CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

The Role of Protonation in the PfMATE Transporter Protein Structural Transitions

Multi-antimicrobial extrusion (MATE) transporter membrane proteins provide drug and toxin resistivity by expelling compounds from cells. MATE proteins can be pictured as V-shaped. To regulate its functioning, the protein structure can switch between outward-facing (OF) and inward-facing (IF). Pyrococcus furiosus MATE (PfMATE) is the only member of the multidrug/oligosaccharidyl-lipid/polysaccharide (MOP) superfamily that has available both the IF and OF crystal structures. With the availability of both the IF and OF structures, we are able to perform computational investigations to determine how protonation of specific amino acids causes a cascade of changes in the protein conformation that allow PfMATE to change its state from OF to IF in order to regulate its antiporter function. Using a variety of computational and theoretical techniques, we investigated four different systems of IF and OF PfMATE along with the native archaeal lipid bilayer, without or with protonation at the experimentally determined locations within the protein. We performed molecular dynamics (MD) simulations to investigate the flexibility of the four different PfMATE structures and also performed targeted molecular dynamics (TMD) simulations, during which we observed occluded conformations. Our analysis of hydrogen bond changes, potential of mean force, dynamic network analysis, and transfer entropy analysis provides information on how protonation can induce cascading structural changes responsible for the transition between the IF and OF configurations.

In silico vaccine design for Yersinia enterocolitica: A comprehensive approach to enhanced immunogenicity, efficacy and protection

Yersinia enterocolitica, a foodborne pathogen, has emerged as a significant public health concern due to its increased prevalence and multidrug resistance. This study employed reverse vaccinology to identify novel vaccine candidates against Y. enterocolitica through comprehensive in silico analyses. The core genome's conserved protein translocase subunit SecY was selected as the target, and potential B-cell, MHC class I, and MHC class II epitopes were mapped. 3B-cell epitopes, 3 MHCI and 11 MHCII epitopes were acquired. A multi-epitope vaccine construct was designed by incorporating the identified epitopes, TLR4 Agonist was used as adjuvants to enhance the immunogenic response. EAAAK, CPGPG and AYY linkers were used to form a vaccine construct, followed by extensive computational evaluations. The vaccine exhibited desirable physicochemical properties, stable secondary and tertiary structures as evaluated by PDBSum and trRosetta. Moreover, favorable interactions with the human Toll-like receptor 4 (TLR4) was observed by ClusPro. Population coverage analysis estimated the vaccine's applicability across 99.74 % in diverse populations. In addition, molecular dynamics simulations and normal mode analysis confirmed the vaccine's structural stability and dynamics in a simulated biological environment. Furthermore, codon optimization and in silico cloning facilitated the evaluation of the vaccine's expression potential in E. coli and pET-28a was used a recombinant plasmid. This study provides a promising foundation for the development of an efficacious vaccine against Y. enterocolitica infections.

An influence of electronic structure theory method, thermodynamic and implicit solvation corrections on the organic carbonates conformational and binding energies

An impact of an electronic structure or force field method, gas-phase thermodynamic correction, and continuum solvation model on organic carbonate clusters (S)n conformational and binding energies is explored. None of the tested force field (GFN-FF, GAFF, MMFF94) and standard semiempirical methods (PM3, AM1, RM1, PM6, PM6-D3, PM6-D3H4, PM7) can reproduce reference RI-SCS-MP2 conformational energies. Tight-binding GFNn-xTB methods provide more realistic conformational energies which are accurate enough to discard the least stable conformers. The effect of thermodynamic correction is moderate and can be ignored if the gas phase conformational stability ranking is a goal. The influence of continuum solvation is stronger, especially if reinforced with the Gibbs free energy thermodynamic correction, and results in the reduced spread of conformational energies. The cluster formation binding energies strongly depend on a particular approach to vibrational thermochemistry with the difference between traditional harmonic and modified scaled rigid - harmonic oscillator approximations reaching 10 kcal mol-1.

Elucidation of the hydration pattern of trifluoroacetic acid in dilute solutions: FTIR and computational study

The atmospheric partitioning of trifluoroacetic acid (TFA) in aerosol is a complex function of the size of suspended water droplets and their pH value. The unraveling of the affinity of TFA towards basic but not acidic conditions may be accomplished by providing an insight into the hydration pattern of undissociated TFA. Owing to rather scarce details on very dilute aqueous solutions of trifluoroacetic acid (TFA), we examined CF3COOD and CF3COONa solutions in D2O in the concentration range 0.001-0.1 mol dm-3 using transmission FTIR spectroscopy and computational methods. Besides detecting the signals originated from undissociated species in both CF3COOD (1787 cm-1 and 1766 cm-1 at c0 = 0.1 mol dm-3) and CF3COONa (1807 cm-1 at c0 = 0.1 mol dm-3) D2O solutions, through computational techniques we identified different TFA hydrates that contribute to the complexity of the spectral appearance. The combination of experimental and computational data suggested the concentration dependence of the predominant hydrogen bonding pattern of TFA. The results obtained in this work should help in understanding the partitioning of TFA into micron-size water droplets in the atmosphere in molecular and structural terms, i.e. the eventual stability of a hydrated complex for a particular TFA conformer.

Acidic sphingomyelinase interactions with lysosomal membranes and cation amphiphilic drugs: A molecular dynamics investigation

Lysosomes are pivotal in cellular functions and disease, influencing cancer progression and therapy resistance with Acid Sphingomyelinase (ASM) governing their membrane integrity. Moreover, cation amphiphilic drugs (CADs) are known as ASM inhibitors and have anti-cancer activity, but the structural mechanisms of their interactions with the lysosomal membrane and ASM are poorly explored. Our study, leveraging all-atom explicit solvent molecular dynamics simulations, delves into the interaction of glycosylated ASM with the lysosomal membrane and the effects of CAD representatives, i.e., ebastine, hydroxyebastine and loratadine, on the membrane and ASM. Our results confirm the ASM association to the membrane through the saposin domain, previously only shown with coarse-grained models. Furthermore, we elucidated the role of specific residues and ASM-induced membrane curvature in lipid recruitment and orientation. CADs also interfere with the association of ASM with the membrane at the level of a loop in the catalytic domain engaging in membrane interactions. Our computational approach, applicable to various CADs or membrane compositions, provides insights into ASM and CAD interaction with the membrane, offering a valuable tool for future studies.

