Journal of Molecular Graphics and Modelling

Pain is a global health burden, highlighting the need for effective therapeutic strategies. Gabapentin (GBP) and pregabalin (PGB), used for neuropathic pain, act primarily through 2{delta} auxiliary subunits of voltage-gated calcium channels. Caenorhabditis elegans expresses UNC-36, an ortholog of mammalian 2{delta} proteins involved in calcium-channel function and nocifensive behavior. However, whether UNC-36 preserves the molecular features required for gabapentinoid recognition remains unclear. We compared human 2{delta}-1 and UNC-36 using sequence and structural analyses, molecular docking, 500-ns molecular dynamics simulations, interaction profiling, principal component and free-energy landscape analyses, and MM/GBSA calculations. UNC-36 preserved the overall architecture of the mammalian gabapentinoid-binding region despite substantial sequence divergence, and both ligands remained associated with the modeled pockets. However, residue-level interaction networks differed between species. Human 2{delta}-1 showed greater contributions from aromatic interactions, whereas UNC-36 relied more prominently on cationic and hydrogen-bond donor interactions mediated by Arg501 and Arg503. The human 2{delta}-1-PGB complex maintained the most stable ligand pose, whereas 2{delta}-1-GBP showed greater positional variation. In UNC-36, PGB exhibited greater deviation from its initial binding pose than GBP. The first two principal components accounted for more conformational variance in UNC-36 complexes than in human complexes. MM/GBSA estimates showed that PGB was energetically favored over GBP in human 2{delta}-1, whereas GBP was favored over PGB in UNC-36. These findings show that conservation of the gabapentinoid-binding architecture is accompanied by species-specific differences in interaction chemistry, conformational dynamics, and estimated binding energetics, providing a molecular basis for interpreting C. elegans gabapentinoid responses in a translational context.

Cancer is a serious public health problem, and is becoming more common, with a projected increase in deaths and more than 25 million new cases in coming decades. A number of molecular mechanisms are involved in the tumoral process, with one of them, never in mitosis A-related kinase 2 (NEK2), a serine/threonine protein kinase, being a frequent target of amplification in various malignancies that is responsible for chromosomal instability, aneuploidy and activation of several oncogenic pathways. Available kinase inhibitors are not yet optimized in terms of their pharmacokinetic properties for clinical use, and current therapies, such as chemotherapeutic agents or immunotherapies are often limited by their resistance. In silico methods represent an effective tool to search for novel potent inhibitors, before testing in animals, with time constraints and limited resources. To find new inhibitors of NEK2, we used E pharmacophore-based modeling and structure based virtual screening in this study. NEK2 was chosen as the target for therapeutic intervention and an energy optimized pharmacophore model was employed to screen the Enamine REAL library of millions of compounds. Pharmacodynamic and Pharmacokinetic properties of the Top hits were tested using ADMET profiling. These were further screened using molecular docking (standard precision and extra precision) and virtual screening to obtain three lead compounds 1, 2, and 3 which have docking score of -7.414, -8.037 and -7.562 respectively. MM-GBSA calculations were used to estimate the binding free energies for these complexes, which were determined to be -54.92, -54.18 and -49.23 kcal/mol. Lastly, 100 ns molecular dynamics simulations have been run to evaluate complex stability in dynamic situations. The overall results of the MD showed the overall stability of the NEK2-ligand complexes, and thus these three compounds are promising NEK2 inhibitor candidates and could be further validated in vitro and in vivo for clinical application. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/742111v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@14e9cfeorg.highwire.dtl.DTLVardef@24ec78org.highwire.dtl.DTLVardef@20be75org.highwire.dtl.DTLVardef@1b80c02_HPS_FORMAT_FIGEXP M_FIG C_FIG

