All-atom empirical potential for molecular modeling and dynamics studies of proteins

In Silico Discovery of Potential Inhibitors Targeting the MEIG1-PACRG Complex for Male Contraceptive Development

The interaction between meiosis-expressed gene 1 (MEIG1) and Parkin co-regulated gene (PACRG) is a critical determinant of spermiogenesis, the process by which round spermatids mature into functional spermatozoa. Disruption of the MEIG1-PACRG complex can impair sperm development, highlighting its potential as a therapeutic target for addressing male infertility or for the development of non-hormonal contraceptive methods. This study used virtual screening, molecular docking, and molecular dynamics (MD) simulations to identify small molecule inhibitors targeting the MEIG1-PACRG interface. MD simulations provided representative protein conformations, which were used to virtually screen a library of 821 438 compounds, resulting in 48 high-ranking candidates for each protein. PACRG emerged as a favorable target due to its flexible binding pockets and better docking scores compared to MEIG1. Key binding residues with compounds included W50, Y68, N70, and E74 on MEIG1, and K93, W96, E101, and H137 on PACRG. MD simulations revealed that compound stability in MEIG1 complexes is primarily maintained by hydrogen bonding with E74 and π-π stacking interactions with W50 and Y68. In PACRG complexes, compound stabilization is facilitated by hydrogen bonding with E101 and π-π interactions involving W96 and H137. These findings highlight distinct molecular determinants of ligand binding for each protein. Our work provides mechanistic insights and identifies promising compounds for further experimental validation, establishing a foundation for developing MEIG1-PACRG interaction inhibitors as male contraceptives.

Neural network conditioned to produce thermophilic protein sequences can increase thermal stability

This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 million protein homologous pairs from organisms adapted to different temperatures, demonstrates promising capability in targeting thermal stability. A designed variant of the Drosophila melanogaster Engrailed Homeodomain shows a melting temperature increase of 15.5 K. Furthermore, NOMELT achieves zero-shot predictive capabilities in ranking experimental melting and half-activation temperatures across a number of protein families. It achieves this without requiring extensive homology data or massive training datasets as do existing zero-shot predictors by specifically learning thermophilicity, as opposed to all natural variation. These findings underscore the potential of leveraging organismal growth temperatures in context-dependent design of proteins for enhanced thermal stability.

Can We Ever Develop an Ideal RNA Force Field? Lessons Learned from Simulations of the UUCG RNA Tetraloop and Other Systems

Molecular dynamics (MD) simulations are an important and well-established tool for investigating RNA structural dynamics, but their accuracy relies heavily on the quality of the employed force field (ff). In this work, we present a comprehensive evaluation of widely used pair-additive and polarizable RNA ffs using the challenging UUCG tetraloop (TL) benchmark system. Extensive standard MD simulations, initiated from the NMR structure of the 14-mer UUCG TL, revealed that most ffs did not maintain the native state, instead favoring alternative loop conformations. Notably, three very recent variants of pair-additive ffs, OL3CP-gHBfix21, DES-Amber, and OL3R2.7, successfully preserved the native structure over a 10 × 20 μs time scale. To further assess these ffs, we performed enhanced sampling folding simulations of the shorter 8-mer UUCG TL, starting from the single-stranded conformation. Estimated folding free energies (ΔG°fold) varied significantly among these three ffs, with values of 0.0 ± 0.6, 2.4 ± 0.8, and 7.4 ± 0.2 kcal/mol for OL3CP-gHBfix21, DES-Amber, and OL3R2.7, respectively. The ΔG°fold value predicted by the OL3CP-gHBfix21 ff was closest to experimental estimates, ranging from -1.6 to -0.7 kcal/mol. In contrast, the higher ΔG°fold values obtained using DES-Amber and OL3R2.7 were unexpected, suggesting that key interactions are inaccurately described in the folded, unfolded, or misfolded ensembles. These discrepancies led us to further test DES-Amber and OL3R2.7 ffs on additional RNA and DNA systems, where further performance issues were observed. Our results emphasize the complexity of accurately modeling RNA dynamics and suggest that creating an RNA ff capable of reliably performing across a wide range of RNA systems remains extremely challenging. In conclusion, our study provides valuable insights into the capabilities of current RNA ffs and highlights key areas for future ff development.

Reaction Mechanism Path Sampling Based on Parallel Cascade Selection QM/MM Molecular Dynamics Simulation: PaCS-Q

Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations are essential for elucidating complex biochemical reaction mechanisms. However, conventional enhanced sampling methods, such as umbrella sampling and metadynamics, often face limitations in computational cost, sampling completeness, and reliance on predefined reaction coordinates. To address these challenges, we developed Parallel Cascade Selection QM/MM MD (PaCS-Q) simulation, a novel strategy that efficiently explores reaction pathways by iteratively identifying high-potential structures for configurational transitions without predefined biases or external constraints. PaCS-Q directly tracks changes in bond distances over time, enabling the identification of transition states and intermediates. Validation of the Claisen rearrangement in chorismate mutase and the peptidyl aldehyde reaction in the Zika virus NS2B/NS3 serine protease demonstrated accurate pathway capture, reduced computational costs, and efficient sampling. With its user-friendly workflow, PaCS-Q broadens accessibility for computational and experimental researchers, offering a robust tool for studying enzymatic mechanisms with high accuracy and efficiency.

Applying Absolute Free Energy Perturbation Molecular Dynamics to Diffusively Binding Ligands

We have developed and tested an absolute free energy perturbation (FEP) protocol, which combines all-atom molecular dynamics, replica exchange with solute tempering (REST) enhanced sampling, and a spherical harmonic restraint applied to a ligand. Our objective was to compute the binding free energy together with the underlying binding mechanism for a ligand, which binds diffusively to a protein. Such ligands represent nearly impossible targets for traditional FEP simulations. To test our FEP/REST protocol, we selected a conserved motif peptide KKPK termed minNLS from the nuclear localization signal sequence of the Venezuelan equine encephalitis virus capsid protein. This peptide fragment binds diffusively to importin-α transport protein without forming well-defined poses. Our FEP/REST simulations with a spherical restraint provided a converged estimate of minNLS binding free energy. We found that minNLS binds with moderate affinity to importin-α utilizing an unusual, purely entropic mechanism in which binding free energy is determined by favorable entropic gain. For this cationic minNLS peptide, a favorable binding entropic gain is primarily associated with the release of water from the solvation shells of charged amino acids. We demonstrated that FEP/REST simulations sample the KKPK bound ensemble well, allowing us to characterize the distribution of bound structures, binding interactions, and locations on the importin-α surface. Analysis of experimental studies offered support to our rationale behind the KKPK entropic binding mechanism.

Genome-wide accumulations of non-random adaptive point mutations drive westward evolution of Helicobacter pylori

BACKGROUND

For last seven decades we remained convinced that the natural point mutations occur randomly in the genome of an organism. However, our whole genome sequence analyses show that for the gastric pathogen Helicobacter pylori, which causes peptic ulcer and gastric cancer, accumulations of point mutations in the genome are non-random and they contribute to its unidirectional evolution. Based on the oncoprotein CagA, the pathogen can be classified into Eastern (East Asian countries like China and Japan; high incidence of gastric cancer) and Western (Europe, Africa, South-West Asian countries like India; low incidence of gastric cancer) types.

RESULTS

We have found a unique high-altitude Himalayan region, Sikkim (an Indian state bordering China, Nepal and Bhutan), where the evolving Eastern and Western H. pylori types co-exist and show the signs of genetic admixtures. Here, we present genomic evidence for more virulent Eastern-H. pylori getting converted to less virulent Western-H. pylori by accumulating non-random adaptive point mutations.

CONCLUSION

The lesser virulence of the westernized H. pylori is beneficial since this pathogen typically remains colonized in the stomach for decades before causing terminal diseases like gastric cancer. Moreover, the mutation-driven westward evolution of H. pylori is a global phenomenon, which occurred in the geographical regions where people from Eastern and Western ethnicities met and cohabited. The identified evolution of virulent Eastern H. pylori strains to lesser virulent Western variants by accumulation of point mutations also provides insight into the pathogenic potentials of different H. pylori strains.

