Accessible Surface Research Articles

Designing hypothesis of substituted naphthyridines as anti-HIV agent: A QSAR Approach

HIV-1 Integrase is a validated drug target for anti-HIV therapy. It is an essential enzyme required for replication of the AIDS-virus. 1,3,4-oxadiazole substituted naphthyridine derivatives act against HIV integrase and thus have the potential to become a part of anti-HIV drug regime. In present study, we have carried out QSAR study of 1,3,4-oxadiazole substituted naphthyridine derivatives. Stepwise multiple linear regression analysis was performed to derive QSAR models and was evaluated for statistical significance and predictive power. The best QSAR model was selected for anti-HIV activity, having correlation coefficient (R) = 0.862, standard error of estimation (SEE) = 0.271 and cross validated squared correlation coefficient (Q2) = 0.676. The QSAR model indicates that shape index, partition coefficient and solvent accessible surface area play an important role in the anti-HIV activities of 1,3,4-oxadiazole substituted naphthyridine derivatives. The results of the present study may be useful in designing more potent analogues.

Electrospun Nanofiber Supported Nano/Mesoscale Covalent Organic Frameworks Boost Iodine Sorption.

Covalent Organic Frameworks (COFs) are benchmark materials for iodine sorption, but their use has largely been confined to crystalline bulk forms. In this state, COFs face diffusion limitations leading to slow sorption kinetics. To address this, a series of [2+3] imine-linked COFs with varying particle sizes and morphologies (mesospheres, nanoflowers, and bulk) is synthesized. Reducing particle size (from 826±48 to 412±22 nm) and adding surface protrusions in COF mesospheres improved iodine adsorption capacity (7.6 to 8.5 g g⁻¹), kinetics (K80%, 0.61 to 0.76 g g⁻¹ h⁻¹), and chemisorption efficiency. Notably, solvothermally synthesized (120°C, 5 d) crystalline bulk COF with accessible porous surfaces exhibited faster kinetics (K80%, 1.13 g g⁻¹ h⁻¹) than nano/mesoCOFs.This implies nano- and mesoCOFs exhibit surface aggregation that passivates their external binding sites and hinders iodine diffusion and mass transfer.To prevent this, morphologically controlled COF particles are immobilized onto electrospun polyacrylonitrile nanofibrous membranes via in situ growth strategy, creating a hierarchical structure that improved iodine diffusion pathways. This modification increased iodine sorption kinetics by 98%-153% and strengthened the charge-transfer process compared to COF powders.

In silico Investigation of the Pro-apoptotic Potential of Syringic Acid Analog

Background: Conformational changes in BAX are associated with the activation of its pro-apoptotic potential. Previously, small molecule BAX antagonists have been shown to bring about apoptosis by inducing conformational changes in BAX by direct binding to the serine 184 site of BAX. Methods: In this article, we have proposed that syringic acid analog SA14 can incur apoptosis by directly binding to and inducing conformational changes in BAX. The pro-apoptotic potential of SA14 has been investigated using an in silico structure-based approach, i.e., docking and molecular dynamics computations are employed to study the binding of SA14 to the residues of the active site of BAX. Results: Based on docking results, four BAX-SA14 complexes, each representative of a cluster of conformations, have been selected for molecular dynamics simulations. The root mean square deviation has indicated the formation of stable conformations for two of the complexes. Other parameters, such as root mean square fluctuation, radius of gyration, and solvent accessible surface area, have been used to confirm the results, which have indicated favorable binding between BAX and SA14. Conclusion: Overall, the results have indicated that SA14 can bring about stable conformational changes in BAX and shows merit as a potential BAX-activating pro-apoptotic agent worthy of further experimental studies.