The spread and evolution of antimicrobial resistance (AMR) pose significant threats to public health, food safety, and sustainable development. Metallo bea lactamases (MBLs), a class of carbapenemases that hydrolyze carbapenems, often considered last resort antibiotics, are of particular concern and underscore the urgent need to develop effective inhibitors. Recent advancements in bicyclic boronate inhibitors represent significant progress toward this goal. Although the mechanistic basis of NDM1 inhibition by bicyclic boronate inhibitors remains incompletely elucidated, this study systematically characterizes the binding profiles and intermolecular interaction landscapes between NDM1 and four cyclic boronic acid based inhibitors, vaborbactam (RPX7009), taniborbactam (VNRX 5133), xeruborbactam (QPX7728), and ledaborbactam (VNRX-5236). We established the NDM-1-mediated hydrolysis of two representative carbapenem antibiotics, meropenem and imipenem, as the reference system for comparative analysis. While conventional docking workflows often struggle to model metalloenzyme active sites accurately, the AMDock (Assisted Molecular Docking) platform, integrated with AutoDock optimized zinc force field, enables robust and reliable docking simulations for this enzyme family. Our AMDock based molecular docking not only identified the critical NDM1 binding site residues governing hydrogen-bond networks with ligands, but also revealed that bicyclic boronate inhibitors show substantially greater binding stability than both carbapenems and their monocyclic boronate counterparts. A follow-up 100 ns all atom molecular dynamics simulation in GROMACS provided atomistic level evidence for this enhanced performance: RMSD, RMSF, radius of gyration, continuous hydrogen bonding occupancy, and 2D free energy landscape analyses all consistently supported the higher binding affinity of bicyclic boronates. Ultimately, this study characterizes two promising drug candidates, QPX7728 and VNRX5133, as competitive inhibitors that can effectively rescue carbapenem activity against NDM1 MBL mediated antimicrobial resistance. This visualization elucidates interactions between NDM1 and its two ligand classes, carbapenem antibiotics and cyclic boronate inhibitors. It reveals the stability and interaction strength underlying the distinct inhibition pattern of bicyclic boronate inhibitors in the enzyme active site, offering a promising strategy to combat antibiotic resistance.

Engulfment and Cell Motility protein 1 (ELMO1) regulates cell migration, phagocytosis, and cytoskeletal remodeling, positioning it as a compelling therapeutic target across kidney diseases, oncology, enteric infections and inflammation. Despite this potential, no approved therapeutics or clinically validated small-molecule modulators of ELMO1 currently exist. ELMO1 functions by forming a complex with DOCK180 (or DOCK2) to activate the small GTPase Rac1, and the recent structural resolution of the ELMO1/DOCK2 complex now provides an opportunity to target this protein-protein interface directly. Here, we present the first investigation into the druggability of the ELMO1/DOCK2 complex and report the initial virtual screening to identify small-molecule inhibitors of this interaction. Molecular dynamics (MD) and free energy level (FEL) studies were carried out to validate the potential of the predicted hits. This work establishes a computational framework for the development of the first generation of ELMO1-targeted therapeutics. In addition to demonstrating the drugability of ELMO1, this work introduces two open-source Python tools for the rapid analysis and visualization of protein-protein interaction and ligand-protein MD trajectories from DESMOND output files. These tools are designed to be broadly accessible, offering practical utility to the wider DESMOND user community.

Identifying short peptides that bind therapeutically relevant proteins is a practical step toward developing peptide-based inhibitors. Here we screened 64 tetrapeptides for binding to the IL-17A homodimer using classical all-atom molecular dynamics simulations (GROMACS 2022.2, FF19SB force field, TIP3P water, 200 ns production per complex). Binding was ranked by a composite score that combines short-range interaction energies (Coul-SR + LJ-SR), close-contact frequency, mean intermolecular distance, and hydrogen bond occupancy. The tetrapeptide LYS-THR-CYS-ASP achieved the highest score in the set (composite score 2.85, total interaction energy -556 kJ/mol, average 8.0 H-bonds). Across all 64 simulations, electrostatic interactions accounted for approximately 72% of the total interaction energy. Stronger binders tended to contain charged and polar residues (Asp, Glu, Cys, Arg, Thr), while weaker binders were enriched in hydrophobic residues. Contact analysis identified a recurring interaction surface on IL-17A centered on cysteine and aromatic residues (Chain A: CYS87, Chain B:CYS196, A:HIS86, B:TYR175, B:HIS195), which we describe as a cysteine-aromatic cradle. These results nominate LYS-THR-CYS-ASP as a candidate for experimental binding validation and suggest simple sequence guidelines for designing IL-17A-targeting peptides.