Improving pKa Predictions with Reparameterized Force Fields and Free Energy Calculations

Given the growing interest in designing targeted covalent inhibitors, methods for rapidly and accurately probing pKas─and, by extension, the reactivities─of target cysteines are highly desirable. Complementary to cysteine, histidine is similarly relevant due to its frequent presence in protein active sites and its unique ability to exist in two tautomeric states. Here, we demonstrate that nonequilibrium free energy calculations can accurately determine the pKa values of both residues, often outperforming conventional predictors. Importantly, we find that (1) increasing the van der Waals radius of cysteine's sulfur atom, (2) modifying the backbone charges of histidine, and (3) introducing effective polarization by downscaling the side chain partial charges of both residues can all significantly improve pKa prediction accuracy. Using the modified CHARMM36m force field on the full dataset reduces the prediction error from 2.12 ± 0.27 pK to 1.28 ± 0.15 pK and increases the correlation with experiment from 0.25 ± 0.09 to 0.58 ± 0.08. Similarly, using the modified Amber14SB force field decreases the error from 3.21 ± 0.29 pK to 1.69 ± 0.23 pK and improves the correlation from 0.15 ± 0.10 to 0.36 ± 0.10.

Small-Molecule FICD Inhibitors Suppress Endogenous and Pathologic FICD-Mediated Protein AMPylation

The AMP transferase, FICD, is an emerging drug target fine-tuning stress signaling in the endoplasmic reticulum (ER). FICD is a bifunctional enzyme, catalyzing both AMP addition (AMPylation) and removal (deAMPylation) from the ER-resident chaperone BiP/GRP78. Despite increasing evidence linking excessive BiP/GRP78 AMPylation to human diseases, small molecules that inhibit pathogenic FICD variants are lacking. Using an in vitro high-throughput screen, we identify two small-molecule FICD inhibitors, C22 and C73. Both molecules significantly inhibit FICD-mediated BiP/GRP78 AMPylation in intact cells while only weakly inhibiting BiP/GRP78 deAMPylation. C22 and C73 also inhibit pathogenic FICD variants and improve proinsulin processing in β cells. Our study identifies and validates FICD inhibitors, highlighting a novel therapeutic avenue against pathologic protein AMPylation.

Molecular mechanism of the effect of ZnCl2 and MgCl2 solution on the conformation of the tau267-312 monomer

Alzheimer's disease is generally believed to be caused by abnormal aggregation of tau protein; however, there remains a lack of understanding about the aggregation process of tau protein in a solution environment. To explore the conformational properties of the tau protein monomer (tau267-312) in the presence of zinc and magnesium ions, we performed all-atom molecular dynamics simulations of tau267-312 in solutions of zinc chloride and magnesium chloride at different concentrations and compared these results with those obtained in pure water. The calculation results show that the β-sheet content increases significantly in the presence of zinc and magnesium ions, which causes a more compact structure for the tau protein monomers. Furthermore, it was found that stronger interactions between residues, as well as alterations in hydrophilic and hydrophobic interactions, are molecular mechanisms driving structural changes within the tau protein monomers. These findings suggest that zinc and magnesium ions facilitate a more stable conformation and promote the aggregation of tau protein monomers, which is important for understanding the aggregation and folding process of tau protein in the environment of saline solution.

Unveiling the Architecture of Human Fibrinogen: A Full-Length Structural Model

Fibrinogen is a protein involved in the haemostasis process playing a central role by forming the fibrin clot. An understanding of protein structure is vital to determining biological function. Despite many studies on the fibrin polymerization process, its molecular mechanism remains elusive mainly due to the absence of a full-length three-dimensional model of human fibrinogen. Amino- and carboxyl-terminal regions of the three pairs of chains that form this molecule are missing in the crystallographic structure, being the carboxyl-terminal of the Aα chain the most affected with a section of more than 400 amino acids missing. To have a full structure of the fibrinogen molecule would allow the creation of a model of protofibril, shedding light into the fibrin formation process through computational techniques such as molecular dynamics simulations. Absent regions were explored using homology modelling and coarse-grained molecular dynamics simulations. Later on, the model was refined and stabilized with atomistic molecular dynamic simulations. In the present study, we obtained the first realistic full-length structure of fibrinogen, with features in accordance with previous results obtained by experimental techniques.

Energetics of Expanded PAM Readability by Engineered Cas9-NG

The energetic basis for the enhanced PAM (protospacer adjacent motif) readability in engineered Cas9-NG (a variant of Cas9 from Streptococcus pyogenes (SpCas9)) with seven mutations: (R1335V, E1219F, D1135V, L1111R, T1337R, G1218R, and A1322R) remains a fundamental unsolved problem. Utilizing the X-ray structure of the precatalytic complex (SpCas9:sgRNA:dsDNA) as a template, we calculated the changes in PAM (TGG, TGA, TGT, or TGC) binding affinity (ΔΔG) associated with each of the seven mutations in SpCas9 through rigorous alchemical simulations (sampling ∼ 53 μs). The underlying thermodynamics (ΔΔG) accounts for the experimentally observed differences in DNA cleavage activity between SpCas9 and Cas9-NG across various DNA substrates. The interaction energies between SpCas9 and DNA are significantly influenced by the type and location of the amino acid mutations. Notably, the R1335V mutation disfavors DNA binding by disrupting critical interactions with the PAM. However, the destabilizing effect of the R1335V mutation is mitigated by four advantageous mutations (E1219F, D1135V, L1111R, and T1337R), which primarily introduce nonbase-specific interactions and enhance PAM readability. The hydrophobic substitutions (E1219F and D1135V) are particularly impactful, as they exclude solvent from the PAM binding pocket, strengthening electrostatic interactions in the low dielectric medium and increasing the stability of the noncognate PAM complexes by ∼2-5 kcal/mol. Additionally, L1111R and T1337R facilitate DNA binding by forming direct electrostatic contacts. In contrast, the charge mutations G1218R and A1322R do not effectively promote interactions with the negatively charged DNA, clearly demonstrating that the location of mutations is crucial in shaping these interaction energetics. We demonstrated that stabilization of the Cas9-NG: noncognate PAM complexes enables broader PAM recognition. This is primarily achieved through two mechanisms: (1) the establishment of new nonbase-specific interactions between the protein and nucleotides and (2) the enhancement of electrostatic interactions within a relatively dry and hydrophobic pocket. The findings revealed that mutation-induced desolvation can improve the recognition of noncognate PAMs, paving the way for the rational and innovative design of SpCas9 mutants.

Optimizing On-the-Fly Probability Enhanced Sampling for Complex RNA Systems: Sampling Free Energy Surfaces of an H-Type Pseudoknot

All-atom molecular dynamics (MD) simulations offer crucial insights into biomolecular dynamics, but inherent time scale constraints often limit their effectiveness. Advanced sampling techniques help overcome these limitations, enabling predictions of deeply rugged folding free energy surfaces (FES) of RNA at atomistic resolution. The Multithermal-Multiumbrella On-the-Fly Probability Enhanced Sampling (MM-OPES) method, which combines temperature and collective variables (CVs) to accelerate sampling, has shown promise and cost-effectiveness. However, the applications have so far been limited to simpler RNA systems, such as stem-loops. In this study, we optimized the MM-OPES method to explore the FES of an H-type RNA pseudoknot, a more complex fundamental RNA folding unit. Through systematic exploration of CV combinations and temperature ranges, we identified an optimal strategy for both sampling and analysis. Our findings demonstrate that treating the native-like contacts in two stems as independent CVs and using a temperature range of 300-480 K provides the most effective sampling, while projections onto native Watson-Crick-type hydrogen bond CVs yield the best resolution FES prediction. Additionally, our sampling scheme also revealed various folding/unfolding pathways. This study provides practical insights and detailed decision-making strategies for adopting the MM-OPES method, facilitating its application to complex RNA structures at atomistic resolution.

On the role of α-alumina in the origin of life: Surface-driven assembly of amino acids

We investigate the hypothesis that mineral/water interfaces played a crucial catalytic role in peptide formation by promoting the self-assembly of amino acids. Using classical molecular dynamics simulations, we demonstrate that the α-alumina(0001) surface exhibits an affinity of 4 kBT for individual glycine or GG dipeptide molecules due to hydrogen bonds. In simulations with multiple glycine molecules, surface-bound glycine enhances further adsorption, leading to the formation of long chains connected by hydrogen bonds between the carboxyl and amine groups of glycine molecules. We find that the likelihood of observing chains longer than 10 glycine units increases by at least five orders of magnitude at the surface compared to the bulk. This surface-driven assembly is primarily due to local high density and alignment with the alumina surface pattern. Together, these results propose a model for how mineral surfaces can induce configuration-specific assembly of amino acids, thereby promoting condensation reactions.