Astigmatism Quantification for Depth Localization of Bubbles and Tracers across Curved Surfaces

Abstract The present combined theoretical/experimental study addresses the impact of astigmatism on the two-phase flow diagnostics across the curved surfaces of liquid test-rig containments. In the present context, the target application is the two phase leakage-flow diagnostics across the annular housing gaps of oil-injected rotary positive displacement compressors (RPDC). Earlier studies by the authors identified the Defocusing Particle Tracking Velocimetry (DPTV) and Interferometric Particle Imaging (IPI) as particularly promising combination of flow measurement techniques to investigate the liquid and disperse gas phases inside the annular housing gap of RPDCs. The test-rig-specific influence of astigmatism on the resulting optical transfer function for a quantitative evaluation of the recorded defocused particle images (PI) is first compared to the theoretically derived circular PI diameter upon pure defocussing and subsequently tested for both classes of PIs, i.e DPTV and IPI. To mimic the optical configuration of optically accessible lateral surfaces of typical RPDC test rigs, a circular beaker glass (CBG) of comparable diameter is chosen for the experimental campaign. The results are discussed and future efforts for advanced PI-evaluation strategies are outlined on the grounds of the drawn conclusions.

Seaweed-like Co-MOF/Cu(OH)2/CF composite as an advanced pre-catalyst for oxygen evolution reaction

Directly applying metal-organic frameworks (MOFs) as electrocatalysts or pre-catalysts for the oxygen evolution reaction (OER) faces significant challenges, due to the lack of exposed active sites, low electronic conductivity, and poor structure stability. Herein, a novel alkaline leaching-solvothermal strategy is proposed to synthesize seaweed-like Co-MOF/Cu(OH)2 on copper foam (CF), which is applied as self-supporting pre-catalyst for OER. After electrochemical activation, Co-MOF/Cu(OH)2/CF only requires an overpotential of 279 mV at 50 mA cm-2 and operates steadily for 72 h with negligible activity deterioration. The high activity and stability mainly benefit from the unique structural arrangement, in which Cu(OH)2 nanoneedles serve as firm substrates to grow and stabilize Co-MOFs. The two-dimensional Co-MOFs with nanometer thickness and high accessible surfaces could expose sufficient metal coordination sites, which are ready for reconstruction and electrocatalysis. Additionally, CF framework helps to maintain the self-supporting structure and acts as current collector to enhance the charge/electron transfer efficiency during OER.

Synthesis of silver-decorated titanium dioxide nanostructured films for enhanced visible light photocatalysis

Titanium dioxide (TiO2) has been extensively investigated for applications in photocatalysis due to its stability, nontoxicity, and robust photocatalytic properties. Although thin films of TiO2 are effective in wastewater treatment, their dense structure limits surface accessibility. The oblique angle deposition (OAD) technique can be used to create high surface area nanostructured thin films essential for photocatalytic applications. In this study, OAD was used to grow TiO2 thin films. To extend the activity to the visible light region, plasma-reduced silver (Ag) particles were coupled to the TiO2 surface. The Ag-decorated TiO2 (Ag-TiO2) nanostructured films were fabricated using a custom-built magnetron sputter deposition system with OAD technique capability. Different substrate angles of 0°, 35°, and 70° with respect to the target normal were used. The films were characterized for their structural, compositional, and optical properties. The photodegradation performance was evaluated using methylene blue (MB) as the test analyte under visible light irradiation. The results showed a significant improvement in degradation efficiency using plasma-reduced Ag-TiO2. Substrates tilted at 70° achieved the highest MB degradation efficiency of 89.84% after 5 h exposure. This tilt angle also revealed high surface roughness and high surface area. By tilting the substrate with respect to the target, high surface area thin films can be fabricated. This technique is ideal for applications that depend on the area of contact, such as photocatalysis.