Amylose contributes to starch crystallinity, but the stability of packed amylose double helices in water at elevated temperature remains insufficiently characterized. Here, we used molecular dynamics simulations to test whether chain length affects the short-timescale stability of A-type amylose oligomers in water. Six systems differing in chain length (6, 12, or 24 glucose units per chain) and oligomer size (isolated double strand or dodecamer of six double strands) were simulated, and five independent 1-s production runs were analyzed for each simulated condition. Oligomers with six glucose units showed structural collapse accompanied by increased water penetration. By contrast, dodecamers with 12 or 24 glucose units largely retained packed double-helical organization over the simulated timescale, although fraying was observed at their ends. These results indicate that chain length and lateral packing strongly affect the early structural response of amylose-like crystalline segments in hot water. The present simulations do not establish the ultimate fate of longer oligomers at longer timescales, but they identify a relative stability difference that is relevant to molecular interpretations of hydration-driven disordering in starch.

Kinema is a traditional fermented soybean food indigenous to the eastern Himalayan regions of Nepal and India. The fermentation process is primarily mediated by the bacterium Bacillus subtilis, which produces several bioactive compounds and enzymes with potential therapeutic applications. Considering the growing burden of cardiovascular diseases and the need for effective fibrinolytic agents for thrombolytic therapy, this study aimed to extract, partially purify, and evaluate the thrombolytic potential of kinemakinase derived from kinema prepared from white soybeans. Partial purification of the enzyme was achieved using ammonium sulfate precipitation. Thrombolytic activity was assessed in vitro using human blood clots, where three enzyme dilutions demonstrated clot lysis ranging from 66% to 68%, indicating considerable fibrinolytic potential. In silico analyses were also performed to investigate the structural and functional characteristics of the enzyme. The tertiary structure obtained from UniProt was modeled using the Robetta server and refined with GalaxyRefine. Docking with fibrin using ClusPro 2.0 and molecular dynamics simulations using iMODS confirmed favorable interaction and structural stability, while disulfide engineering enhanced protein stability. The findings suggest that kinema-derived kinemakinase may serve as a promising alternative thrombolytic agent, warranting further biochemical characterization and dosage optimization.

Interleukin-13 (IL-13) is an immunomodulatory cell signaling cytokine that has been implicated in neurodegenerative disease and chronic inflammation. IL-13 binds to its low and high affinity receptors, IL-13 receptor 1 (IL-13R1) and IL-13 receptor 2 (IL-13R2), respectively, with residence times that vary accordingly. As the binding kinetics of the cytokine-receptor complexes influence cellular responses, we employed the molecular dynamics (MD) simulation-based{tau} -random acceleration molecular dynamics method ({tau}RAMD) to compute relative residence times for wild-type (WT) IL-13 and 19 IL-13 mutants to the two receptors. Comparison with experimental kinetic data shows that the{tau} RAMD computations capture the trends in residence times. Analysis of simulated dissociation trajectories of the cytokine-receptor complexes reveals two distinct dissociation pathways of IL-13 from each of the receptors. This study thus pinpoints key determinants of the interaction of IL-13 with its receptors which could be targeted for therapeutic design. Statement of SignificanceCytokines are regulatory proteins that bind to cell surface receptors and thereby send signals to the cellular interior. Interleukin-13 (IL-13) is a cytokine that has a low and a high affinity receptor. It has important physiological roles, and its deregulation is involved in diseases such as atopic dermatitis and asthma. We employed a molecular dynamics simulation-based method to compute the effects of changes in the sequence of IL-13 on the lifetimes of complexes of IL-13 and its receptors. Comparison with experiments supports the validity of the computational approach and analysis of the simulations reveals two distinct ways in which IL-13 dissociates from each receptor. These results thus provide a map for targeting IL-13 - receptor interactions for the design of therapeutics.