Challenging the Biginelli scaffold to surpass the first line antitubercular drugs: Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt) inhibition activity and molecular modelling studies

New Biginelli adducts were rationalised, via the introduction of selected anti-tubercular (TB) pharmacophores into the dihydropyrimidine (DHPM) ring of deoxythymidine monophosphate (dTMP), the natural substrate of Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt). Repurposing was one of the design rationale strategies for some selected mimics of the designed compounds. The anti-TB activity was screened against the Mtb H37Rv strain where 11a was superior to ethambutol (EMB), and was 9-fold more potent than pyrazinamide (PZA). Additionally, compounds 11b, 4a, 4b, 13a, 13b and 14a elicited higher anti-TB activity than PZA, showing better safety profiles than EMB against RAW 264.7 cells' growth. The in vitro TMPKmt inhibition assay released compounds 11a, 11b and 13b as the most potent inhibitors. Docking studies presumed the binding modes and molecular dynamics (MD) simulation revealed the dynamic stability of 11a-TMPKmt complex over 100 ns. In silico prediction of the chemo-informatics properties of the most active compounds was conducted.

Isomer-sourced structure iteration methods for in silico development of inhibitors: Inducing GTP-bound NRAS-Q61 oncogenic mutations to an "off-like" state

The NRAS-mutant subset of melanoma represent some of the most aggressive and deadliest types associated with poor overall survival. Unfortunately, for more than 40 years, no therapeutic agent directly targeting NRAS mutations has been clinically approved. In this work, based on microsecond scale molecular dynamics simulations, the effect of Q61 mutations on NRAS conformational characteristics is revealed at the atomic level. The GTP-bound NRAS-Q61R and Q61K mutations show a specific targetable pocket between Switch-II and α-helix 3 whereas the NRAS-Q61L non-polar mutation category shows a different targetable pocket. Moreover, a new isomer-sourced structure iteration method has been developed for the in silico design of potential inhibitor prototypes for oncogenes. We show the possibility of a designed prototype HM-387 to target activated NRAS-Q61R and that it can gradually induce the transition from the activated NRAS-Q61R to an "off-like" state.

Structure optimization and molecular dynamics studies of new tumor-selective s-triazines targeting DNA and MMP-10/13 for halting colorectal and secondary liver cancers

A series of triazole-tethered triazines bearing pharmacophoric features of DNA-targeting agents and non-hydroxamate MMPs inhibitors were synthesized and screened against HCT-116, Caco-2 cells, and normal colonocytes by MTT assay. 7a and 7g surpassed doxorubicin against HCT-116 cells regarding potency (IC50 = 0.87 and 1.41 nM) and safety (SI = 181.93 and 54.41). 7g was potent against liver cancer (HepG-2; IC50 = 65.08 nM), the main metastatic site of CRC with correlation to MMP-13 expression. Both derivatives induced DNA damage at 2.67 and 1.87 nM, disrupted HCT-116 cell cycle and triggered apoptosis by 33.17% compared to doxorubicin (DNA damage at 0.76 nM and 40.21% apoptosis induction). 7g surpassed NNGH against MMP-10 (IC50 = 0.205 μM) and MMP-13 (IC50 = 0.275 μM) and downregulated HCT-116 VEGF related to CRC progression by 38%. Docking and MDs simulated ligands-receptors binding modes and highlighted SAR. Their ADMET profiles, drug-likeness and possible off-targets were computationally predicted.

Mechanistic insights into P-glycoprotein ligand transport and inhibition revealed by enhanced molecular dynamics simulations

P-glycoprotein (P-gp) plays a crucial role in cellular detoxification and drug efflux processes, transitioning between inward-facing (IF) open, occluded, and outward-facing (OF) states to facilitate substrate transport. Its role is critical in cancer therapy, where P-gp contributes to the multidrug resistance phenotype. In our study, classical and enhanced molecular dynamics (MD) simulations were conducted to dissect the structural and functional features of the P-gp conformational states. Our advanced MD simulations, including kinetically excited targeted MD (ketMD) and adiabatic biasing MD (ABMD), provided deeper insights into state transition and translocation mechanisms. Our findings suggest that the unkinking of TM4 and TM10 helices is a prerequisite for correctly achieving the outward conformation. Simulations of the IF-occluded conformations, characterized by kinked TM4 and TM10 helices, consistently demonstrated altered communication between the transmembrane domains (TMDs) and nucleotide binding domain 2 (NBD2), suggesting the implication of this interface in inhibiting P-gp's efflux function. A particular emphasis was placed on the unstructured linker segment connecting the NBD1 to TMD2 and its role in the transporter's dynamics. With the linker present, we specifically noticed a potential entrance of cholesterol (CHOL) through the TM4-TM6 portal, shedding light on crucial residues involved in accommodating CHOL. We therefore suggest that this entry mechanism could be employed for some P-gp substrates or inhibitors. Our results provide critical data for understanding P-gp functioning and developing new P-gp inhibitors for establishing more effective strategies against multidrug resistance.

Structure-guided mutations in CDRs for enhancing the affinity of neutralizing SARS-CoV-2 nanobody

The optimization of antibodies to attain the desired levels of affinity and specificity holds great promise for the development of next generation therapeutics. This study delves into the refinement and engineering of complementarity-determining regions (CDRs) through in silico affinity maturation followed by binding validation using isothermal titration calorimetry (ITC) and pseudovirus-based neutralization assays. Specifically, it focuses on engineering CDRs targeting the epitopes of receptor-binding domain (RBD) of the spike protein of SARS-CoV-2. A structure-guided virtual library of 112 single mutations in CDRs was generated and screened against RBD to select the potential affinity-enhancing mutations. Protein-protein docking analysis identified 32 single mutants of which nine mutants were selected for molecular dynamics (MD) simulations. Subsequently, biophysical ITC studies provided insights into binding affinity, and consistent with in silico findings, six mutations that demonstrated better binding affinity than native nanobody were further tested in vitro for neutralization activity against SARS-CoV-2 pseudovirus. Leu106Thr mutant was found to be most effective in virus-neutralization with IC50 values of ∼0.03 μM, as compared to the native nanobody (IC50 ∼0.77 μM). Thus, in this study, the developed computational pipeline guided by structure-aided interface profiles and thermodynamic analysis holds promise for the streamlined development of antibody-based therapeutic interventions against emerging variants of SARS-CoV-2 and other infectious pathogens.