Increasing warm-season evaporation rates across European lakes under climate change

Lakes represent a vital source of freshwater, accounting for 87% of the Earth’s accessible surface freshwater resources and providing a range of ecosystem services, including water for human consumption. As climate change continues to unfold, understanding the potential evaporative water losses from lakes becomes crucial for effective water management strategies. Here we investigate the impacts of climate change on the evaporation rates of 23 European lakes and reservoirs of varying size during the warm season (July–September). To assess the evaporation trends, we employ a 12-member ensemble of model projections, utilizing three one-dimensional process-based lake models. These lake models were driven by bias-corrected climate simulations from four General Circulation Models (GCMs), considering both a historical (1970–2005) and future (2006–2099) period. Our findings reveal a consistent projection of increased warm-season evaporation across all lakes this century, though the magnitude varies depending on specific factors. By the end of this century (2070–2099), we estimate a 21%, 30% and 42% average increase in evaporation rates in the studied European lakes under RCP (Representative Concentration Pathway) 2.6, 6.0 and 8.5, respectively. Moreover, future projections of the relationship between precipitation (P) and evaporation (E) in the studied lakes, suggest that P-E will decrease this century, likely leading to a deficit in the availability of surface water. The projected increases in evaporation rates underscore the significance of adapting strategic management approaches for European lakes to cope with the far-reaching consequences of climate change.

AutoGeoFAIR: A framework for evaluating the sharing degree of open earth surface system data based on extended FAIR principles

Expert participation and collaboration are an efficient, transparent, credible and innovative way to implement open scientific data management, evaluation and analytical mining. An unprecedented surge in openly accessible earth surface system (ESS) data across web platforms has emerged. This data is characterized by dispersion, multi-sourcing, heterogeneity, and multi-modality, and predominantly manifests through thematic sharing websites, data services, metadata, and journal publications, particularly data papers. Addressing the pressing need to swiftly evaluate the sharing degree of these openly shared ESS data sets constitutes a new frontier in this domain. Current frameworks and tools designed for open scientific data sharing lack direct applicability to the intricacies of earth surface systems, thereby impeding users’ access to data of high sharing degree. This study introduces an ESS-oriented evaluation tool tailored to assess the sharing degree of open ESS data. Central to this tool are the components of an evaluation metric system and an evaluation model. Leveraging the principles of FAIR (Findable, Accessible, Interoperable, and Reusable), a comprehensive sharing degree assessment index comprising 19 secondary metrics categorized under 5 primary metrics is formulated. Furthermore, a novel evaluation model for quantifying the sharing degree of open scientific data is proposed, integrating hierarchical analysis and the entropy method. This integration effectively captures the nuanced uncertainties and variability inherent in the data, enhancing the accuracy and reliability of evaluation outcomes. The resulting software tool facilitates rapid and quantitative assessment of open scientific data sharing degree within the ESS domain, thereby enabling the recommendation of highly-shared datasets to researchers and modelers alike.

Thermodynamic and Conformational Analysis of GTRNase and Lysozyme Proteins Under Thermal Variations using Molecular Dynamics Simulations

This study examines the thermodynamic and conformational dynamics of GTRNase and lysozyme proteins under varying temperature conditions using molecular dynamics (MD) simulations. The objective is to evaluate their structural stability, folding behavior, and thermodynamic properties to understand their responses to thermal fluctuations. Protein structures were retrieved from the Protein Data Bank (PDB), refined to remove extraneous molecules, and simulated using GROMACS 2022.2 under NVT and NPT ensembles, spanning temperatures from 270 K to 380 K. The results revealed distinct behaviors for the two proteins. GTRNase exhibited a slight escalation in radius of gyration (Rg) from 1.434 nm at 270 K to 1.445 nm at 380 K, suggesting a marginal conformational expansion. In contrast, lysozyme maintained a consistent Rg of 1.38 nm over the same temperature range, indicating structural compactness. Root mean square deviation (RMSD) data demonstrated increased flexibility in both proteins, with GTRNase escalating from 0.115 nm at 270 K to 0.179 nm at 380 K and lysozyme rising from 0.102 nm to 0.142 nm across the temperature range. Solvent-accessible surface area (SASA) for GTRNase fluctuated between 69 nm² and 73 nm², with the lowest value observed at 300 K and the highest at 370 K. These findings highlight that GTRNase is more susceptible to thermal perturbations than lysozyme, showing greater conformational flexibility and expansion. This research underscores the utility of MD simulations in exploring protein behavior and provides valuable insights for applications in protein engineering and drug design.