Plant-derived small molecules possess highly diverse physicochemical properties, and the computational design of their protein recognition elements depends not only on the global structural quality of candidate backbones, but also on whether the local binding pocket, ligand-contact pattern, and predefined recognition conformation can be consistently retained after sequence design and structural back-prediction. To explore pocket-design strategies for different types of natural-product small molecules, this study selected capsaicin, (4R)-limonene, and quercetin as model ligands, representing a flexible amphipathic molecule, a compact hydrophobic monoterpene, and a rigid polyphenolic flavonoid scaffold, respectively, and covering the dimensions of pungent sensory flavor, volatile aroma, and flavonoid functional constituents. A ligand- physicochemical-property-guided computational design and multi-stage prioritization framework was established for candidate protein binders. The results showed that candidates with favorable initial global structural scores did not necessarily form reasonable local small-molecule binding pockets, indicating that evaluation of the local ligand environment is essential for candidate prioritization. After screening, 31 partial- pocket candidate backbones for capsaicin, 75 buried hydrophobic-pocket candidate backbones for (4R)-limonene, and 56 pocket-qualified candidate backbones for quercetin were obtained. Further sequence design and structural back-prediction analyses indicated that a subset of candidates could maintain the original pocket geometry and major ligand-contact patterns after sequence realization. Overall, these results suggest that the physicochemical properties of different plant-derived small molecules substantially influence the efficiency of de novo protein pocket formation, with compact hydrophobic ligands being more compatible with buried hydrophobic- pocket strategies, whereas flexible or multipolar ligands require a more refined balance between hydrophobic burial and polar exposure. This study provides a pre- experimental computational prioritization framework for natural-product small- molecule-recognizing proteins and offers candidate resources for subsequent protein expression, in vitro binding validation, active-constituent enrichment, and development of small-molecule biorecognition tools. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/743643v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@8fe6c2org.highwire.dtl.DTLVardef@176cef2org.highwire.dtl.DTLVardef@10c8201org.highwire.dtl.DTLVardef@2b28cf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Recent models describe drug release from polymeric nanoparticles through an analogy with the quantum tunneling effect, treating the delivery system as a static rectangular potential barrier. In this work, we argue that this analogy is structurally identical to the standard solution of the Schrodinger equation for a rectangular barrier, and that the introduction of a multifractal formalism to describe time evolution -- obtained via a formal Wick rotation (x [->] t) -- lacks direct physical justification. We propose, instead, to treat the barrier height as an effective function of time, Ueff(t) = U0 f(t), with f(t) varying slowly within the barrier region, reflecting the progressive degradation/swelling of the polymeric matrix, under two hypotheses for f(t)-- exponential decay and rational decay (Hill-type). Rather than the thick-barrier WKB approximation, the exact transmission formula is used throughout, which is real-analytic in f(t) and continues smoothly into the resonance (over-barrier) regime once the barrier collapses, avoiding the artificial step-like transitions produced by the WKB approximation used in earlier drafts of this work. Both hypotheses for f(t) predict a finite barrier collapse time, t*, whose dependence on the energy ratio m = U0/E differs qualitatively between them (t* {propto}ln m vs. t* {propto}(m-1)1/n), offering a distinguishable criterion from experimental release data. The model was tested against ex-vivo chicken-skin permeation kinetics of 5-FU digitized from Rata et al. [1] (three systems: NCA-1-5-FU, G-NCA-1-5-FU, G-5-FU). The exact formula substantially improved fit quality relative to the WKB approximation for all three systems. Fits were obtained by global optimization (differential evolution, polished with scipy.optimize.curve_fit for covariance estimates) rather than a single local search, which proved necessary: for G-5-FU and NCA-1-5-FU, the exponential family is well-identified (all parameter uncertainties below 11% and 6% of the estimates, respectively; R2 > 0.999), while the rational (Hill) family remained poorly identified for all three systems despite the improved formula - favoring, by parsimony, the simpler exponential model throughout. Only G-NCA-1-5-FU remained non-identified with m free. A sensitivity check fixing m at the G-5-FU-derived value (m = 1.377) resolves this non-identifiability for G-NCA-1-5-FU at negligible cost in fit quality, consistent with a shared energy ratio for that system; the same constraint applied to NCA-1-5-FU, however, degrades its (already well-identified) fit by a factor of [~]4 in maximum residual; its own energy ratio (m = 1.188 {+/-} 0.007) differs from the shared value by [~]4{sigma}, a formally significant difference, so a single universal m is rejected for the complete set of systems studied. Reference values from the original multifractal study [2-4] and candidate extensions to further aptamer-functionalized nanocarrier systems [5-7] are also discussed. We discuss the implications of this treatment and its limits of validity, and point out paths for further empirical validation.