Peptide-Based Regulation of TNF-α-Mediated Cytotoxicity

Tumor necrosis factor alpha (TNF-α) is a pro-inflammatory cytokine associated with TNF receptor 1 (TNFR1) and TNF receptor 2 (TNFR2), which play important roles in several inflammatory diseases. There is a growing interest in developing alternative molecules that can be used as TNF blockers. In this study, we focused on TNF-α-, TNFR1-, and TNFR2-mimicking peptides to inhibit TNF-α receptor binding in various ways. Six peptides (OB1, OB2, OB5, OB6, OB7, and OB8) were developed to bind TNFR1, TNFR2, and TNF-α. OB1 and OB2 bound to TNF-α with lower Kd values of 300 and 46.7 nM, respectively, compared to previously published sequences. These synthetic peptides directly and indirectly inhibited TNF-α in vitro without cytotoxicity to L929 cells, and OB1 significantly inhibited apoptosis in the presence of hTNF-α. Peptides developed in this study may prove to be useful for therapeutic inhibition of TNF-α.

Rational Design Principles for De Novo α-Helical Peptide Barrels with Dynamic Conductive Channels

Despite advances in peptide and protein design, the rational design of membrane-spanning peptides that form conducting channels remains challenging due to our imperfect understanding of the sequence-to-structure relationships that drive membrane insertion, assembly, and conductance. Here, we describe the design and computational and experimental characterization of a series of coiled coil-based peptides that form transmembrane α-helical barrels with conductive channels. Through a combination of rational and computational design, we obtain barrels with 5 to 7 helices, as characterized in detergent micelles. In lipid bilayers, these peptide assemblies exhibit two conductance states with relative populations dependent on the applied potential: (i) low-conductance states that correlate with variations in the designed amino-acid sequences and modeled coiled-coil barrel geometries, indicating stable transmembrane α-helical barrels; and (ii) high-conductance states in which single channels change size in discrete steps. Notably, the high-conductance states are similar for all peptides in contrast to the low-conductance states. This indicates the formation of large, dynamic channels, as observed in natural barrel-stave peptide channels. These findings establish rational routes to design and tune functional membrane-spanning peptide channels with specific conductance and geometry.

The interface hydrophilic-hydrophobic integration of fluorinated defective graphene towards biomedical applications

In biomedical fields, rational design of novel two-dimensional (2D) biomedical nanomaterials aims to precisely manipulate biomolecules, including efficient capture, structural-functional transformation, directional movement, and self-assembly. In this work, we innovatively proposed new graphene nanosheets and selected two representative proteins to explore their binding mechanisms, structural-functional transformation of proteins, and biological effects of the materials. Fluorinated defective graphene (FDG) exhibited highly efficient capture and structural-functional transformation for the receptor binding domain (RBD), and we observed its collapse phenomenon in 2D materials for the first time. For the main protease (Mpro), FDG achieved an optimal balance between efficient capture, immobilization, and structural disruption. Further studies showed that fluorination on oxygen-containing defect graphene significantly enhanced variances in water distribution, surface properties, and hydrogen bond networks on the material surface. This allowed amino acids to be confined to specific areas, achieving efficient capture and directional movement. Additionally, the adsorption behavior and interaction strength of peptides and deoxynucleotides on FDG further validated the possibility of self-assembly. In summary, we highlight FDG as an excellent biomedical material with hydrophilic-hydrophobic integration.

Interrogating the Surface Interactions of Resilin-Like Peptides on h-BN and Graphene

Resilin protein-based elastomers could provide pathways to synthetic materials with increased mechanical resilience; however, it remains challenging to replicate their properties when they are made in the lab. This is because Tyr-based cross-linking is necessary, which may require preorganized configurations of resilin in its natural environment. In previous work, the P1 graphene-binding peptide was conjugated with resilin-like peptides (RLPs) to produce P1/RLP conjugates. The binding of these peptides to the graphene surface was studied using QCM analysis and atomic force microscopy as an initial step toward preorganization for eventual cross-linking. Herein, the adsorption studies of RLPs (R1 and R2) and their conjugates with the P1 graphene-binding peptide are studied on hexagonal boron nitride (h-BN) using QCM analysis and molecular modeling. The results are compared with those of previous work based on the graphene surface. The binding affinity of P1/RLPs to h-BN is found to be similar to that of graphene, with notable changes that can be attributed to the variations in the surface composition. In addition, molecular simulations of the surface-adsorbed P1/RLP structures on h-BN indicate substantial differences compared to those on the graphene surface, with the RLP domain dominating the binding on h-BN. Moreover, the parent RLP peptides demonstrated increased binding to h-BN, which was not observed with graphene, thus indicating that h-BN is likely to be a poorer surface for peptide preorganization for eventual cross-linking for the controlled preparation of resilient elastomers.

Unfolding of the Villin Headpiece Domain: Revealing Structural Heterogeneity with Time-Resolved X-Ray Solution Scattering and Markov State Modeling

Understanding protein folding pathways is crucial to deciphering the principles of protein structure and function. Here, the unfolding dynamics of the 35-residue villin headpiece (HP35) and a norleucine-substituted variant (2F4K) using a combination of experimental and computational techniques is investigated. Time-resolved X-ray solution scattering coupled with equilibrium molecular dynamics simulations and Markov state modeling reveals distinct unfolding mechanisms between the two variants: HP35 and 2F4K. Specifically, HP35 exhibits a two-state unfolding process, whereas an intermediate state is identified for the 2F4K mutant. A Markov state model constructed from simulations is used to map atomic-level transitions to experimental observations, providing insights into the role of sequence variations in modulating folding pathways. The findings underscore the importance of integrating experimental and computational approaches to unravel protein unfolding mechanisms between heterogenous structural ensembles.

Enzymatic Birch reduction via hydrogen atom transfer at [4Fe-4S]-OH2 and [8Fe-9S] clusters

The alkali metal- and ammonia-dependent Birch reduction is the classical synthetic method for achieving dihydro additions to arenes, typically yielding 1,4-cyclodienes. A mild biological alternative to this process are 1,5-dienoyl-coenzyme A (CoA)-forming class I and II benzoyl-CoA reductases (BCRs), widely abundant key enzymes in the biodegradation of aromatic compounds at anoxic environments. To obtain a comprehensive mechanistic understanding of class I BCR catalysis, we produced the active site subunits from a denitrifying bacterium and determined the X-ray structure of its substrate and product complexes at 1.4 Å revealing non-canonical double-cubane [8Fe-9S] and active site aqua-[4Fe-4S] clusters. Together with kinetic, spectroscopic and QM/MM studies, we provide evidence for a radical mechanism with a [4Fe-4S] cluster-bound water molecule acting as hydrogen atom and electron donor at potentials beyond the biological redox window. An analogous Birch-like radical mechanism is applied by class II BCRs with the catalytic water bound to a tungsten-bis-metallopterin cofactor. The use of activated, metal-bound water ligands as hydrogen atom donor serves as a basic blueprint for future enzymatic or biomimetic Birch reduction processes.

Molecular Dynamics Investigation into the Stability of KRas and CRaf Multimeric Complexes

In the Ras/Raf/MAPK signaling pathway, Ras and Raf proteins interact synergistically to form a tetrameric complex. NMR experiments have demonstrated that Ras dimerizes in solution and binds stably to Raf, forming Ras·Raf complexes. In this study, we constructed the ternary and quaternary complexes of KRas and CRaf based on crystal structures, denoted as (KRas)2·CRaf and (KRas)2·(CRaf)2, respectively. Molecular dynamics (MD) simulations were performed to investigate the stability of these complexes, while hydrogen bonds as well as salt bridges formed at the protein-protein interaction interfaces were analyzed based on simulation trajectories. The results revealed that the KRas·CRaf complex is more stable in explicit solvent compared with the KRas dimer. Formation of the stable quaternary complex (KRas)2·(CRaf)2 might be attributed to the association of two binary KRas·CRaf complexes. Additionally, MD simulations of the KRasG12D·CRaf complex revealed a stable and extended binding site at the KRas-CRaf interaction interface. This binding site was identified as a potential therapeutic target to block abnormal signal transmission in the pathway.