Ultrathin Ni(OH)2 nanosheets: Microemulsion assisted hydrothermal synthesis and application in advanced hybrid supercapacitors

Nickel hydroxide (NH) has garnered considerable attention in supercapacitors due to its large theoretical capacity, low cost, and eco-friendliness. However, insufficient accessible surface area and poor cyclic stability have hindered its large-scale application. In this study, ultrathin NH nanosheets were synthesized using a microemulsion-assisted hydrothermal strategy. The H2O/EtOH volume ratio (K(H2O/EtOH)) significantly influences the specific surface area (SA) of the prepared NH nanosheets. The Ni(OH)2 nanosheets (NH-1–1) exhibited a thickness of ca. 4 nm and a remarkable SA of 285.0 m2 g–1 at a K(H2O/EtOH) value of 1/1. The NH-1–1 electrode demonstrated an impressive specific capacity of 824.5 C g–1 at a current density of 500 mA g–1. Additionally, the NH-1–1//activated carbon hybrid supercapacitor (NH-1–1//AC HSC) delivered 91.3 F g–1 at 500 mA g–1 with an energy density of 34.5 Wh kg–1 at 412.5 W kg–1. Even when the power density was increased to 8,250 W kg–1, the NH-1–1//AC HSC still provided 22.4 Wh kg–1. After 20,000 consecutive cycles at 5.0 A g–1, the capacitance retention of this device was 89.5 %. Impressively, the NH-1–1//AC HSC operated a clock for ca. 32 min. The exceptional energy storage capability of the NH-1–1 is attributed to its large SA and ultrathin structure.

Comparing enzymatic post-treatments by endoglucanase (EG) and lytic polysaccharide monooxygenase (LPMO) on microfibrillated cellulose (MFC) to enhance cellulose film fabrication

Cellulose is the world's most abundant natural polymer and it can be used as a substitute for fossil derived products. The work described here evaluated the use of mono-component enzyme treatment, using endoglucanase (EG) and lytic polysaccharide monooxygenase (LPMO), to improve the properties of micro-fibrillated cellulose (MFC) produced from mechanically refined kraft pulp. Endoglucanase treatment of the pulp significantly reduced the degree of polymerization (DP) of the cellulose by promoting fiber cutting. In contrast, LPMO treatment only slightly reduced the fiber length and pulp viscosity. However, the introduction of carboxylic acid groups by the action of LPMO appeared to enhance the accessible surface area of cellulose. Enzyme-treated MFC showed improved nano-fibrillation with transmittance and water retention values increased after both enzyme treatments. The cellulose films derived from enzyme-treated MFC showed enhanced mechanical properties with the LPMO-treated films showing superior tensile strength (77 MPa) and Young's modulus (3600 MPa). Thermogravimetric analysis (TGA) also indicated improved thermal stability for both enzyme-treated films. LPMO treatments proved more effective, promoting nano-fibrillation while maintaining fiber integrity and enhanced intermolecular interactions.

DFT-based, Monte Carlo and Grand Canonical Monte Carlo simulations of nitro-organic pollutants 4-nitrophenol, 2-nitrophenol, 9-nitroanthracene and nitrogen trifluoride interacting with water in zeolite imidazole framework (ZIF-8)

We report in this study the behaviour of adsorbed Nitrogen-volatile organic compounds (NVOCs) such as 2NP (2-Nitrophenol), 4NP (4-Nitrophenol), 9NAnt (9-Nitroanthracene), NF3 (Nitrogen trifluoride) with and without water in Zinc-Imidazolate Framework (ZIF-8) using the Density Functional Theory (DFT). The work considers both single and multiple molecular capture of different species of pollutants, along with theoretical research based on force fields to determine the maximum number of molecules that can be loaded inside the material. Negative adsorption energy is obtained when each pollutant is considered separately or in mixtures. The values range from −2.6 kJ/mol to −137.1 kJ/mol depending on the size of adsorbed species. Modelling of the adsorbed pollutants on ZIF-8 towards the use of the code CASTEP show the possible interaction with the imidazole rings of the bulk crystal. The interaction energy (Eint) indicates that the capture of 2NP and 4NP is more favourable with H2O than 9NAnt and NF3. More specifically, Eint corresponding to one water molecule with one pollutant (4NP, 2NP, 9NAnt, NF3) is −0.473, −5.580, +0.588, and +8.307 kJ/mol, respectively. The Connolly surface was calculated to gain a better understanding of the volume and surface accessibility of ZIF-8, which helps to predict and support CASTEP results. Finally, an isotherm study was conducted using a Monte Carlo simulation, which proved useful in interpreting the most probable mechanism of the competing mixed capture. The results obtained were similar to those provided by Density Functional Theory (DFT).