Hydrophobic forces at play: insights into AmelOBP4 and brood volatile interactions in Apis mellifera hygienic behavior

Understanding the intricate processes underlying olfaction necessitates unraveling the complexities of odorant binding protein's interactions with volatile compounds triggering hygienic behavior in Apis mellifera, This study delves into the intricate processes of olfaction by focusing on the interactions between Apis mellifera Odorant Binding Protein 4 (AmelOBP4) and volatile compounds associated with hygienic behavior, employing a comprehensive computational approach. Molecular docking analyses reveal detailed binding interactions, emphasizing the significance of hydrophobic interactions and specific amino acid residues in stabilizing AmelOBP4-volatile complexes, notably with 2-nonacosanone (-8.4 kcal/mol) and hexacosyl acetate (-8.4 kcal/mol). Molecular dynamics simulations demonstrate sustained stability and principal component analysis affirms structural integrity through restricted global motions. Binding free energy calculations underscore robust interactions, with per-residue free energy decomposition identifying key amino acids contributing significantly to binding affinity. These findings illuminate the pivotal role of hydrophobic interactions and specific residues (Phe 60, Leu 83, Ile 116, Leu 126, and Leu 130) in modulating AmelOBP4-volatile interactions, providing foundational insights into volatile-based applications and potential olfactory response modulation, contributing to our understanding of olfactory processes.

A Strep-Tag Imprinted Polymer Platform for Heterogenous Bio(electro)catalysis

Molecularly imprinted polymers (MIPs) are artificial receptors equipped with selective recognition sites for target molecules. One of the most promising strategies for protein MIPs relies on the exploitation of short surface-exposed protein fragments, termed epitopes, as templates to imprint binding sites in a polymer scaffold for a desired protein. However, the lack of high-resolution structural data of flexible surface-exposed regions challenges the selection of suitable epitopes. Here, we addressed this drawback by developing a polyscopoletin-based MIP that recognizes recombinant proteins via imprinting of the widely used Strep-tag II affinity peptide (Strep-MIP). Electrochemistry, surface-sensitive IR spectroscopy, and molecular dynamics simulations were employed to ensure an utmost control of the Strep-MIP electrosynthesis. The functionality of this novel platform was verified with two Strep-tagged enzymes: an O2-tolerant [NiFe]-hydrogenase, and an alkaline phosphatase. The enzymes preserved their biocatalytic activities after multiple utilization confirming the efficiency of Strep-MIP as a general biocompatible platform to confine recombinant proteins for exploitation in biotechnology.

Synthesis, pharmacological evaluation, and modeling of novel quaternary ammonium salts derived from β-carboline containing an imidazole moiety as angiogenesis inhibitors

In this study, a series of novel β-carboline condensed imidazolium derivatives (7a-7y) were designed and synthesized by incorporating imidazolium salt structures into β-carboline. The cytotoxicity of compounds 7a-7y was evaluated in various cancer cell lines, including lung cancer (A549), gastric cancer (BGC-823), mouse colon cancer (CT-26), liver cancer (Bel-7402), and breast cancer (MCF-7), using the MTT assay. Most compounds exhibited significant activity against one or more of the cancer cell lines. Notably, compounds 7 g, 7o, 7r, 7 s, 7u, 7v, 7x, and 7w showed the highest cytotoxic activity (IC50 < 2 μM) in the tested tumor cell lines. Compound 7x demonstrated cytotoxic activities of 1.3 ± 0.3 μM (for BGC-823), 2.4 ± 0.4 μM (against A549), 7.8 ± 0.9 μM (for Bel-7402), and 9.8 ± 1.4 μM (against CT-26). The chick chorioallantoic membrane assay revealed significant anti-angiogenic potential of compound 7x. Molecular imprinting studies suggested the anti-angiogenic effect of compound 7x might be attributed to inhibition of VEGFR2 kinase. Molecular docking and molecular dynamics further indicate that its activity may be primarily associated with the potential inhibition of VEGFR2. Our research outcomes have provided valuable lead compounds for the development of novel antitumor drugs and have offered beneficial insights for subsequent drug design and optimization.

High Yield of L-Sorbose via D-Glucose Isomerization in Ethanol over a Bifunctional Titanium-Boron-Beta Zeolite

D-Glucose-to-L-sorbose isomerization on Lewis acidic zeolite is a highly attractive avenue for sorbose production. But the L-sorbose yield is limited by the competing D-glucose-to-D-fructose isomerization and reaction equilibrium. In this work, it is suggested that ethanol directs the glucose conformation for selective D-glucose-to-L-sorbose isomerization. It also reacts with the produced L-sorbose to form ethyl-sorboside, which allows the D-glucose-to-L-sorbose isomerization to proceed beyond the thermodynamic equilibrium limit. It is shown that a bifunctional zeolite Beta containing framework titanium (Ti) and boron (B) is a selective catalyst for this tandem reaction: Lewis acidic framework Ti catalyzes the D-glucose-to-L-sorbose isomerization via an intramolecular 5,1-hydride shift process as confirmed by isotopic tracing experiments followed by 13C-NMR, while weak Brønsted acid framework B selectively promotes the sorbose ketalization with ethanol. A remarkably high yield of L-sorbose with a high fraction of sugar (>95 %: 27 % unreacted glucose, 11.4 % fructose, 57 % sorbose) was obtained after the mixture produced in ethanol was hydrolyzed.

