calculations and characterize molecular interactions in the composite. The optimized composite demonstrated favorable release characteristics and structural properties, confirming its suitability for cosmetic applications. DFT calculations revealed the potential molecular-level interactions between the organic components, indicating the stability and functional integration of the composite. The resulting innovative composite was successfully incorporated into eco-friendly cosmetic formulations, including a solid shampoo bar and a nail conditioner. Full article

Alzheimer’s disease (AD), one of the neurodegenerative disorders, afflicts negatively across the whole world. Due to its complex etiology, no available treatments are disease-altering. This study aimed to explore isolated saponins profiles from Platycodon grandiflorum in the binding pockets of six target proteins of AD using computational and quantum chemistry simulations. Initially, saponin compounds were docked to AD enzymes, such as GSK-3β and synapsin I, II, and III. The subsequent research from MD simulations of the best three docked compounds (polygalacin D2, polygalacin D, and platycodin D) suggested that their profiles match with the binding of standard active drugs like ifenprodil and donepezil to the six enzymes. Moreover, analyzing DFT quantum calculations of top-scoring compounds fully unravels their electronic and quantum properties and potential in anti-AD. The subtle differences between polygalacin D and D2, and platycodin D, were studied at the level of theory DFT/B3LYP, showing that the electron-donating effect of the hydroxy ethyl group in platycodin D rendering this compound of moderate electrophilicity and reactivity. Polygalacin D2 diglucoside substituent in position-2 contributed to its best binding and intermolecular interactions more than polygalacin D and prosapogenin D, which acted as the negative decoy drug. Full article

Ribavirin, 1-(β-D-Ribofuranosyl)-1H-1,2,4-triazole-3-carboxamide, which is included in the list of drugs recommended in the guidelines for the diagnosis and treatment of SARS-CoV-2 infection, has been the subject of experimental and theoretical investigation. The most thermodynamically stable polymorphic form was studied using ¹H-¹⁴N NQR cross-relaxation, periodic DFT/QTAIM/RDS/3D Hirshfeld surfaces, and molecular docking. For the first time, a ¹H-¹⁴N cross-relaxation spectrum of ribavirin was recorded and interpreted. Twelve resonance frequencies were assigned to four inequivalent nitrogen positions in the molecule using combined experimental techniques and solid-state quantum chemical calculations. The influence of the structural alteration on the NQR parameters was modeled using GGA/RPBE. The differences in the binding pattern of ribavirin, acadesine, inosine, guanosine, and favipiravir-ribofuranosyl in the solid state and the protein-ligand complex were assessed to elucidate the differences in the binding mechanism at the molecular level due to aglycone modification. The replacement of the carbon adjacent to the ribose with nitrogen, in conjunction with the absence of oxygen at the 2-position of the ring, resulted in an increased flexibility of the RBV structure in comparison to the favipiravir-ribofuranosyl structure. The present study identified the intramolecular hydrogen bond NH···N in RBV as playing a crucial role in the formation of a quasi-five-membered ring. However, this bond was proven to be too weak to force positioning of the amide group in the ring plane. The ribofuranosyl in RBV inhibits tautomerism and freezes the conformation of the amide group. The results of the molecular dynamics simulations demonstrated that RBV and favipiravir-ribofuranosyl incorporated into the RNA primer exhibited comparable stability within the protein binding region. The titular anti-butterfly (inverted butterfly) effect is associated with the consequences of both the changes in aglycone moiety and the neighborhood alteration. Seven structure-binding strength indices and six novel quadrupolar indices defined in this study have been proven to facilitate the evaluation of the similarity of binding motifs in the solid state and protein-ligand complex. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continually undergoes mutation, leading to variants with altered pathogenicity and transmissibility. The Omicron variant (B.1.1.529), first identified in South Africa in 2021, has become the dominant strain worldwide. It harbors approximately 50 mutations compared to the original strain, with 15 located in the receptor-binding domain (RBD) of the spike protein that facilitates viral entry via binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. How do these mutated residues modulate the intermolecular interactions and binding affinity between the RBD and ACE2? This is a question of great theoretical importance and practical implication. In this study, we employed quantum chemical calculations at the B2PLYP-D3/def2-TZVP level of theory to investigate the molecular determinants governing Omicron’s ACE2 interaction. Comparative analysis of the Omicron and wild-type RBD–ACE2 interfaces revealed that mutations including S477N, Q493R, Q498R, and N501Y enhance binding through the formation of bifurcated hydrogen bonds, π–π stacking, and cation–π interactions. These favorable interactions counterbalance such destabilizing mutations as K417N, G446S, G496S, and Y505H, which disrupt salt bridges and hydrogen bonds. Additionally, allosteric effects improve the contributions of non-mutated residues (notably A475, Y453, and F486) via structural realignment and novel hydrogen bonding with ACE2 residues such as S19, leading to an overall increase in the electrostatic and π-system interaction energy. In conclusion, our findings provide a mechanistic basis for Omicron’s increased infectivity and offer valuable insights for the development of targeted antiviral therapies. Moreover, from a methodological perspective, we directly calculated mutation-induced binding energy changes at the residue level using advanced quantum chemical methods rather than relying on the indirect decomposition schemes typical of molecular dynamics-based free energy analyses. The strong correlation between calculated energy differences and experimental deep mutational scanning (DMS) data underscores the robustness of the theoretical framework in predicting the effects of RBD mutations on ACE2 binding affinity. This demonstrates the potential of quantum chemical methods as predictive tools for studying mutation-induced changes in protein–protein interactions and guiding rational therapeutic design. Full article