Unusual Hydrophobic Property of Blue Fluorescent Amino Acid 4-Cyanotryptophan.

It is a common belief that the negative heat capacity change (ΔCp) associated with protein folding, which is a manifestation of the hydrophobic effect, results from a decrease in the solvent accessible hydrophobic surface area. Herein, we investigate the conformational energy landscape and dynamics of a tetrapeptide composed of two glycine and two 4-cyanotryptophan residues using time-resolved fluorescence spectroscopy, molecular dynamics simulations, and density functional theory calculations and find that, contrary to this expectation, the hydrophobic association of two 4-cyanotryptophan side chains leads to a positive ΔCp (approximately 543 J K-1 mol-1). Furthermore, we find that promoting one of the 4-cyanotryptophans to its excited electronic state strengthens this self-association. Taken together, our results provide not only insight into how modification of an aromatic amino acid can affect its hydrophobicity but also a potential strategy for designing protein sequences that can fold (unfold) at high (low) temperatures.

Modulating electronic density of active metal site via MXene intercalated by alkali ions for superior hydrogen production

As the core of a catalyst, the active site plays a crucial role in determining the activity and selectivity in hydrogen production reactions. Herein, the size and surface electron density of bimetallic alloy nanoparticles (NPs) were engineered by (alkali ions)-intercalated-Ti3C2Tx MXene, in which alkali ions were removed by water after the intercalation of Ti3C2Tx. The intercalation of alkali ions can effectively increase the interlayer spacing of Ti3C2Tx, enhance the surface accessibility, and improve the interaction between active metal species and Ti3C2Tx, resulting in monodisperse, ultrafine, and surface electron-rich active metal NPs. Resultantly, the obtained NiPt/(Li+)-Ti3C2Tx exhibits an exceptional catalytic performance with a turnover frequency (TOF) value of 3200 h−1 toward complete dehydrogenation of N2H4·H2O at 323 K, which is about 43 and 4-times higher than that of pristine NiPt NPs (75 h−1) and them on Ti3C2Tx without alkali ions intercalation (787 h−1), respectively, and surpassing all the reported catalysts for this dehydrogenation reaction. Additionally, this catalyst also shows an ultrahigh catalytic performance (7317 h−1) for complete dehydrogenation of N2H4BH3 under the same reaction conditions. This work for the first time found that the more electrons on the surface of the active center, the better the activity for hydrazine decomposition, providing inspiration for regulating catalytic active sites and designing efficient heterogeneous catalysts to achieve nitrogen-based hydride activation.

Unraveling the physiochemical characteristics and molecular insights of Zein protein through structural modeling and conformational dynamics: a synergistic approach between machine learning and molecular dynamics simulations