Structural Analysis of Mammalian Sialic Acid Esterase

Sialic acid esterase (SIAE) catalyzes the removal of O-acetyl groups from sialic acids found on cell surface glycoproteins to regulate cellular processes such as B cell receptor signalling and apoptosis. Loss-of-function mutations in SIAE are associated with several common autoimmune diseases including Crohn's, ulcerative colitis, and arthritis. To gain a better understanding of the function and regulation of this protein, we determined crystal structures of SIAE from three mammalian homologs, including an acetate bound structure. The structures reveal that the catalytic domain adopts the fold of the SGNH hydrolase superfamily. The active site is composed of a catalytic dyad, as opposed to the previously reported catalytic triad. Attempts to determine a substrate-bound structure yielded only the hydrolyzed product acetate in the active site. Rigid docking of complete substrates followed by molecular dynamics simulations revealed that the active site does not form specific interactions with substrates, rather it appears to be broadly specific to accept sialoglycans with diverse modifications. Based on the acetate bound structure, a catalytic mechanism is proposed. Structural mapping of disease mutations reveals that most are located on the surface of the enzyme and would only cause minor disruptions to the protein fold, suggesting that these mutations likely affect binding to other factors. These results improve our understanding of SIAE biology and may aid in the development of therapies for autoimmune diseases and cancer.

BEGAN: Boltzmann-Reweighted Data Augmentation for Enhanced GAN-Based Molecule Design in Insect Pheromone Receptors

Identifying small molecules that bind strongly to target proteins in rational molecular design is crucial. Machine learning techniques, such as generative adversarial networks (GAN), are now essential tools for generating such molecules. In this study, we present an enhanced method for molecule generation using objective-reinforced GANs. Specifically, we introduce BEGAN (Boltzmann-enhanced GAN), a novel approach that adjusts molecule occurrence frequencies during training based on the Boltzmann distribution exp(-ΔU/τ), where ΔU represents the estimated binding free energy derived from docking algorithms and τ is a temperature-related scaling hyperparameter. This Boltzmann reweighting process shifts the generation process toward molecules with higher binding affinities, allowing the GAN to explore molecular spaces with superior binding properties. The reweighting process can also be refined through multiple iterations without altering the overall distribution shape. To validate our approach, we apply it to the design of sex pheromone analogs targeting Spodoptera frugiperda pheromone receptor SfruOR16, illustrating that the Boltzmann reweighting significantly increases the likelihood of generating promising sex pheromone analogs with improved binding affinities to SfruOR16, further supported by atomistic molecular dynamics simulations. Furthermore, we conduct a comprehensive investigation into parameter dependencies and propose a reasonable range for the hyperparameter τ. Our method offers a promising approach for optimizing molecular generation for enhanced protein binding, potentially increasing the efficiency of molecular discovery pipelines.

In Silico Structural Comparison of Aromatic and Aliphatic Chiral Peptoid Oligomers

Atomistic simulations of peptoids have the capability to predict structure-property relationships, depending on the accuracy of the associated force field. This work presents an addendum to the CGenFF-NTOID peptoid force field for aliphatic side chains. We develop parameters for two aliphatic side chains, RN1-tertiary butylethyl glycine (r1tbe) and SN1-tertiary butylethyl glycine (s1tbe). Enhanced sampled (well-tempered metadynamics) atomistic simulations are performed using CGenFF-NTOID to determine the monomer structural preferences for these side chains. The free energy minima attained through these simulations are compared with structural observations obtained from experiments. We also compare the structural preferences of aliphatic s1tbe and aromatic SN1-naphthylethyl glycine (s1ne). This is done through parallel bias metadynamics on monomers and pentamers of s1tbe and s1ne. The structural observations through simulations are also compared with available experimental metrics of the dihedral angles and pitch. The pentamer minima structures are also compared with ab initio optimized structures, which show excellent agreement. This comparison illustrates alternatives to aromatic side chains that can be used to stabilize peptoid secondary structures. The developed parameters help to increase the diversity of peptoid side chains available for materials discovery through computational studies.

Machine-Learning Approach to Identify Potential Dengue Virus Protease Inhibitors: A Computational Perspective

The global prevalence of dengue virus (DENV), a widespread flavivirus, has led to varied epidemiological impacts, economic burdens, and health consequences. The alarming increase in infections is exacerbated by the absence of approved antiviral agents against the DENV. Within flaviviruses, the NS3/NS2B serine protease plays a pivotal role in processing the viral polyprotein into distinct components, making it an attractive target for antiviral drug development. In this study, machine-learning (ML) techniques were employed to build predictive models for the screening of a library containing 32,000 protease inhibitors. Utilizing GNINA for structure-based virtual screening, the top potential candidates underwent a subsequent evaluation of their absorption, distribution, metabolism, excretion, and toxicity properties. Selected compounds were subjected to molecular dynamics simulations and binding free energy calculations via MM/GBSA. The results suggest that comp530 possesses binding potential to DENV protease as a noncovalent inhibitor with multiple positions for chemical substitutions, presenting opportunities for optimizing their selectivity and specificity. However, other compounds predicted via ML models may still provide a promising start for covalent inhibitors.

Omics-centric evidences of fipronil biodegradation by Rhodococcus sp. FIP_B3

The widespread use of the pesticide fipronil in domestic and agriculture sectors has resulted in its accumulation across the environment. Its use to assure food security has inadvertently affected soil microbiome composition, fertility and, ultimately, human health. Degradation of residual fipronil present in the environment using specific microbial species is a promising strategy for its removal. The present study delves into the omics approach for fipronil biodegradation using the native bacterium Rhodococcus sp. FIP B3. It has been observed that within 40 days, nearly 84% of the insecticide gets degraded. The biodegradation follows a pseudo-first-order kinetics (k = 0.0197/d with a half-life of ∼11 days). Whole genome analysis revealed Cytochrome P450 monooxygenase, peroxidase-related enzyme, haloalkane dehalogenase, 2-nitropropane dioxygenase, and aconitate hydratase are involved in the degradation process. Fipronil-sulfone, 5-amino-1-(2-chloro-4-(trifluoromethyl)phenyl)-4- ((trifluoromethyl)sulfonyl)-1H-pyrazole-3-carbonitrile, (E)-5-chloro-2-oxo-3- (trifluoromethyl)pent-4-enoic acid, 4,4,4-trifluoro-2-oxobutanoic acid, and 3,3,3- trifluoropropanoic acid were identified as the major metabolites that support the bacterial degradation of fipronil. In-silico molecular docking and molecular dynamic simulation-based analyses of degradation pathway intermediates with their respective enzymes have indicated stable interactions with significant binding energies (-5.9 to -9.7 kcal/mol). These results have provided the mechanistic cause of the elevated potential of Rhodococcus sp. FIP_B3 for fipronil degradation and will be advantageous in framing appropriate strategies for the bioremediation of fipronil-contaminated environment.