Monobodies are fibronectin type-III-based binding proteins that specifically bind target proteins and regulate their functions. We previously identified monobodies that selectively recognize either the OPEN or CLOSED conformation of adenylate kinase (Adk), revealing that monobodies can discriminate distinct conformational states of a target protein. However, the molecular basis of OPEN-form recognition has remained unclear because the structure of the complex between an OPEN-form-specific monobody and Adk had not been determined. To address this issue, we determined the crystal structure of the complex between Adk and the OPEN-form-specific monobody OP-4, employing hierarchical clustering analysis of X-ray diffraction datasets. The structure revealed that OP-4 binds to the surface formed by the expanded LID and CORE domains of Adk. Mutations in the interface residues reduced the OP- 4-binding affinity, indicating that the crystallographically identified interface is also relevant in solution. In particular, R123 mutations markedly impaired OP-4 binding. Molecular dynamics simulations further suggested that the R123-D159-R156 hydrogen-bond network is retained in solution and may contribute to efficient complex formation. These findings establish the structural basis for monobody OP-4 binding to open-form Adk and identify the R123-centered interaction network as a key determinant of complex formation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC="FIGDIR/small/742914v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@4b529org.highwire.dtl.DTLVardef@1119ffcorg.highwire.dtl.DTLVardef@1e9469org.highwire.dtl.DTLVardef@1a17eaf_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe crystal structure of the OPEN-form adenylate kinase/monobody OP-4 complex was successfully determined. C_LIO_LIThe crystal structure revealed that OP-4 binds to surface formed by the expanded LID and CORE domains in adenylate kinase. C_LIO_LIIsothermal titration calorimetry measurements for adenylate kinase mutants confirmed that the binding modes observed in solution are consistent with those observed in the crystal structure. C_LIO_LIMolecular dynamics simulations suggested that the R123-D159-R156 hydrogen bond network prior to OP-4 binding is important for complex formation. C_LI

ObjectiveThe complement regulatory protein CD59 has been shown to promote SNARE complex assembly, yet its interaction with vesicle-associated membrane protein 2 (VAMP2) remains poorly characterized. This study aims to identify the key domain in VAMP2 that mediates the CD59 interaction and to evaluate whether CD59 point mutations affect SNARE complex assembly. MethodsThe interaction between CD59 and VAMP2 was examined by immunofluorescence confocal microscopy and co-immunoprecipitation (co-IP). The effect of CD59 on SNARE complex assembly was assessed by co-expressing CD59 with the three core SNARE proteins (syntaxin-1, SNAP-25, and VAMP2) and detecting complex formation by western blotting. Four CD59 single-point mutants were generated and evaluated in SNARE assembly assays. AlphaFold3 was employed to predict the interaction between CD59 and individual VAMP2 domains (confidence threshold: ipTM + pTM [≥] 0.75). Truncated VAMP2 constructs were further characterized by molecular dynamics simulations and co-IP. Results(1) CD59 directly bound VAMP2 and promoted SNARE complex assembly without altering individual SNARE protein levels. (2) All four CD59 single-point mutants retained the ability to promote SNARE assembly at a level comparable to wild-type CD59, despite showing differential effects on binding stability in molecular dynamics simulations. (3) The proline-rich (P-rich) N-terminal domain of VAMP2 was identified as the key binding interface; its deletion abolished the CD59 interaction, whereas deletion of the SNARE motif did not. ConclusionCD59 promotes SNARE complex assembly through interaction with the P-rich N-terminal domain of VAMP2. The examined point mutations do not impair this function, suggesting that these sites may tolerate substitutions or that redundant contact residues maintain the interaction.