Quantum mechanics/molecular mechanics studies on mechanistic photophysics of epigenetic C5-halogenated DNA nucleosides: 2'-deoxy-5-chlorocytidine and 2'-deoxy-5-bromocytidine in aqueous solution

In this work, we have employed the high-level QM(CASPT2//CASSCF)/MM method to study the photophysical mechanisms of two important metabolized DNA/RNA nucleoside byproducts, i.e., 2'-deoxy-5-chlorocytidine (5CldCyd) and 2'-deoxy-5-bromocytidine (5BrdCyd), in aqueous solution. On the basis of our optimized minimum-energy structures, conical intersections, and crossing points, as well as the computed associated excited-state relaxation pathways involving the different internal conversion (IC) and intersystem crossing (ISC) processes in and between the S1, T1, T2, and S0 states, we have suggested the feasible excited-state relaxation mechanisms of these two important epigenetic halogenated DNA nucleosides. The initially populated spectroscopic bright 1ππ* state in the Franck-Condon (FC) region is the S1 state both for 5CldCyd and 5BrdCyd under 295 nm irradiation. The excited S1 state first evolves into its minimum S1-MIN and rapidly undergoes efficient IC to the S0 state via the nearby low-lying S1/S0 conical intersection. The corresponding energy barrier of the S1 → S0 IC path in 5CldCyd is estimated to be 4.6 kcal mol-1 at the QM(CASPT2)/MM level, while it is found to be an almost barrierless process in 5BrdCyd. In addition to this very efficient IC, the S1 state can partially slowly undergo ISC to transfer to the T1 state. Because the small spin-orbit couplings (SOCs) of S1/T1 and S1/T2 are estimated to be less than 5.0 cm-1 at the QM(CASPT2)/MM level, the ISC involved T1 formation is not so efficient. The resulting T1 state from the minor S1 → T1 and S1 → T2 → T1 ISCs will first relax to its minimum T1-MIN and continue to approach the nearby accessible T1/S0 crossing point, followed by further T1 → S0 ISC to the S0 state. Relatively, the T1 → S0 ISC of 5BrdCyd is significantly enhanced by a large T1/S0 SOC of 32.9 cm-1 at the T1/S0 crossing point. The present work rationalizes the excited-state dynamics of 5CldCyd and 5BrdCyd in aqueous solution and could provide mechanistic insights into understanding the photophysics of similar halogenated DNA nucleosides and their derivatives.

An intramolecular FRET biosensor for the detection of SARS-CoV-2 in biological fluids

The development of a FRET-based sensor for detecting the Spike surface antigen of SARS-CoV-2 in biological fluids is described here, exploiting the fluorescence properties of Green Fluorescent Protein (GFP). Our design strategy combines experimental and molecular modeling and simulations to build a smart modular architecture, allowing for future optimization and versatile applications. The prototype structure incorporates two reporter elements at the N-terminus and C-terminus, with two interaction elements mediating their separation. This design supports two fluorescence measurement methods: direct measurement and the molecular beacon approach. The former detects changes in GFP fluorescence intensity due to interactions with the Spike protein, while the latter involves an organic quencher that restores GFP fluorescence upon Spike protein binding. In silico design of linkers, using molecular dynamics (MD) simulations, ensured optimal flexibility and stability. The AAASSGGGASGAGG linker was selected for its balance between flexibility and stability, while the LEAPAPA linker was chosen for its minimal structural impact on the interaction elements. Fluorophores' behavior was analyzed, showing stable FRET efficiency, essential for reliable detection. Quenching efficiency calculations, based on Förster energy transfer theory, validated the sensor's sensitivity. Further, MD simulations assessed GFP stability, confirming minimal unfolding tendencies, which explains the sensor functioning mechanism. The sensor was successfully produced in E. coli, and functional validation demonstrated its ability to detect the Spike protein, with fluorescence recovery proportional to protein concentration, while the modular computer aided design allowed for sensitivity optimization. The developed biosensor prototype offers a promising tool for rapid and precise viral detection in clinical settings.

Optimizing Polyethylene Glycol Coating for Stealth Nanodiamonds

Nanodiamonds (NDs) have emerged as potential candidates for versatile platforms in nanomedicine, offering unique properties that enhance their utility in drug delivery, imaging, and therapeutic applications. To improve their biocompatibility and nanomedical applicability, NDs are coated with organic polymer chains, such as poly(ethylene glycol) (PEG), which are well known to prolong their blood-circulating lifetime by reducing the surface adsorption of serum proteins. Theoretical simulations are useful tools to define, at the atomic level, the optimal parameters that guide the presentation of the coating chains in the biological environment and the interaction of coated NDs with proteins. In this work, we perform atomistic molecular dynamics (MD) simulations of several PEGylated spherical ND models immersed in a realistic physiological medium. In particular, we evaluate the effect of the polymer chain's terminal group, length, grafting density, and the ND core dimension on both the structural properties of the PEG coating and the interaction of the nanoconjugates with the aqueous phase. Moreover, we investigate the role played by the chemical nature of the core material through a comparative analysis with a PEGylated spherical titanium dioxide (TiO2) nanoparticle (NP). Among all the parameters evaluated, we find that the PEG grafting density, the PEG chain length, and the NP core material are key factors in determining the dynamic behavior of PEGylated nanosystems in solution, whereas the PEG terminal group and the ND dimension only play a marginal role. These factors can be strategically adjusted to identify the optimal conditions for enhanced clinical performance. Finally, we prove that the PEG coating prevents the aggregation of two ND particles. We believe that this computational study will provide valuable insights to the experimental community, supporting the rational design of polymer-coated inorganic NPs for more efficient nanomedical applications.

Assessing the interaction between the N-terminal region of the membrane protein magnesium transporter A and a lipid bilayer

This study investigates the interaction of KEIF, the intrinsically disordered N-terminal region of the magnesium transporter MgtA, with lipid bilayers mimicking cell membranes. Combining experimental techniques such as neutron reflectometry (NR), quartz-crystal microbalance with dissipation monitoring (QCM-D), synchrotron radiation circular dichroism (SRCD), and oriented circular dichroism (OCD), with molecular dynamics (MD) simulations, we characterized KEIF's adsorption behavior.

HYPOTHESIS

KEIF undergoes conformational changes upon interacting with lipid bilayers, potentially influencing MgtA's function within the plasma membrane.

EXPERIMENTS

The study assessed KEIF's structural transitions and position within lipid bilayers under various conditions, including zwitterionic versus anionic bilayers and different salt concentrations. The techniques analyzed adsorption-induced structural shifts and peptide localization within the bilayer.

FINDINGS

KEIF transitions from a disordered to a more structured state, notably increasing α-helical content upon adsorption to lipid bilayers. The peptide resides primarily in the hydrophobic tail region of the bilayer, where it may displace lipids. Electrostatic interactions, modulated by bilayer charge and ionic strength, play a critical role. These results suggest that KEIF's conformational changes and bilayer interactions can be integral to its potential modulatory role in MgtA function within the plasma membrane. This research highlights the importance of surface-induced structural transitions in intrinsically disordered proteins and their implications for membrane protein modulation.

Roles of basic amino acid residues in substrate binding and transport of the light-driven anion pump Synechocystis halorhodopsin (SyHR)

Microbial rhodopsins are photoreceptive seven-transmembrane α-helical proteins, many of which function as ion transporters, primarily for small monovalent ions such as Na+, K+, Cl-, Br-, and I-. Synechocystis halorhodopsin (SyHR), identified from the cyanobacterium Synechocystis sp. PCC 7509, uniquely transports the polyatomic divalent SO42- inward, in addition to monovalent anions (Cl- and Br-). In this study, we conducted alanine-scanning mutagenesis on twelve basic amino acid residues to investigate the anion transport mechanism of SyHR. We quantitatively evaluated the Cl- and SO42- transport activities of the WT SyHR and its mutants. The results showed a strong correlation between the Cl- and SO42- transport activities among them (R = 0.94), suggesting a shared pathway for both anions. Notably, the R71A mutation selectively abolished SO42- transport activity while maintaining Cl- transport, whereas the H167A mutation significantly impaired both Cl- and SO42- transport. Furthermore, spectroscopic analysis revealed that the R71A mutant lost its ability to bind SO42- due to the absence of a positive charge, while the H167A mutant failed to accumulate the O intermediate during the photoreaction cycle (photocycle) due to reduced hydrophilicity. Additionally, computational analysis revealed the SO42- binding modes and clarified the roles of residues involved in its binding around the retinal chromophore. Based on these findings and previous structural information, we propose that the positive charge and hydrophilicity of Arg71 and His167 are crucial for the formation of the characteristic initial and transient anion-binding site of SyHR, enabling its unique ability to bind and transport both Cl- and SO42-.

Coarse-Grained Simulations of Phosphorylation Regulation of p53 Autoinhibition

Intrinsically disordered proteins (IDPs) are key components of cellular signaling and regulatory networks. They frequently remain dynamic even in complexes and thus rely on potentially subtle shifts in the disordered conformational ensemble for function. Understanding the molecular basis of these fascinating mechanisms of IDP function and regulation requires a detailed characterization of dynamic ensembles in various biologically relevant states. Here, we study the phosphorylation dependence of the dynamic interaction between the N-terminal transactivation domain (NTAD) and DNA-binding domain (DBD) of tumor suppressor p53, which plays a key role in the autoinhibition and regulation of p53 activation or termination during various stages of stress response. By extending the hybrid-resolution (HyRes) coarse-grained (CG) protein force field to model phosphorylated side chains, we show that HyRes simulations accurately recapitulate the effects of phosphorylation on the p53 NTAD/DBD interactions. The simulated ensembles show that phosphorylation of Thr55 as well as Ser46 enhances dynamic NTAD/DBD interactions and further induces conformational shifts that promote trans interactions between two p53 dimers to drive dissociation from DNA. These CG simulations thus provide a strong molecular basis in support of previous experimental studies suggesting the central role of dynamic interactions of disordered domains and phosphorylation in the function of p53. The success of this study also suggests that HyRes provides an efficient and viable tool for studying dynamic interactions and post-translational modifications in IDP function and regulation.