Theoretically grounded approaches to account for polarization effects in fixed-charge force fields

Non-polarizable, or fixed-charge, force fields are the workhorses of most molecular simulation studies. They attempt to describe the potential energy surface (PES) of the system by including polarization effects in an implicit way. This has historically been done in a rather empirical and ad hoc manner. Recent theoretical treatments of polarization, however, offer promise for getting the most out of fixed-charge force fields by judicious choice of parameters (most significantly the net charge or dipole moment of the model) and application of post facto polarization corrections. This Perspective describes these polarization theories, namely the "halfway-charge" theory and the molecular dynamics in electronic continuum theory, and shows that they lead to qualitatively (and often, quantitatively) similar predictions. Moreover, they can be reconciled into a unified approach to construct a force field development workflow that can yield non-polarizable models with charge/dipole values that provide an optimal description of the PES. Several applications of this approach are reviewed, and avenues for future research are proposed.

Discerning potent CSF-1r inhibitors for targeting and therapy of neuroinflammation using computational approaches

Microglia, the primary cellular mediator of neuroinflammation, plays a pivotal role in numerous neurological disorders. Precise and non-invasive quantification of microglia is of paramount importance. Despite various investigations into cell-specific biomarkers for assessing neuroinflammation, many suffer from poor cellular specificity and low signal-to-noise ratios. Colony-stimulating factor-1 receptor (CSF-1R), also known as FMS kinase, has emerged as a promising neuroinflammation biomarker with significant relevance to inflammatory diseases. Additionally, CSF-1R inhibitors (CSF-1Ri) have shown therapeutic potential in central nervous system (CNS) pathological conditions by depleting microglia. Therefore, the development of more specific CSF-1R inhibitors for targeting and treating various CNS insults and neurological disorders is imperative. This study focuses on the search for novel CSF-1R inhibitors. Based on the literature on CSF-1R inhibitors, we proposed and investigated ten ligands as novel CSF-1R inhibitors. Among these, the top three ligands, selected based on their maximum binding scores in docking calculations, are subjected to 100 nanoseconds of molecular dynamics (MD) simulation, alongside three reference ligands. All protein-ligand complexes remain stable throughout the dynamics and exhibit minimal fluctuations during the analysis. The results obtained through this study may prove significant for the future design of CSF-1R inhibitors with potential applications in the field of biomedicine.

Transition Path Sampling Based Free Energy Calculations of Evolution's Effect on Rates in β-Lactamase: The Contributions of Rapid Protein Dynamics to Rate

β-Lactamases are one of the primary enzymes responsible for antibiotic resistance and have existed for billions of years. The structural differences between a modern class A TEM-1 β-lactamase compared to a sequentially reconstructed Gram-negative bacteria β-lactamase are minor. Despite the similar structures and mechanisms, there are different functions between the two enzymes. We recently identified differences in dynamics effects that result from evolutionary changes that could potentially account for the increase in substrate specificity and catalytic rate. In this study, we used transition path sampling-based calculations of free energies to identify how evolutionary changes found between an ancestral β-lactamase, and its extant counterpart TEM-1 β-lactamase affect rate.

The structural and mechanistic bases for the viral resistance to allosteric HIV-1 integrase inhibitor pirmitegravir

Allosteric HIV-1 integrase (IN) inhibitors (ALLINIs) are investigational antiretroviral agents that potently impair virion maturation by inducing hyper-multimerization of IN and inhibiting its interaction with viral genomic RNA. The pyrrolopyridine-based ALLINI pirmitegravir (PIR) has recently advanced into phase 2a clinical trials. Previous cell culture-based viral breakthrough assays identified the HIV-1(Y99H/A128T IN) variant that confers substantial resistance to this inhibitor. Here, we have elucidated the unexpected mechanism of viral resistance to PIR. Although both Tyr99 and Ala128 are positioned within the inhibitor binding V-shaped cavity at the IN catalytic core domain (CCD) dimer interface, the Y99H/A128T IN mutations did not substantially affect the direct binding of PIR to the CCD dimer or functional oligomerization of full-length IN. Instead, the drug-resistant mutations introduced a steric hindrance at the inhibitor-mediated interface between CCD and C-terminal domain (CTD) and compromised CTD binding to the CCDY99H/A128T + PIR complex. Consequently, full-length INY99H/A128T was substantially less susceptible to the PIR-induced hyper-multimerization than the WT protein, and HIV-1(Y99H/A128T IN) conferred >150-fold resistance to the inhibitor compared with the WT virus. By rationally modifying PIR, we have developed its analog EKC110, which readily induced hyper-multimerization of INY99H/A128T in vitro and was ~14-fold more potent against HIV-1(Y99H/A128T IN) than the parent inhibitor. These findings suggest a path for developing improved PIR chemotypes with a higher barrier to resistance for their potential clinical use.IMPORTANCEAntiretroviral therapies save the lives of millions of people living with HIV (PLWH). However, the evolution of multi-drug-resistant viral phenotypes is a major clinical problem, and there are limited or no treatment options for heavily treatment-experienced PLWH. Allosteric HIV-1 integrase inhibitors (ALLINIs) are a novel class of antiretroviral compounds that work by a unique mechanism of binding to the non-catalytic site on the viral protein and inducing aberrant integrase multimerization. Accordingly, ALLINIs potently inhibit both wild-type HIV-1 and all drug-resistant viral phenotypes that have so far emerged against currently used therapies. Pirmitegravir, a highly potent and safe investigational ALLINI, is currently advancing through clinical trials. Here, we have elucidated the structural and mechanistic bases behind the emergence of HIV-1 integrase mutations in infected cells that confer resistance to pirmitegravir. In turn, our findings allowed us to rationally develop an improved ALLINI with substantially enhanced potency against the pirmitegravir-resistant virus.

Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins

Modulating the function of Intrinsically Disordered Proteins (IDPs) with small molecules is of considerable importance given the crucial roles of IDPs in the pathophysiology of numerous diseases. Reported binding affinities for ligands to diverse IDPs vary broadly, and little is known about the detailed molecular mechanisms that underpin ligand efficacy. Molecular simulations of IDP ligand binding mechanisms can help us understand the mode of action of small molecule inhibitors of IDP function, but it is still unclear how binding energies can be modeled rigorously for such a flexible class of proteins. Here, we compare alchemical absolute binding free energy calculations (ABFE) and Markov-State Modeling (MSM) protocols to model the binding of the small molecule 10058-F4 to a disordered peptide extracted from a segment of the oncoprotein c-Myc. The ABFE results produce binding energy estimates that are sensitive to the choice of reference structure. In contrast, the MSM results produce more reproducible binding energy estimates consistent with weak mM binding affinities and transient intermolecular contacts reported in the literature.

Committor Guided Estimates of Molecular Transition Rates

The probability that a configuration of a physical system reacts, or transitions from one metastable state to another, is quantified by the committor function. This function contains richly detailed mechanistic information about transition pathways, but a full parametrization of the committor requires the construction of a high-dimensional function, a generically challenging task. Recent efforts to leverage neural networks as a means to solve high-dimensional partial differential equations, often called "physics-informed" machine learning, have brought the committor into computational reach. Here, we build on the semigroup approach to learning the committor and assess its utility for predicting dynamical quantities such as transition rates. We show that a careful reframing of the objective function and improved adaptive sampling strategies provide highly accurate representations of the committor. Furthermore, by directly applying the Hill relation, we show that these committors provide accurate transition rates for molecular systems.

Structural basis of MICAL autoinhibition

MICAL proteins play a crucial role in cellular dynamics by binding and disassembling actin filaments, impacting processes like axon guidance, cytokinesis, and cell morphology. Their cellular activity is tightly controlled, as dysregulation can lead to detrimental effects on cellular morphology. Although previous studies have suggested that MICALs are autoinhibited, and require Rab proteins to become active, the detailed molecular mechanisms remained unclear. Here, we report the cryo-EM structure of human MICAL1 at a nominal resolution of 3.1 Å. Structural analyses, alongside biochemical and functional studies, show that MICAL1 autoinhibition is mediated by an intramolecular interaction between its N-terminal catalytic and C-terminal coiled-coil domains, blocking F-actin interaction. Moreover, we demonstrate that allosteric changes in the coiled-coil domain and the binding of the tripartite assembly of CH-L2α1-LIM domains to the coiled-coil domain are crucial for MICAL activation and autoinhibition. These mechanisms appear to be evolutionarily conserved, suggesting a potential universality across the MICAL family.

Elucidating Protein Structures in the Gas Phase: Traversing Configuration Space with Biasing Methods

Achieving accurate characterization of protein structures in the gas phase continues to be a formidable challenge. To tackle this issue, the present study employs Molecular Dynamics (MD) simulations in tandem with enhanced sampling techniques (methods designed to efficiently explore protein conformations). The objective is to identify suitable structures of proteins by contrasting their calculated Collision Cross-Section (CCS) with those observed experimentally. Significant discrepancies were observed between the initial MD-simulated and experimentally measured CCS values through Ion Mobility-Mass Spectrometry (IMS-MS). To bridge this gap, we employed two distinct enhanced sampling methods, Harmonic Biasing Potential and Adaptive Biasing Force, which help the proteins overcome energy barriers to adopt more compact configurations. These techniques leverage the radius of gyration as a reaction coordinate (guiding parameter), guiding the system toward compressed states that potentially match experimental configurations more closely. The guiding forces are only employed to overcome existing barriers and are removed to allow the protein to naturally arrive at a potential gas phase configuration. The results demonstrated close alignment (within ∼4%) between simulated and experimental CCS values despite using different strengths and/or methods, validating their efficacy. This work lays the groundwork for future studies aimed at optimizing biasing methods and expanding the collective variables used for more accurate gas-phase structural predictions.

Discovery of Five Classes of Bacterial Defensins: Ancestral Precursors of Defensins from Eukarya?

Defensins are present in many organisms and are divided into two evolutionary groups, termed cis- and trans-defensins. Cis-defensins have only recently been reported in bacteria, and knowledge of these defensins is limited, with no family classification. Here, we describe the identification of 74 cis-defensins from bacteria and propose five classes for their classification. We also report the first NMR structure determination of a Myxoccocus xanthus defensin, as well as its in silico expression analysis. Xanthusin-1 has a unique structure among the published defensins, which could indicate that the proposed class II peptides constitute a separate group of defensins. Xanthusin-1 gene expression was observed in casitone-based and Streptomyces coelicolor coculture-grown media. Our results demonstrate a wider distribution of defensins outside the Eukarya domain, shedding light on the origin and distribution of defensins. The sharing of three disulfide defensins between bacteria and eukaryotes points to a possible prokaryotic origin of the CSαβ motif. Moreover, the identification of defensins in Gram-positive and Gram-negative bacteria indicates an early origin but with many gene losses during the evolutionary process, similar to findings for eukaryotic defensins.

Exploring Free Energy Landscapes for Protein Partitioning into Membrane Domains in All-Atom and Coarse-Grained Simulations

It is known that membrane environment can impact the structure and function of integral membrane proteins. As such, elucidation of the thermodynamic driving forces governing protein partitioning between membrane domains of varying lipid composition is a fundamental topic in membrane biophysics. Molecular dynamics simulations provide valuable tools for quantitatively characterizing the free energy landscapes governing protein partitioning at the molecular level. In this study, we propose an efficient simulation methodology for the calculation of free energies for the partitioning of transmembrane proteins between liquid-disorder (Ld) and liquid-ordered (Lo) domains in all-atom (AA) phase-separated lipid bilayers. The computed potential of mean force defining the equilibrium partition coefficients is compared for AA and coarse-grained systems. Energy decomposition is used to identify differences in the underlying thermodynamics. Our findings highlight the importance of employing AA models to accurately estimate relevant free energy changes during protein translation between membrane domains.