Background and Purpose: Among new psychoactive substances, synthetic cannabinoid receptor agonists (SCRAs) encompass considerable structural diversity and show wide variation in cannabinoid receptor 1 (CB1) potency and efficacy, but the molecular and receptor-interaction characteristics underlying these differences remain unclear. We assessed the pharmacological profiles of 16 SCRAs and examined structural features associated with differences in CB1 potency and efficacy. Experimental Approach: CB1 agonist activity was measured in a CB1-G15-based Ca2+ assay, and cataleptic effects were assessed in mice. Ligand-receptor interactions were characterized by molecular docking to an active-state CB1 structure. Principal component analysis (PCA) was applied to residue-level interaction profiles, and the resulting scores were tested for associations with CB1 potency and efficacy. Key Results: Potency and efficacy varied widely across cellular and animal assays, with several SCRAs exhibiting different pharmacological responses across the two experimental systems. PCA identified an interaction pattern whose PC1 scores were significantly associated with Emax but not EC50, with contributions from activation-related CB1 residues including the PHE200-TRP356 toggle switch. Molecular descriptor analysis likewise identified structural features significantly associated with in vitro and in vivo Emax. Conclusion and Implications: Our findings suggest that CB1 efficacy is associated with distinct receptor-interaction patterns among structurally diverse SCRAs. Combining functional pharmacology with receptor-level interaction analysis provides structural insight into SCRA efficacy and may help prioritize emerging compounds for further pharmacological and behavioral evaluation.

IL-4Ra is a key regulatory receptor for type 2 inflammatory responses, signal transduce from IL-4 and IL-13 through binding with IL-13Ra or the gamma c chain to activate the downstream JAK1-STAT6 pathway. IL-4Ra is currently the most successful "golden target" in the field of allergic disease therapeutics. Its representative monoclonal antibody drug, dupilumab, through the dual blockade mechanism of IL-4/IL-13 has pioneered a new era of precision therapy for type 2 inflammation. In our manuscript, we employed large-scale deep learning-based computational design methods to de novo design mini-protein antagonists specific for both human and mouse IL-4Ra. The binding affinity was improved from 22.1 nM to 569 pM through partial diffusion. The design accuracy and binding specificity were verified through X-ray crystallography and biochemical studies. In vitro IL4/IL13 signal blockade assays revealed that de novo designed monomeric mini-protein antagonist exhibited comparable blockade ability to bivalent dupilumab. In vivo pharmacokinetic half-life studies demonstrated that fusion to an HSA-binding domain extended the half-life of the mini-protein antagonist from 2.7 hours to 60.6 hours. The IL-4Ra mini-protein antagonist had excellent expression levels, solubility and thermal stability. The IL4/IL13 signal blockade ability remained unchanged even after being heating to 95 degrees. In conclusion, through large-scale cluster computing and deep learning-based de novo design, we developed well-performed IL-4Ra mini-protein antagonist, and demonstrates certain potential for drug development.

Carbapenems are the most potent {beta}-lactams, key antibiotics for healthcare-associated infections by Gram-negative bacteria and evade hydrolysis by most {beta}-lactamases, but are increasingly threatened by emergence of enzymes exhibiting hydrolytic activity towards them. Of the four recognised {beta}-lactamase subclasses, class A (active-site serine enzymes that hydrolyse {beta}-lactams via a covalent acylenzyme intermediate) is the most widely disseminated and, while the majority of such enzymes react with carbapenems to form long-lasting acylenzyme complexes, several possess carbapenem-hydrolyzing activity (carbapenemases). Here, we investigate the basis for these differences in a panel of class A {beta}-lactamases using molecular dynamics (MD) simulations of the respective acylenzyme complexes and tetrahedral intermediates (TI). The simulations reveal multiple features associated with catalytic activity across the spectrum of enzymes tested, including more extensive interactions of the carbapenem acylenzyme carbonyl and generally increased lifetimes of active site water molecules positioned for deacylation. Analysis of the dynamic trajectories shows carbapenemases to have reduced root mean-squared fluctuation (RMSF) differences between the acylenzyme and TI, that are not limited to the active site, indicating that the acylenzyme complex is pre-organised for reaction in carbapenemases but not in carbapenem-inhibited enzymes. Similarly, Principal Component Analysis (PCA) of acylenzyme and TI dynamics shows greater overlap between the two states in carbapenemases, providing further evidence for acylenzyme pre-organisation. Such simulations may represent an effective computational assay able to identify enzymes with carbapenemase activity at relatively modest computational cost.