TCR catch bonds nonlinearly control CD8 cooperation to shape T cell specificity

Naturally evolved T-cell receptors (TCRs) exhibit remarkably high specificity in discriminating non-self antigens from self-antigens under dynamic biomechanical modulation. In contrast, engineered high-affinity TCRs often lose this specificity, leading to cross-reactivity with self-antigens and off-target toxicity. The underlying mechanism for this difference remains unclear. Our study reveals that natural TCRs exploit mechanical force to form optimal catch bonds with their cognate antigens. This process relies on a mechanically flexible TCR-pMHC binding interface, which enables force-enhanced CD8 coreceptor binding to MHC-α1α2 domains through sequential conformational changes induced by force in both the MHC and CD8. Conversely, engineered high-affinity TCRs create rigid, tightly bound interfaces with cognate pMHCs of their parental TCRs. This rigidity prevents the force-induced conformational changes necessary for optimal catch-bond formation. Paradoxically, these high-affinity TCRs can form moderate catch bonds with non-stimulatory pMHCs of their parental TCRs, leading to off-target cross-reactivity and reduced specificity. We have also developed comprehensive force-dependent TCR-pMHC kinetics-function maps capable of distinguishing functional and non-functional TCR-pMHC pairs and identifying toxic, cross-reactive TCRs. These findings elucidate the mechano-chemical basis of the specificity of natural TCRs and highlight the critical role of CD8 in targeting cognate antigens. This work provides valuable insights for engineering TCRs with enhanced specificity and potency against non-self antigens, particularly for applications in cancer immunotherapy and infectious disease treatment, while minimizing the risk of self-antigen cross-reactivity.

Synthesis of New Cationic Dicephalic Surfactants and Their Nonequivalent Adsorption at the Air/Solution Interface

The interfacial behavior of aqueous solutions of newly synthesized 2-alkyl-N,N,N,N',N',N'-hexamethylpropan-1,3-ammonium dibromides with decyl, dodecyl, and tetradecyl alkyl chains was investigated both experimentally and theoretically. The results of the surface tension measurements were described using the modified surface quasi-two-dimensional electrolyte (mSTDE) model of ionic surfactant adsorption, which was supported by molecular dynamics simulations. Our contribution encompasses the design, synthesis, and characterization of a novel class of dicephalic-type cationic surfactants, branched on a methine motif, possessing two symmetric trimethylammonium groups, which constitute a double-head extension of the standard alkyltrimethylammonium salts of the single-head, single-tail structure. The convenient synthetic route and final purification steps allowed for the high-yield, high-purity production of the surfactants. Dicephalic-type surfactants demonstrated lower surface activity and higher critical micelle concentration values when compared with their single head-single tail counterparts. That can be attributed primarily to the presence of strong electrostatic repulsive forces within the bulky, double-charge headgroups and significant counterion condensation. Furthermore, molecular dynamics simulations demonstrated a propensity for the desorption of surfactants from the interface, even in diluted solutions, which constrained the attainable surface concentration and resulted in a lower reduction in surface tension. The mSTDE model of adsorption provided an excellent description of the experimental surface isotherms with a concise set of parameters. The model's predictive power was demonstrated by the studies of the effect of inorganic salts on the surface activity of investigated surfactants. Our unique approach enabled us to gain a theoretical explanation of the newly devised surfactants' behavior at the water/air interface.

Using Short Molecular Dynamics Simulations to Determine the Important Features of Interactions in Antibody-Protein Complexes

The last few years have seen the rapid proliferation of machine learning methods to design binding proteins. Although these methods have shown large increases in experimental success rates compared to prior approaches, the majority of their predictions fail when they are experimentally tested. It is evident that computational methods still struggle to distinguish the features of real protein binding interfaces from false predictions. Short molecular dynamics simulations of 20 antibody-protein complexes were conducted to identify features of interactions that should occur in binding interfaces. Intermolecular salt bridges, hydrogen bonds, and hydrophobic interactions were evaluated for their persistences, energies, and stabilities during the simulations. It was found that only the hydrogen bonds where both residues are stabilized in the bound complex are expected to persist and meaningfully contribute to binding between the proteins. In contrast, stabilization was not a requirement for salt bridges and hydrophobic interactions to persist. Still, interactions where both residues are stabilized in the bound complex persist significantly longer and have significantly stronger energies than other interactions. Two hundred and twenty real antibody-protein complexes and 8194 decoy complexes were used to train and test a random forest classifier using the features of expected persistent interactions identified in this study and the macromolecular features of interaction energy (IE), buried surface area (BSA), IE/BSA, and shape complementarity. It was compared to a classifier trained only on the expected persistent interaction features and another trained only on the macromolecular features. Inclusion of the expected persistent interaction features reduced the false positive rate of the classifier by two- to five-fold across a range of true positive classification rates.

SAAP-148 Oligomerizes into a Hexamer Forming a Hydrophobic Inner Core

Human cathelicidin LL-37 derivative, the 24-mer SAAP-148, is highly effective in vitro in eradicating multidrug-resistant bacteria without inducing resistance. SAAP-148 has a high cationic charge (+11) and 46% hydrophobicity, which, once the peptide folds into an alpha helix, forms a wide hydrophobic face. This highly amphipathic nature facilitates on the one hand its insertion into the membrane's fatty acyl chain region and on the other hand it´s interaction with anionic membrane components, which aids in killing bacteria. However, the contributions of the secondary and quaternary structures have not been thoroughly investigated so far. To address this, we applied circular dichroism, NMR spectroscopy, X-ray scattering, AlphaFold 3 protein folding software, and molecular dynamics simulations. Our results reveal that SAAP-148 adopts a stable hexameric bundle composed of three parallel dimers, that together form a hydrophobic core of aromatic side chain residues. The hexameric structure is retained at the membrane interface, whereby, MD simulation studies indicated the formation of a fiber-like structure in the presence of anionic membranes. This certainly seems plausible, as oligomers are stabilized by aromatic residues, and the exposure of positively charged side chains on the surface likely facilitates the transition of the peptide into fibrils on anionic membranes.

Discovery and In Silico Characterization of Anatolian Water Buffalo Rumen-Derived Bacterial Thermostable Xylanases: A Sequence-Based Metagenomic Approach