Insights into podophyllotoxin lactone features: New cyclolignans as potential dual tubulin-topoisomerase II inhibitors

Chemomodulation of natural cyclolignans as podophyllotoxin has been a successful approach to obtain semisynthetic bioactive derivates. One example of this approach is the FDA-approved drug etoposide for solid and hematological tumors. It differs from the antimitotic activity of the natural product in its mechanism of action, this drug being a topoisomerase II inhibitor instead of a tubulin antimitotic. Within the molecular requirements for the activity of these compounds, the trans-γ-lactone moiety presented in the parent compound has always been a feature to be explored to chemomodulate its bioactivity. In this study, we have obtained different compounds that comply with the molecular characteristics for antitubulin and antitopoisomerase II activity combined in a single molecule. Furthermore, we explored the influence of the trans-lactone moiety on the final activity, finding that the cis-lactone was also interesting in terms of bioactivity. The best values of cytotoxicity and cell cycle inhibition were obtained for a compound lacking the lactone ring, thus mimicking the podophyllic aldehyde functionalization, a selective antimitotic podophyllotoxin derivate. The analogs with cis-lactone also presented interesting cytotoxic activity. The present study illustrates the potential of the chemomodulation of natural products such as natural cyclolignan podophyllotoxin derivates for the discovery of new antitumor agents.

The role of lipid oxidation pathway in reactive oxygen species-mediated cargo release from liposomes

Reactive oxygen species (ROS)-mediated photooxidation is an efficient method for triggering a drug release from liposomes. In addition to the release of small molecules, it also allows the release of large macromolecules, making it a versatile tool for controlled drug delivery. However, the exact release mechanism of large macromolecules from ROS-sensitive liposomes is still unclear. There are no studies on the effect of lipid oxidation on the release of cargo molecules of different sizes. By using HPLC-HRMS method we analyzed the oxidation products of ROS-sensitive DOTAP lipid in phthalocyanine-loaded DOTAP:Cholesterol:DSPE-PEG liposomes after 630 nm light irradiation of different durations. Shorter illumination time (1-2 minutes) led to the formation of hydroperoxides and vic-alcohols predominantly. Longer 9-minute irradiation resulted already in aldehydes generation. Interestingly, the presence of epoxides/mono-hydroperoxides and vic-alcohols in a lipid bilayer ensured a high 90% release of small hydrophilic cargo molecules i.e. calcein, but not large (≥10 KDa) macromolecules. Oxidation till aldehydes was mandatory to deliver e.g. dextrans of 10-70 kDa with ca. 30% efficiency. Molecular dynamics simulations revealed that the formation of aldehydes is required to form pores or even fully disrupt the lipid membrane, while e.g. presence of hydroperoxides is enough to make the bilayer more permeable just for water and small molecules. This is an important finding that shed a light on the release mechanism of different cargo molecules from ROS-sensitive drug delivery systems.

Structure and Energetics of PET-Hydrolyzing Enzyme Complexes: A Systematic Comparison from Molecular Dynamics Simulations

Discovered in 2016, the enzyme PETase, secreted by bacterial Ideonella Sakaiensis 201-F6, has an excellent hydrolytic activity toward poly(ethylene terephthalate) (PET) at room temperature, while it decreases at higher temperatures due to the low thermostability. Many variants have been engineered to overcome this limitation, which hinders industrial application. In this work, we systematically compare PETase wild-type (WT) and four mutants (DuraPETase, ThermoPETase, FastPETase, and HotPETase) using standard molecular dynamics (MD) simulations and unbinding free energy calculations. In particular, we analyze the enzymes' structural characteristics and binding to a tetrameric PET chain (PET4) under two temperature conditions: T1─300 K and T2─350 K. Our results indicate that (i) PET4 forms stable complexes with the five enzymes at room temperature (∼300 K) and (ii) most of the interactions are localized close to the active site of the protein, where the W185 and Y87 residues interact with the aromatic rings of the substrate. Specifically, (iii) the W185 side-chain explores different conformations in each variant (a phenomenon known in the literature as "W185 wobbling"). This suggests that the binding pocket retains structural plasticity and flexibility among the variants, facilitating substrate recognition and localization events at moderate temperatures. Moreover, (iv) PET4 establishes aromatic interactions with the catalytic H237 residue, stabilizing the catalytic triad composed of residues S160-H237-D206, and helping the system achieve an effective configuration for the hydrolysis reaction. Conversely, (v) the binding affinity decreases at a higher temperature (∼350 K), retaining moderate interactions only for HotPETase. Finally, (vi) MD simulations of complexes formed with poly(ethylene-2,5-furan dicarboxylate) (PEF) show no persistent interactions, suggesting that these enzymes are not yet optimized for binding this alternative semiaromatic plastic polymer. Our study offers valuable insights into the structural stability of these enzymes and the molecular determinants driving PET binding onto their surfaces, sheds light on the mechanistic steps that precede the onset of hydrolysis, and provides a foundation for future enzyme optimization.

A Coarse-Grained Molecular Dynamics Perspective on the Release of 5-Fluorouracil from Liposomes

Liposomes, small bilayer phospholipid-containing vesicles, are frequently used to ensure slow drug release for a prolonged and improved therapeutic effect. Nevertheless, current findings on the membrane affinity and permeability of the anticancer agent 5-fluorouracil (5-FU) are confounding, which leads to a lack of a clear understanding of how lipid composition impacts the distribution of 5-FU within liposomal structures and its delivery. In the current work, we report a comprehensive coarse-grained molecular dynamics (CGMD) investigation on the influence of cholesterol (CHOL) and the cationic lipid 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) on the partitioning of 5-FU in 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) double-bilayer systems, as well as its in vitro release from liposomes with identical lipid compositions. Our results show that 5-FU tends to accumulate at the water-lipid interface, in the vicinity of polar headgroups, without partitioning in the hydrophobic tail region. At the same time, the presence of CHOL proportionally increases the distribution of this drug in the interbilayer aqueous space, decreasing the drug's affinity toward the membrane polar head region, while DOTAP has only a slight effect on drug distribution. Thus, it is expected that 5-FU will be released slower from CHOL-containing DPPC liposomes but not DOTAP-containing vesicles. However, in vitro release studies showed that the release kinetics of 5-FU from DPPC vesicles is not influenced by the presence of CHOL and that the incorporation of 10 mol % DOTAP leads to the best release profile for 5-FU, highlighting the complexity of nanocarrier drug release kinetics. We hypothesize that the initial rapid release seen in dialysis experiments is not related to drug membrane permeability but rather to 5-FU adsorbed on the outer surface of liposomes.