Antibodies generally exhibit high specificity for their cognate epitopes, but structural and physicochemical similarities between distinct epitopes can enable an antibody to recognize different antigens, resulting in cross-reactivity. This property can be exploited for antibody repurposing. To identify epitopes that share such similarities, both sequence- and structure-based approaches can be employed. In this context, 3D Zernike descriptors provide a compact representation of protein surface geometry as numerical feature vectors, enabling quantitative comparisons independently of structural alignment and orientation. Thus, this study aimed to evaluate the application of 3D Zernike descriptors for the structural clustering of antibodies and epitopes and to explore their use in antibody repurposing for the recognition of new targets. To this end, antibody binding sites previously associated with recognition of similar epitopes were analyzed at different structural levels, considering the CDRs, CDRH3, and complete paratopes. Surface similarity was subsequently quantified by calculating the Euclidean distance between their corresponding 3D Zernike feature vectors. Performance was benchmarked against SPACE2. Additionally, different distance thresholds were evaluated based on their ability to recover antibody pairs recognizing the same epitope. The paratope-based approach provided the best balance between the number of identified pairs and precision at a distance threshold of 2.7, whereas epitope clustering showed robust performance up to a distance of 3.0. At these thresholds, the 3D Zernike descriptors identified a greater number of functional pairs than SPACE2 while maintaining comparable precision and identifying complementary sets of antibody pairs.. BTaken together, these findings support the use of 3D Zernike descriptors for structural clustering of antibodies and epitopes and for guiding antibody repurposing G, a highly lethal zoonotic pathogen. Structural screening identified three antibodies with epitopes similar to the NiV target that also showed a consistent binding preference for the target epitope in molecular docking assays. Notably, one candidate, originally directed against a SARS-CoV-2 epitope, formed a stable complex with the NiV epitope, remaining within the 5 [A] RMSD threshold during heated molecular dynamics simulations and emerging as a potential cross-reactive candidate.These results support the use of this computational framework for biopharmaceutical discovery against emerging targets. Taken together, these findings support the use of 3D Zernike descriptors for structural clustering of antibodies and epitopes and for guiding antibody repurposing.

The leukocyte-specific {beta}2-integrin receptor family exerts a wide range of functions: {beta}2-integrins are involved in leukocyte trafficking, where they mediate cell adhesion during inflammatory responses via binding to ICAM-1, ICAM-2, or JAM-C. Furthermore, they are essential for the recognition and phagocytosis of pathogens opsonized by complement. Accordingly, the {beta}2-integrin family is known to be involved in autoimmune and inflammatory diseases, such as systemic lupus erythematosus. Owing to their complex biology, involving multiple conformational transitions, different signaling pathways, and a broad spectrum of ligands, the development of {beta}2-integrin-targeted probes and therapeutics has remained challenging. We aimed to develop macrocyclic peptides, derived from phage display screening, which can be used to unravel ligand binding profiles of {beta}2-integrins with an emphasis on the I domain. The selection of suitable lead peptides, and the characterization of their interaction profiles with different I domains, was enabled by an established in-vitro assay platform. Various peptide sequences were enriched during several rounds of phage display against the I-domain of CR3, of which two peptides with particularly low micromolar binding affinity were further characterized. Both peptides showed direct binding to {beta}2-integrin I-domains and, in a competitive assay, dose-dependent inhibition of the I-domains interactions with their main ligands iC3b and ICAM-1, respectively. These ligand-interfering properties were confirmed in bead- and cell-based adhesion assays. The modulators developed here are expected to provide valuable insight into the (patho-)physiology of CR3 and the other members of the {beta}2-integrin family, as the two peptides were able to compete with different ligands. In the future, this may help to identify potential therapeutic approaches for autoimmune, inflammatory, and age-related diseases.