This study involved shotgun sequencing of rumen metagenomes from three Anatolian water buffalos, an exploration of the relationship between microbial flora and xylanases, and in silico analyses of thermostable xylanases, focusing on their sequence, structure, and dynamic properties. For this purpose, the rumen metagenome of three Anatolian water buffalos was sequenced and bioinformatically analyzed to determine microbial diversity and full-length xylanases. Analyses of BLAST, biophysicochemical characteristics, phylogenetic tree, and multiple sequence alignment were performed with Blastp, ProtParam, MEGA11 software, and Clustal Omega, respectively. Three-dimensional homology models of three xylanases (AWBRMetXyn5, AWBRMetXyn10, and AWBRMetXyn19) were constructed by SWISS-MODEL and validated by ProSA, ProCheck, and Verify3D. Also, their 3D models were structurally analyzed by PyMOL, BANΔIT, thermostability predictor, What If, and Protein Interaction Calculator (PIC) software. Protein-ligand interactions were examined by docking and MD simulation. Shotgun sequence and Blastp analyses showed that Clostridium (Clostridiales bacterial order), Ruminococcus (Oscillospiraceae bacterial family), Prevotella (Bacteroidales bacterial order), and Butyrivibrio (Lachnospiraceae bacterial family) were found as dominant potential xylanase-producer genera in three rumen samples. Furthermore, the biophysicochemical analysis indicated that three xylanases exhibited an aliphatic index above 80, an instability index below 40, and melting temperatures (T m) surpassing 65 °C. Phylogenetic analysis placed three xylanases within the GH10 family, clustering them with thermophilic xylanases, while homology modeling identified the optimal template as a xylanase from a thermophilic bacterium. The structural analysis indicated that three xylanases possessed the number of salt bridges, hydrophobic interactions, and T m score higher than 50, 165, and 70 °C, respectively; however, the reference thermophilic XynAS9 had 43, 145, and 54.41 °C, respectively. BANΔIT analysis revealed that three xylanases exhibited lower B'-factor values in the β3-α1 loop/short-helix at the N-terminal site compared to the reference thermophilic XynAS9. In contrast, six residues (G79, M123, D150, T199, A329, and G377) possessed higher B'-factor values in AWBRMetXyn5 and their aligned positions in AWBRMetXyn10 and AWBRMetXyn19, relative to XynAS9 including Gln, Glu, Ile, Lys, Ser, and Val at these positions, respectively. MD simulation results showed that the β9-η5 loop including catalytic nucleophile glutamic acid in the RMSF plot of three xylanases had a higher fluctuation than the aligned region in XynAS9. The distance analysis from the MD simulation showed that the nucleophile residue in AWBRMetXyn5 and AWBRMetXyn10 remained closer to the ligand throughout the simulation compared with XynAS9 and AWBRMetXyn19. The most notable difference between AWBRMetXyn5 and AWBRMetXyn10 was the increased amino acid fluctuations in two specific regions, the η3 short-helix and the η3-α3 loop, despite a minimal sequence difference of only 1.24%, which included three key amino acid variations (N345, N396, and T397 in AWBRMetXyn5; D345, K396, and A397 in AWBRMetXyn10). Thus, this study provided computational insights into xylanase function and thermostability, which could inform future protein engineering efforts. Additionally, three xylanases, especially AWBRMetXyn5, are promising candidates for various high-temperature industrial applications. In a forthcoming study, three xylanases will be experimentally characterized and considered for potential industrial applications. In addition, the amino acid substitutions (G79Q, M123E, D150I, T199K, A329S, and G377V) and the residues in the β3-α1 loop will be targeted for thermostability improvement of AWBRMetXyn5. The amino acids (N345, N396, and T397) and the residues on the β9-η5 loop, η3 short-helix, and η3-α3 loop will also be focused on development of the catalytic efficiency.

Mechanistic insights into alkaloid-based inhibition of squalene epoxidase: A combined in silico and experimental approach for targeting cholesterol biosynthesis

Squalene epoxidase (SQLE) is a key enzyme in the cholesterol biosynthesis pathway and an attractive therapeutic target for hypercholesterolemia and antifungal treatment. In this study, we investigated the inhibitory potential of six alkaloids-berberine, evodiamine, harmine, reserpine, matrine, and sanguinarine-against SQLE using a combined in silico and in vitro approach. Molecular docking revealed strong binding affinities ranging from -8.1 to -11.0 kcal/mol, with evodiamine demonstrating the highest affinity, followed by sanguinarine and berberine. 200 ns MD simulations confirmed stable interactions for all alkaloid-enzyme complexes, characterized by low RMSD values, robust hydrogen bonding, and favorable free energy landscapes, as supported by MM/PBSA analysis. Experimental validation through in vitro inhibition assays revealed that evodiamine (IC₅₀ = 2.87 ± 0.08 μM) exhibited potent inhibition comparable to the standard inhibitor TNSCPA (IC₅₀ = 2.65 ± 0.18 μM), while berberine (IC₅₀ = 3.57 ± 0.18 μM) and reserpine (IC₅₀ = 4.91 ± 0.34 μM) showed strong and moderate inhibition, respectively. Harmine, matrine, and sanguinarine were less effective. Enzyme kinetics studies demonstrated that berberine and reserpine act as noncompetitive inhibitors, binding to allosteric sites, whereas evodiamine exhibited competitive inhibition at the active site. ADMET analysis highlighted favorable pharmacokinetic properties for berberine, evodiamine, and sanguinarine, while reserpine and matrine exhibited limited bioavailability due to solubility and size constraints. The unique inhibitory mechanisms observed were consistent with the structural and physicochemical properties of the compounds. These findings establish berberine, evodiamine, and reserpine as promising SQLE inhibitors, with evodiamine emerging as a lead candidate.

A multifaceted examination of the action of PDE4 inhibitor rolipram on MMP2/9 reveals therapeutic implications

A PDE4 (phosphodiesterase 4) inhibitor, Rolipram, was previously found to down-regulate (in a manner dependent on cAMP (cyclic adenosine monophosphate)-PKA (protein kinase A)) MMP2 (matrix metalloproteinase 2) and MMP9 protein expression levels, important markers of epithelial-to-mesenchymal transition in human breast cancer cell lines. However, zymographic studies revealed that rolipram could also alter the enzymatic activities of these MMPs, even in the presence of the PKA inhibitor H89. This calls for more detailed investigations of the inhibitory mechanism of rolipram on MMP2 and MMP9. The prediction of ligand-based targets through online reverse screening indicated that proteases are likely targets of rolipram. Computational molecular docking also demonstrated significant binding affinities of rolipram for both MMP2 and MMP9 proteins. Concurrently, a well-known inhibitor of MMPs, SB3CT, was utilized as a positive control for this study. The best models of the docked complexes were used as initial conditions for molecular dynamics (MD) simulations to explore their dynamic behavior and stability. In particular, both the MMP2-rolipram and MMP9-rolipram complexes were found to be stable and compact for the duration of the simulation ([Formula: see text]). Several stable hydrogen bonds were also detected between the proteins and rolipram. In vitro experiments using primary cells from patients with breast cancer also showed that rolipram could alter the enzymatic activities of MMP2 and MMP9, independent of the cAMP-PKA signaling pathway, though it was thought to be cAMP-PKA dependent previously. These observations indicate the ability of rolipram to control breast cancer by regressing the functions of MMP2 and MMP9, thus having 'off-targets' other than PDE4 to have direct control over proteins that are involved in the advancement of metastasis.

Solvation free energies from neural thermodynamic integration

We present a method for computing free-energy differences using thermodynamic integration with a neural network potential that interpolates between two target Hamiltonians. The interpolation is defined at the sample distribution level, and the neural network potential is optimized to match the corresponding equilibrium potential at every intermediate time step. Once the interpolating potentials and samples are well-aligned, the free-energy difference can be estimated using (neural) thermodynamic integration. To target molecular systems, we simultaneously couple Lennard-Jones and electrostatic interactions and model the rigid-body rotation of molecules. We report accurate results for several benchmark systems: a Lennard-Jones particle in a Lennard-Jones fluid, as well as the insertion of both water and methane solutes in a water solvent at atomistic resolution using a simple three-body neural-network potential.

Understanding dynamics in coarse-grained models. V. Extension of coarse-grained dynamics theory to non-hard sphere systems

Coarse-grained (CG) modeling has gained significant attention in recent years due to its wide applicability in enhancing the spatiotemporal scales of molecular simulations. While CG simulations, often performed with Hamiltonian mechanics, faithfully recapitulate structural correlations at equilibrium, they lead to ambiguously accelerated dynamics. In Paper I [J. Jin, K. S. Schweizer, and G. A. Voth, J. Chem. Phys. 158(3), 034103 (2023)], we proposed the excess entropy scaling relationship to understand the CG dynamics. Then, in Paper II [J. Jin, K. S. Schweizer, and G. A. Voth, J. Chem. Phys. 158(3), 034104 (2023)], we developed a theory to map the CG system into a dynamically consistent hard sphere system to analytically derive an expression for fast CG dynamics. However, many chemical and physical systems do not exhibit hard sphere-like behavior, limiting the extensibility of the developed theory. In this paper, we aim to generalize the theory to the non-hard sphere system based on the Weeks-Chandler-Andersen perturbation theory. Since non-hard sphere-like CG interactions affect the excess entropy term as it deviates from the hard sphere description, we explicitly account for the extra entropy to correct the non-hard sphere nature of the system. This approach is demonstrated for two different types of interactions seen in liquids, and we further provide a generalized description for any CG models using the generalized Gaussian CG models using Gaussian basis sets. Altogether, this work allows for extending the range and applicability of the hard sphere CG dynamics theory to a myriad of CG liquids.

Structural insights into lipid chain-length selectivity and allosteric regulation of FFA2

The free fatty acid receptor 2 (FFA2) is a G protein-coupled receptor (GPCR) that selectively recognizes short-chain fatty acids to regulate metabolic and immune functions. As a promising therapeutic target, FFA2 has been the focus of intensive development of synthetic ligands. However, the mechanisms by which endogenous and synthetic ligands modulate FFA2 activity remain unclear. Here, we present the structures of the human FFA2-Gi complex activated by the synthetic orthosteric agonist TUG-1375 and the positive allosteric modulator/allosteric agonist 4-CMTB, along with the structure of the inactive FFA2 bound to the antagonist GLPG0974. Structural comparisons with FFA1 and mutational studies reveal how FFA2 selects specific fatty acid chain lengths. Moreover, our structures reveal that GLPG0974 functions as an allosteric antagonist by binding adjacent to the orthosteric pocket to block agonist binding, whereas 4-CMTB binds the outer surface of transmembrane helices 6 and 7 to directly activate the receptor. Supported by computational and functional studies, these insights illuminate diverse mechanisms of ligand action, paving the way for precise GPCR-targeted drug design.