This research article presents a comprehensive investigation into the three-dimensional structure, physicochemical characteristics and conformational stability of the Zein protein. Machine learning (ML) based homology modeling approach, was employed to predict the 3D structure of Zein protein. Convolutional neural networks (CNNs) were utilized for refining the model, capturing complex spatial features and improving decoy refinement. The predicted 3D structure of Zein protein showed a high-confidence score, i.e. C-score of 0.96. Physiochemical characteristic was also analyzed to investigate its protonation and deprotonation behavior across a range of pH values. A comprehensive analysis of the titration curve and electrostatic charges was performed to uncover valuable molecular insights into the zein protein’s charge distribution, electrostatic interactions and potential conformational changes. Molecular dynamics (MD) simulations were performed to analyze the zein structural behavior under different pH values (2.0, 4.5, 6.8, 10.0 and 12.5), ionic strengths (0 mM, 25 mM, 50 mM, 75 mM, 100 mM) and temperatures (300K, 350K, 375K). Our results demonstrated the influence of these factors on zein protein’s stability and conformational dynamics. At extreme pH values of 2.0 and 12.5, the Zein protein exhibited increased structural deviations and potential unfolding, while intermediate pH values closer to the protein’s isoelectric point (pI) demonstrated more compact and stable conformations. Analysis of root mean square deviation, radius of gyration, solvent accessible surface area and Ramachandran plot provided clear understandings of the protein’s compactness and surface exposure, confirming the impact of pH, ionic strength and temperature on the protein’s conformation.

Quantification of electrochemically accessible iridium oxide surface area with mercury underpotential deposition.

Research drives development of sustainable electrocatalytic technologies, but efforts are hindered by inconsistent reporting of advances in catalytic performance. Iridium-based oxide catalysts are widely studied for electrocatalytic technologies, particularly for the oxygen evolution reaction (OER) for proton exchange membrane water electrolysis, but insufficient techniques for quantifying electrochemically accessible iridium active sites impede accurate assessment of intrinsic activity improvements. We develop mercury underpotential deposition and stripping as a reversible electrochemical adsorption process to robustly quantify iridium sites and consistently normalize OER performance of benchmark IrOx electrodes to a single intrinsic activity curve, where other commonly used normalization methods cannot. Through rigorous deconvolution of mercury redox and reproportionation reactions, we extract net monolayer deposition and stripping of mercury on iridium sites throughout testing using a rotating ring disk electrode. This technique is a transformative method to standardize OER performance across a wide range of iridium-based materials and quantify electrochemical iridium active sites.

Enhanced Photosensitizer Wettability via Anchoring Competition of Violet Phosphorus Quantum Dots for Breakthroughs in Photodynamic Film Sterilization.

Wettability is important for photodynamic film sterilization since higher wettability enhances the capture of bacteria in contact with photosensitizers. Herein, a small number of violet phosphorus quantum dots (VPQDs) are anchored into hypericin bacterial cellulose films (VP/Hy-BC films) to improve wettability, reducing the water contact angle from 56.8° to 33.0°. This modification facilitated more effective interactions between the bacteria and photosensitizers, rapidly inactivating 7 log10 CFU/mL of Staphylococcus aureus within 60min. First-principles calculations and molecular dynamics simulations reveal that VPQDs, with their low spatial site resistance, reduced the intermolecular Hy self-aggregation force. This increased the solvent-accessible surface area of VP/Hy by ≈25.7%, thereby decreasing hydrophobic photosensitizer aggregation. Consequently, more active sites are exposed, remarkably improving the photoelectron transfer efficiency. VP/Hy-BC demonstrated exceptional efficacy in inhibiting bacterial proliferation; for instance, it extended beef shelf life by up to 10 days. The findings of this study will aid the development of health-conscious, eco-friendly, and efficient antimicrobial packaging films.

Utilizing machine learning and molecular dynamics for enhanced drug delivery in nanoparticle systems

Materials data science and machine learning (ML) are pivotal in advancing cancer treatment strategies beyond traditional methods like chemotherapy. Nanotherapeutics, which merge nanotechnology with targeted drug delivery, exemplify this advancement by offering improved precision and reduced side effects in cancer therapy. The development of these nanotherapeutic agents depends critically on understanding nanoparticle (NP) properties and their biological interactions, often analyzed through molecular dynamics (MD) simulations. This study enhances these analyses by integrating ML with MD simulations, significantly improving both prediction accuracy and computational efficiency. We introduce a comprehensive three-stage methodology for predicting the solvent-accessible surface area (SASA) of NPs, which is crucial for their therapeutic efficacy. The process involves training an ML model to forecast the many-body tensor representation (MBTR) for future time steps, applying data augmentation to increase dataset realism, and refining the SASA predictor with both augmented and original data. Results demonstrate that our methodology can predict SASA values 299 time steps ahead with a 40-fold speed improvement and a 25% accuracy increase over existing methods. Importantly, it provides a 300-fold increase in computational speed compared to traditional simulation techniques, offering substantial cost and time savings for nanotherapeutic research and development.