Vertical transmission of SARS-CoV-2 is controversial. Owing to the low expression of ACE2 along with TMPRSS2 in placenta, role of secondary receptors becomes significant. In our study we predicted twelve interactors of spike protein expressed in placenta through interactome analysis followed by docking and molecular dynamic simulation. Three interactors of SARS-CoV-2 spike protein were found to be CD147, EGFR and LDLR. Expression at transcriptomic and translational level by real-time PCR and immunohistochemistry respectively was observed in placenta samples obtained from women with COVID exposure risk and compared to control. Elevated protein levels of CD147 (OR=14.667), ACE2 (OR=8.25) and LDLR (OR=1.9) was associated with higher exposure risk. However, the variation in mRNA expression was not statistically significant. Computational study showed that CD147/basigin, EGFR and LDLR stably interact with spike protein outside its primary receptor binding domain. In-vitro binding assay confirmed the physical interaction between spike protein and the placental receptors. In-silico site-directed mutagenesis further identified key potential binding hotspots of spike protein- Tyr28 and Trp64 for CD147, Phe643, Val642, Thr632 for LDLR and Leu8, Phe59, Phe32, Tyr28, Trp64, Trwp152, His245, and Val213 for EGFR. Finally, concluded that CD147, EGFR and LDLR might act as secondary non-canonical cofactors for SARS-CoV-2 spike protein in placenta, thereby increasing its susceptibility and tissue tropism. The study overall gives a better insight into potential placental suscpetibility providing targeted therapeutic opportunities.

Background: Comparisons between independently predicted wild-type and missense-variant protein structures can generate mechanistic hypotheses, but small apparent differences may reflect model-selection variability rather than mutation-specific effects. Methods: Human mitochondrial DNA polymerase gamma (POLG; UniProt P54098) variants p.Arg627Gln (R627Q) and p.Trp748Ser (W748S) were evaluated using five AlphaFold2-PTM network-model outputs per condition generated with one random seed under matched ColabFold settings. Ten pairwise wild type comparisons at each site described between-network model-selection variability. Variant effects were summarized across five within-network wild-type-versus-variant comparisons using rotation-invariant local C-alpha pair distances and local displacement after global and local alignment. Because these comparison designs differ, the wild-type distribution was used as context rather than a mutation-effect null. Wild-type cryo-EM structure 9GGF was used for contact and interface mapping. Experimental A467T and G848S structures 9GGE and 9GGC provided contextual benchmarks. Results: R627Q measurements fell within the range of between-network wild-type differences: its median mean local pair-distance change was 0.170 angstrom, compared with a wild-type median of 0.170 angstrom, and its locally aligned displacement was 0.265 versus 0.248 angstrom. W748S showed higher median values (0.168 versus 0.132 angstrom for pair-distance change; 0.236 versus 0.182 angstrom for locally aligned displacement), but the ranges overlapped and the comparison-design asymmetry precluded a calibrated mutation-effect percentile. Experimental A467T and G848S comparisons produced local changes of similar magnitude. In 9GGF, R627 and W748 directly shared a local microenvironment, with a minimum heavy-atom distance of 3.53 angstrom. R627 also formed short polar-contact candidates with D629 and D743, whereas W748 occupied a hydrophobic packing environment containing Y622 and F750. Both sites were more than 18 angstrom from nucleic acid, more than 30 angstrom from POLG2, and more than 33 angstrom from PZL-A in a ligand-bound structure. Conclusions: Available AlphaFold2 comparisons do not establish a mutation-specific structural deformation for either variant. Experimental-structure mapping supports testable physicochemical hypotheses involving a shared R627-W748 microenvironment - loss of an arginine-centered polar network for R627Q and disruption of a buried aromatic environment for W748S - but not direct DNA, POLG2, or PZL-A contact mechanisms. Matched control substitutions and independent seeds are required to calibrate small mutation-associated structural deltas.

Carbohydrates are essential molecules involved in a wide range of biological processes. While their structural representation in the Protein Data Bank (PDB) has been hindered due to their highly diverse and flexible nature, advancements on X-ray crystallography and CryoEM are accelerating the obtaining of their experimental structures, which in turn supports improved analyses of their structural properties, such as the role of their non-chair conformations on biological processes. In this context, the current work provides a comprehensive and up to date overview of carbohydrate structures within the PDB through classification, quantification, and characterization of monosaccharides and glycan chains, incorporating Cremer-Pople puckering coordinates to evaluate pyranose conformations. Our findings show that, even with a steep increase in CryoEM structures including more complex oligosaccharides, carbohydrate data remains concentrate dinsmallglycanchains, with a about 4% of non-chair conformation sintopresolution structures. Free energy landscapes for the pyranose ring in the presence and absence of nine different binding proteins, including both enzymes and non-enzymes, reinforce the preferred stability of chairs and the rarity of conformational induction upon binding.