In vitro and in vivo neutralization of Dengue virus by a single domain antibody

To alleviate the contribution of antibody dependent enhancement in DenV pathogenesis, we obtain a DenV neutralizing single domain antibody (sdAb) from an in-house constructed phage display library of camelid VHH. The anti-DenV sdAb specifically reacts with the envelope (E) protein of DenV with a Kd value of 2x108. Molecular dynamic simulations and docking analysis show that the sdAb interacts with the DenV(E) protein via domain II (EDII) and interferes with the virus internalization process. The anti-DenV(E) sdAb potently inhibits the infectivity of a DenV(E) protein expressing pseudovirus as well as that of a virulent DenV in vitro. A mouse adapted DenV2 induces 100% mortality in the infected IFNRKO mice, but the animals injected with the sdAb neutralized virus remain fully protected. Furthermore, the therapeutically administered anti-DenV(E) sdAb slows down the disease progression and enhances the survival of DenV infected animals. In conclusion, we report an anti-DenV(E) sdAb as a potential therapy to manage DenV pathogenesis.

Computational analysis of the structural-functional dynamics of a Co-receptor proteoglycan

Nerve-Glial Antigen 2/Chondroitin Sulphate Proteoglycan 4 (NG2/CSPG4) is the largest membrane-intercalated cell surface component of the human proteome known to date. NG2/CSPG4 is endowed with the capability of engaging a myriad of molecular interactions and exert co-receptor functions, of which primary ones are sequestering of growth factors and the anchoring of cells to the extracellular matrix. However, the nature of the interactive dynamics of the proteoglycan remains veiled because of its conspicuous size and structural complexity. By leveraging on a multi-scale in silico approach, we have pioneered a comprehensive computational analysis of the structural-functional traits of the NG2/CSPG4 ectodomain. The modelling highlights an intricate assembly of β-sheet motifs linked together by flexible loops. Furthermore, our in silico predictions highlight that the previously delineated D1 domain may consistently remain more accessible for molecular interplays with respect to the D2 and D3 domains. Based on these findings, we have simulated the structural mechanism through the proteoglycan may serve as a co-receptor for growth factor FGF-2, showing that NG2/CSPG4 bends towards the receptor FGFR-1 for this growth factor and confirming the previously hypothesized trimeric complex formation promoted by FGF-2 dimers bridging the FGFR-1-proteoglycan interaction. The Chondroitin Sulphate Proteoglycan 4 is a large multi-domain transmembrane protein involved in several biological processes including pathological conditions. Despite its importance, it has never been studied at the atomistic level due to its large size. Here, we employed a multi-scale computer simulations approach to study its three-dimensional structure, its movements and co-receptor properties, showing that it can serve as mediator in the growth factor signaling process.

Increasing the Accuracy and Robustness of the CHARMM General Force Field with an Expanded Training Set

Small molecule empirical force fields (FFs), including the CHARMM General Force Field (CGenFF), are designed to have wide coverage of organic molecules and to rapidly assign parameters to molecules not explicitly included in the FF. Assignment of parameters to new molecules in CGenFF is based on a trained bond-angle-dihedral charge increment linear interpolation scheme for the partial atomic charges along with bonded parameters assigned based on analogy using a rules-based penalty score scheme associated with atom types and chemical connectivity. Accordingly, the accuracy of CGenFF is related to the extent of the training set of available parameters. In the present study that training set is extended by 1390 molecules selected to represent connectivities new to CGenFF training compounds. Quantum mechanical (QM) data for optimized geometries, bond, valence angle, and dihedral angle potential energy scans, interactions with water, molecular dipole moments, and electrostatic potentials were used as target data. The resultant bonded parameters and partial atomic charges were used to train a new version of the CGenFF program, v5.0, which was used to generate parameters for a validation set of molecules, including drug-like molecules approved by the FDA, which were then benchmarked against both experimental and QM data. CGenFF v5.0 shows overall improvements with respect to QM intramolecular geometries, vibrations, dihedral potential energy scans, dipole moments and interactions with water. Tests of pure solvent properties of 216 molecules show small improvements versus the previous release of CGenFF v2.5.1 reflecting the high quality of the Lennard-Jones parameters that were explicitly optimized during the initial optimization of both the CGenFF and the CHARMM36 force field. CGenFF v5.0 represents an improvement that is anticipated to more accurately model intramolecular geometries and strain energies as well as noncovalent interactions of drug-like and other organic molecules.

Accelerated peptide bond formation at air-water interfaces

Peptides and proteins, essential components of living organisms, are composed of amino acids linked by peptide bonds. However, the mechanism of peptide bond formation during the prebiotic era remains unclear. In this study, advanced Born-Oppenheimer molecular dynamics (BOMD) simulations were used to investigate the mechanisms and kinetics of peptide bond formation at air-water interfaces using diglycine, the simplest dipeptide, as a model molecule. The results show that peptide bonds can be rapidly formed via a unique isomerization-then-OH--elimination pathway. In this mechanism, the diglycine initially isomerizes into its acidic form at the air-water interface, followed by a reaction that releases an OH- anion rather than the previously hypothesized H2O. The free-energy barriers for the interfacial pathway with the assistance of an interfacial electric field are much lower than those in the gas phase by >25 kcal/mol. Further calculations suggest that this mechanism can be extended to the formation of some larger peptides, such as tetraglycine. This pathway offers insights into the origin of life and could inform the development of methods for peptide synthesis.

In Silico Study of a Bacteriorhodopsin/TiO2 Hybrid System at the Molecular Level

Bacteriorhodopsin (bR) is a light-harvesting membrane protein that represents a promising sensitizer of TiO2 for photovoltaic and photoelectrochemical devices. However, despite numerous experimental studies, the molecular-level understanding of the bR/TiO2 hybrid system is still unsatisfactory. In this contribution, we report the construction and analysis of an atomistic model of such a system. To do so, both steered molecular dynamics-molecular dynamics and quantum mechanics/molecular mechanics computations are applied to four different bR orientations on the anatase TiO2 surface. The resulting bR/TiO2 models are then used to compute the light absorption maxima changes relative to those of bR. We show that all four models reproduce the experimentally observed blue-shift value induced by bR binding on TiO2 and could be used to study the binding and binding-induced protein modifications. We conclude that the constructed models could provide a basis for future studies aiming to simulate the complex long-range electron transfer mechanism in bR/TiO2-based solar energy conversion devices as well as in engineering bR to achieve enhanced efficiencies.

Mutagenesis-based optimal design of plant peptide phytosulfokine for enhanced biological activity

Recognition of phytosulfokine (PSK), a sulfated pentapeptide, by its receptor PSKRs is crucial in regulating plant growth, development, and reproduction. However, designing highly active PSK remains a formidable challenge due to the lack of understanding of the structure-property relationship, structural dynamics, and the binding characteristics of PSK. Here, with a combined theoretical and experimental approach, we have investigated the binding dynamics of key interactions between PSK and AtPSKR1LRR to reveal the molecular mechanism of PSK recognition. Our molecular dynamics simulations and free energy perturbation calculations demonstrate that the sulfated tyrosines (PSKsY1 and PSKsY3) are indispensable for forming stable PSK-AtPSKR1LRR complex, while the alanine substitution at PSKQ5 site is rather tolerated. Furthermore, two promising PSK peptide analogs (PSKQ5A and PSKQ5K) with enhanced biological activity have been designed through in silico mutagenesis studies and in vivo experiments. They have a strong promoting effect (20 % enhancement) on stimulating root development compared with the wild-type PSK treatment. This work offers an effective strategy to design new peptide-based drugs for facilitating plant growth and consequent crop productivity, potentially benefiting efforts to address the global food crisis.

Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation

Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To study binding kinetics computationally, it is necessary to identify all of the possible ligand dissociation pathways. The site identification by ligand competitive saturation (SILCS) method involves the precomputation of a set of maps (FragMaps), which describe the free energy landscapes of typical chemical functionalities in and around a target protein or RNA. In the current work, we present and implement a method to use SILCS to identify ligand dissociation pathways, termed "SILCS-Pathway." The A* pathfinding algorithm is utilized to enumerate ligand dissociation pathways between the ligand binding site and the surrounding bulk solvent environment defined on evenly spaced points around the protein based on a Fibonacci lattice. The cost function for the A* algorithm is calculated using the SILCS exclusion maps and the SILCS grid free energy scores, thereby identifying paths that account for local protein flexibility and potential favorable interactions with the ligand. By traversing all evenly distributed bulk solvent points around the protein, we located all possible dissociation pathways and clustered them to identify general ligand unbinding pathways. The procedure is verified by using proteins studied previously with enhanced sampling molecular dynamics (MD) techniques and is shown to be capable of capturing important ligand dissociation routes in a highly computationally efficient manner. The identified pathways will act as the foundation for determining ligand dissociation kinetics using SILCS free energy profiles, which will be described in a subsequent article.

Phylogenetic history and temperature adaptation contribute to structural and functional stability of proteins in marine mollusks

Teasing apart the influences of phylogenetic history from thermal adaptation is a focal challenge in understanding the factors driving change in protein stability. This study conducted comprehensive comparative analyses between the phylogenetic relationships and functional/structural stabilities at protein and mRNA levels of cytosolic malate dehydrogenase (cMDH) orthologs of 41 marine mollusks living at widely different environmental temperatures. At the protein level, a significant negative correlation between adaptation temperature and heat-induced movements of the cMDH backbone was found. The movement fluctuation of individual residue varied similarly among cMDH orthologs. At the mRNA level, the free energy that occurs during the formation of the ensemble of mRNA secondary structure was significantly positively correlated with adaptation temperature. The fraction of guanine and cytosine increased with adaptation temperature. The proportion of variance in adaptation temperature that can be explained by the thermal stability (R2) was decreased after phylogenetic generalized least squares but was almost significant at both protein and mRNA levels (P < 0.05). Those analyses reveal the phylogenetic influence on the thermal adaptation of species. Our findings indicated that multi-level analysis of orthologous proteins should be considered alongside phylogenetic history to permit the development of a more comprehensive understanding of protein thermal adaptation.

Multiphasic condensates formed with mono-component of tetrapeptides via phase separation

Biomolecular condensates, formed by liquid-liquid phase separation of biomacromolecules, play crucial roles in regulating physiological events in biological systems. While multiphasic condensates have been extensively studied, those derived from a single component of short peptides have not yet been reported. Here, we report the symmetrical core-shell structural biomolecular condensates formed with a programmable tetrapeptide library via phase separation. Our findings reveal that tryptophan is essential for core-shell structure formation due to its strongest homotypical π-π interaction, enabling us to modulate the structure of condensates from core-shell to homogeneous by altering the amino acid composition. Molecular dynamics simulation combined with cryogenic focused ion beam scanning electron microscopy and cryogenic electron microscopy show that the inner core of multiphasic tetrapeptide condensates is solid-like, consisting of ordered structures. The core is enveloped by a liquid-like shell, stabilizing the core structure. Furthermore, we demonstrate control over multiphasic condensate formation through intrinsic redox reactions or post-translational modifications, facilitating the rational design of synthetic multiphasic condensates for various applications on demand.

Unveiling the Catalytic Mechanism of Abl1 Kinase: A Single-Magnesium Ion Pathway for Phosphoryl Transfer

Abl1, a nonreceptor tyrosine kinase closely related to Src kinase, regulates critical cellular processes like proliferation, differentiation, cytoskeletal dynamics, and response to environmental cues through phosphorylation-driven activation. Dysregulation places it centrally in the oncogenic pathway leading to blood cancers. making it an ideal drug target for small molecule inhibitors. We sought to understand the underlying mechanism of the phosphoryl-transfer step from the ATP molecule to the substrate tyrosine, as carried out by the Abl1 enzyme. By calculating free energy profiles for the reaction using the empirical valence bond representation of the reacting fragments paired with molecular dynamics and free energy perturbation calculations, a combination of several plausible reaction pathways, ATP conformations, and the number of magnesium ion cofactors have been investigated. For the best-catalyzed pathway, which proceeds through a dissociative mechanism with a single magnesium ion situated in Site I, a close agreement was reached with the experimentally determined catalytic rates. We conclude that the catalytic mechanism in Abl1 requires one magnesium ion for efficient catalysis, unlike other kinases, where two ions are utilized. A better overall understanding of the phosphoryl-transfer reactions in Abl1 can be used for type-I inhibitor development and generally contributes to a comprehensive overview of the mechanism for ATP-driven reactions.

Crystal Structure, Modeling, and Identification of Key Residues Provide Insights into the Mechanism of the Key Toxoflavin Biosynthesis Protein ToxD

Toxoflavin, a toxic secondary metabolite produced by a variety of bacteria, has been implicated as a causative agent in food poisoning and a virulence factor in phytopathogenic bacteria. This toxin is produced by genes encoded in the tox operon in Burkholderia glumae, in which the encoded protein, ToxD, was previously characterized as essential for toxoflavin production. To better understand the function of ToxD in toxoflavin biosynthesis and provide a basis for future work to develop inhibitors of ToxD, we undertook the identification of structurally and catalytically important amino acid residues through a combination of X-ray crystallography and site directed mutagenesis. We solved the structure of BgToxD, which crystallized as a dimer, to 1.8 Å resolution. We identified a citrate molecule in the putative active site. To investigate the role of individual residues, we used Pseudomonas protegens Pf-5, a BL1 plant protective bacterium known to produce toxoflavin, and created mutants in the ToxD-homologue PFL1035. Using a multiple sequence alignment and the BgToxD structure, we identified and explored the functional importance of 12 conserved residues in the putative active site. Eight variants of PFL1035 resulted in no observable production of toxoflavin. In contrast, four ToxD variants resulted in reduced but detectable toxoflavin production suggesting a nonessential role. The crystal structure and structural models of the substrate and intermediate bound enzyme provide a molecular interpretation for the mutagenesis data.

Exploring tubulin-paclitaxel binding modes through extensive molecular dynamics simulations

Cancer treatment remains a pressing challenge, with paclitaxel playing a pivotal role in chemotherapy by disrupting mitotic spindle dynamics through microtubule stabilization. However, the molecular details of paclitaxel interaction with β-tubulin, its target, remain elusive, impeding efforts to overcome drug resistance and optimize efficacy. Here, we employ extensive molecular dynamics simulations to probe the binding modes of paclitaxel within tubulin protofilaments. Our simulations reveal a spectrum of paclitaxel binding poses, correlated with conformational changes in neighboring residues, proposing the ligand (un)binding route. These diverse binding modes exhibit varied interaction patterns and binding energies, elucidating the complex interplay between paclitaxel-tubulin interactions and the conformational dynamics of the M-loop. Furthermore, key residues influencing paclitaxel affinity and resistance are identified, enhancing our mechanistic understanding of the drug-binding mechanism. Finally, we uncover a novel high-affinity binding mode characterized by paclitaxel penetration into a subpocket formed by helices 1, 7, and loop B9-B10 of β-tubulin concerted with the rotational isomerization around a bond connecting the tetracyclic baccatin core with the N-benzoyl-β-phenylisoserine side chain, offering potential avenues for drug development. Our study advances the understanding of paclitaxel mode of action and informs strategies for rational drug design of antitumor agents.

Membrane-dependent dynamics and dual translocation mechanisms of ABCB4: Insights from molecular dynamics simulations

ABCB4 is an ATP-binding cassette transporter expressed at the canalicular membrane of hepatocytes and responsible for translocating phosphatidylcholine into bile. Despite the recent cryo-EM structures of ABCB4, knowledge about the molecular mechanism of phosphatidylcholine transport remains fragmented. In this study, we used all-atom molecular dynamics simulations to investigate ABCB4 dynamics during its transport cycle, leveraging both symmetric and asymmetric membrane models. Our results demonstrate that membrane composition influences the local conformational dynamics of ABCB4, revealing distinct lipid-binding patterns across different conformers, particularly for cholesterol. We explored the two potential mechanisms for phosphatidylcholine translocation: the canonical ATP-driven alternating access model and the "credit-card swipe" model. Critical residues were identified for phosphatidylcholine binding and transport pathway modulation, supporting the canonical mechanism while also indicating a possible additional pathway. The conformer-specific roles of kinking in transmembrane helices (TMH4 and TMH10) were highlighted as key events in substrate translocation. Overall, ABCB4 may utilize a cooperative transport mechanism, integrating elements of both models to facilitate efficient phosphatidylcholine motion across the membrane. This study provides new insights into the relationship between membrane environment and ABCB4 function, contributing to our understanding of its role in bile physiology and susceptibility to genetic and xenobiotic influences.

Computational Methods for Modeling Lipid-Mediated Active Pharmaceutical Ingredient Delivery

Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.