Spermidine is a natural autophagy-inducer and anti-aging compound. Herein, we investigated a potential autophagy-independent mechanism of spermidine, namely its capability to directly impede LDL oxidation, an early step in atherogenesis. In our in vitro-model, LDL oxidation was induced by the addition of CuCl₂ in the presence of increasing concentrations of spermidine, and the degree of oxidation of the lipid, as well as of the protein part of LDL, was measured. We found that spermidine concentration-dependently inhibited the production of lipid hydroperoxides, malondialdehyde, and oxidation-specific immune epitopes in the LDL particle, associated with decreased relative electrophoretic mobilities, respectively. For example, the LPO content was significantly lower when LDL was oxidized in the presence of 500 µg/mL spermidine (26.9 ± 1.6 nmol/mg LDL) than in the absence of spermidine (180.6 ± 7.7 nmol/mg LDL, p < 0.0001). When oxLDL was obtained under increasing spermidine concentrations, its cytotoxicity in EA.hy926 cells concentration-dependently decreased. Quantum chemical calculations show that the reaction between spermidine and hydroxyl radicals is exergonic. We conclude that spermidine is a direct inhibitor of LDL oxidation due to its capability to scavenge hydroxyl radicals. Thus, spermidine supplementation might be a suitable tool to impede atherogenesis and associated (cardio)vascular diseases. Further prospective clinical studies are needed to evaluate the potential atheroprotective/health-promoting effects of spermidine-rich diets. Full article

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. Full article

We start presenting an overview on recent applications of linear polymers and networks in condensed matter physics, chemistry and biology by briefly discussing selected papers (published within 2022–2024) in some detail. They are organized into three main subsections: polymers in physics (further subdivided into simulations of coarse-grained models and structural properties of materials), chemistry (quantum mechanical calculations, environmental issues and rheological properties of viscoelastic composites) and biology (macromolecules, proteins and biomedical applications). The core of the work is devoted to a review of theoretical aspects of linear polymers, with emphasis on self-avoiding walk (SAW) chains, in regular lattices and in both deterministic and random fractal structures. Values of critical exponents describing the structure of SAWs in different environments are updated whenever available. The case of random fractal structures is modeled by percolation clusters at criticality, and the issue of multifractality, which is typical of these complex systems, is illustrated. Applications of these models are suggested, and references to known results in the literature are provided. A detailed discussion of the reptation method and its many interesting applications are provided. The problem of protein folding and protein evolution are also considered, and the key issues and open questions are highlighted. We include an experimental section on polymers which introduces the most relevant aspects of linear polymers relevant to this work. The last two sections are dedicated to applications, one in materials science, such as fractal features of plasma-treated polymeric materials surfaces and the growth of polymer thin films, and a second one in biology, by considering among others long linear polymers, such as DNA, confined within a finite domain. Full article

Background: Superparamagnetic properties and excitation independence have been incorporated into carbon-decorated manganese ferrite nanodots (MnFe@C) to introduce an economical and safer multimodal agent for use in both T1-T2 MRI and fluorescence-based imaging to replace the conventional highly toxic heavy metal contrast agents. Methods: The surface conjugation of 8-anilino-1-naphthalenesulfonate (ANS) to MnFe@C nanodots (ANS-MnFe@C) enhances both longitudinal and transverse MRI relaxation, improves fluorescence for optical imaging, and increases protein detection sensitivity, showing higher multimodal efficacy in terms of molar relaxivity, radiant efficiencies, and fluorescence sensitivity compared to MnFe@C. Results: The band gap energy was determined using Tauc’s equation to be 3.32 eV, while a 72% quantum yield demonstrated that ANS-MnFe@C was highly fluorescent, with the linear range and association constant calculated using the Stern–Volmer relation. The synthesized ANS-MnFe@C demonstrated excellent selectivity and sensitivity for bovine serum albumin (BSA), with a nanomolar detection limit of 367.09 nM and a broad linear range from 0.015 to 0.225 mM. Conclusions: In conclusion, ANS-MnFe@C holds ease of fabrication, good biocompatibility, as assessed in A375 cells, and an effective pH-sensitive doxorubicin release profile to establish anticancer activity in lung cancer cell line (A549), highlighting its potential as an affordable therapeutic agent for multimodal imaging, drug delivery, and protein sensing. Full article

Polyacetylene (PA) compounds, as natural products, exhibit remarkable properties and distinctive chemical activities. Three structurally similar C14-PA compounds—Echinophorin D, Echinophorin B, and Echinophorin A—extracted from plants demonstrate varying biological activities on the Transient Receptor Potential Channel A1 (TRPA1) protein, which belongs to the TRP (Transient Receptor Potential) family. In the current study, we investigated the binding modes of these three PA compounds with TRPA1 using molecular dynamics (MD), molecular docking, binding free energy calculations, and quantum mechanics/molecular mechanics (QM/MM) methods. Initially, a putative binding site (site-II) in TRPA1 was identified for these compounds; Echinophorin B was found to stabilize the upward A-loop of TRPA1, which is critical for its activation. Furthermore, the binding affinity calculations of PA compounds through molecular fragment decomposition indicate that the arrangement of two triple bonds and one double bond in C14-PA compounds is vital for regulating TRPA1 bioactivity. Additionally, the lipophilic and electronic properties of the three molecules were analyzed in relation to binding affinity, establishing a correlation between TRPA1 activity and these molecular properties. Full article