A new insight into the mechanism of loading of Granisetron, Naltrexone and Risperidone in poly(ortho ester) and poly (lactic-co-glycolic acid) as the controlled release drug delivery systems using a computational molecular approach

Owing to the good biocompatibility, bioavailability, biodegradability, and low toxicity of polymeric nanoparticles, considerable research interest has been generated. These polymeric carriers enhance the therapeutic index and improve controlled drug release. In this study, molecular dynamics (MD) simulation of six designed systems were conducted to compare poly(ortho ester) (POE) and poly (lactic-co-glycolic acid) (PLGA) polymeric nanoparticles as carriers and delivery systems for three drugs: Granisetron, Naltrexone, and Risperidone. These drugs are FDA-approved under the brand name SUSTOL (Granisetron for anti-nausea and vomiting post-heavy chemotherapy), VIVITROL (Naltrexone for managing alcohol or opioid use disorder), and RISPERDAL CONSTA (Risperidone for treating schizophrenia). Various parameters, such as interaction energy, radius of gyration (Rg), solvent accessible surface area (SASA), distance, hydrogen bond, radial distribution function (RDF), and root mean square fluctuation (RMSF), were investigated. The MD simulations show good consistency with FDA-approved data, clearly illustrate why PLGA is suitable for NAL and RIS, and POE for GRS, as carriers in drug delivery. The findings, detailing mechanisms of polymer-drug interactions, have potential applications in (i) manufacturing and production of novel sustained-release drugs and biopolymers, (ii) identifying suitable patterns, and (iii) rationally designing new controlled-release drugs based on future artificial intelligence methods.

Exploring B-cell epitope conservation and antigenicity shift in current COVID-19 variants: Analyzing spike-antibody interactions for therapeutic uses

SARS-CoV-2, responsible for the global COVID-19 pandemic, has undergone significant genetic changes, leading to various variants impacting transmissibility, severity, and vaccine efficacy. The methodology involved evaluating SARS-CoV-2 variants designated by WHO as Variants of Interest (VOIs) and Variants Under Monitoring (VUMs). Several noteworthy mutations including G446S, K417N, T478K, E484A, N501Y, and Y505H exhibit a strong pattern of convergent evolution across all these variants, particularly at antigenic sites within the spike protein. Conformational epitopes mapping and antigenicity shift analyses implicated epitope changes which were compared for therapeutic purposes. VUMs BA.2.86 and XBB.2.3 show significant antigenicity changes and epitope dynamics, correlating with high root mean square deviation values and epitope expansions or contractions. Nonsynonymous mutations are predominant in all variants, suggesting functional changes affecting transmissibility and immune evasion. VOIs XBB.1.5, BA.2.86, and CH.1.1 show high solvent-accessible surface area and radius of gyration, indicating structural expansion and increased epitope availability. In contrast, stable VOI EG.5.1 displays minimal structural changes and moderate epitope expansions. We evaluated two classes of antibodies for their effectiveness in neutralizing SARS-CoV-2 variants. Antibodies CC12.1 and P4A1 from Class I, alongside CV07-250, P5A-2G9, and MW05 from Class II, display strong binding across multiple variants, indicating broad neutralizing capabilities. Specifically, P4A1 shows the highest affinity for EG.5 and EG.5.1, while MW05 exhibits the strongest binding to XBB.1.5, CH.1.1, and XBB.2.3, highlighting their potent neutralization potential. This study aims to elucidate epitope variations in evolving SARS-CoV-2 strains, offering critical insights for developing targeted interventions against current challenges posed by the virus.