A multi-scale framework for predicting α-cyclodextrin assembly on polyethylene glycol axles

Controlling the distribution of rings on polymer axles, such as α-cyclodextrin (αCD) on polyethylene glycol (PEG), is paramount in imparting robust mechanical properties to slide-ring gels and polyrotaxane-based networks. Previous experiments demonstrated that the functionalization of polymer ends could modulate the coverage of αCDs on PEG. To explore the design rule, we propose a multi-scale framework for predicting αCD assembly on bare and functionalized PEG. Our approach combines all-atom molecular dynamics with two-dimensional (2D) umbrella sampling to compute the free energy landscapes of threading αCDs onto PEG with ends functionalized by various moieties. Together with the predicted free energy landscapes and a lattice treatment for αCD and polymer diffusion in dilute solutions, we construct a kinetic Monte Carlo (kMC) model to predict the number and intra-chain distribution of αCDs along the polymer axle. Our model predicts the effects of chain length, concentration, and threading barrier on the supramolecular structure of end-functionalized polypseudorotaxane. With simple modifications, our approach can be extended to explore the design rule of polyrotaxane-based materials with advanced network architectures.

Superimposing Ligands with a Ligand Overlay as an Alternate Topology Model for λ-Dynamics-Based Calculations

Alchemical free energy (AFE) calculations can predict binding affinity changes as a function of structural modifications and have become powerful tools for lead optimization and drug discovery. Central to the setup and performance of AFE calculations is the manner of mapping alchemical transformations, known as the topology model. Single, dual, and hybrid topology models have been used with various AFE methods in the field. In recent works, λ-dynamics (λD) free energy calculations, specifically, have preferred the use of a hybrid multiple topology (HMT) for sampling multiple ligand perturbations. In this work, we evaluate a new topology method called ligand overlay (LO) for use with λD-based calculations, including the recently introduced λ-dynamics with a bias-updated Gibbs sampling (LaDyBUGS) approach. LO is a full multiple topology model that allows entire ligands to be sampled and restrained within a λ-dynamics framework. Relative binding free energies were computed with HMT or LO topology models with LaDyBUGS for 45 ligands across five protein benchmark systems. An overall Pearson R correlation of 0.98 and mean unsigned error of 0.32 kcal/mol were observed, suggesting that LO is a viable alternative topology model for λD-based calculations. We discuss the merits of using an HMT or LO model for future ligand studies with λD or LaDyBUGS calculations.

Membrane fusion by dengue virus: The first step

Flaviviruses include important human pathogens such as Dengue, Zika, West Nile, Yellow fever, Japanese encephalitis, and Tick-borne encephalitis viruses as well as some emerging viruses that affect millions of people worldwide. They fuse their membrane with the late endosomal one in a pH-dependent way and therefore the merging of the membranes is one of the main goals for obtaining new antivirals. The envelope E protein, a membrane fusion protein, is accountable for fusion and encompasses different domains involved in the fusion mechanism, including the fusion peptide segment. In this work we have used molecular dynamics to study the interaction of the distal end of domain II of the DENV envelope E protein with a membrane like the late endosomal membrane in order to observe the initiation of membrane fusion carried out by a number of trimers of the DENV envelope E protein interacting with a complex biomembrane and demonstrate its feasibility. Our results demonstrate the likelihood of membrane disorganization and pore formation by trimer complex organization, the amino acids responsible for such condition and the secondary structure arrangements needed for such fundamental process. At the same time, we define new targets of the envelope E protein sequence which could permit designing potent antiviral bioactive molecules.

Enhancement of atmospheric nucleation precursors on formic sulfuric anhydride induced nucleation: Theoretical mechanism

As an intermediate formed by H2SO4 (SA), formic sulfate anhydride (FSA) has been hypothesized to play a role in the nucleation of atmospheric aerosols. It is the first time that the clusters (SA)x(A)y(W)n and (FSA)x(A)y(W)n (x = 1-2; y = 1-2; n = 0-4) were systematically studied in theory on the structures, thermodynamics, intermolecular interactions, humidity dependence, atmospheric dependence and optical properties. FSA is predicted to be more stronger to promote the clustering with ammonia (A) than SA, suggesting that substituent group enhances nucleation capability of FSA. Whereas, the substituent group does not influence the humidity sensitivity of hydrated clusters. The clusters trend to form small hydrated clusters (nwater≦3). The study on atmospheric dependence indicates that the stability of the clusters depends more on temperature other than pressure. Moreover, FSA shows a stronger ability on reducing atmospheric visibility than A, SA and water molecules. This finding aims to draw attention to FSA about atmospheric nucleation.

Microscopic Structure of Neat Linear Alkylamine Liquids: An X-Ray Scattering and Computer Simulation Study

Linear amines, from propylamine to nonylamine, are studied under ambient conditions by X-ray scattering and molecular dynamics simulations of various force field models. The major finding is that the prepeak in alkylamines is about 1 order of magnitude weaker than that in alkanols, hence suggesting much weaker hydrogen bonding-induced clustering of the amine groups than for the hydroxyl groups. Computer simulation studies reveal that the OPLS-UA model reproduces the prepeak, but with larger amplitudes, while the GROMOS-UA and CHARMM-AA force fields show almost no prepeak. Simulations of all models show the existence of hydrogen-bonded clusters, equally confirmed by the prominent prepeak of the structure factor between the nitrogen atoms. The hydrogen bond strength, as modeled by the Coulomb association in classical force field models, is about the same order of magnitude for both systems. Then, one may ask what is the origin of the weaker prepeak in alkylamines? Simulation data reveal that the existence of the prepeak is controlled through the cancellation of the positive contributions from the charged group correlations by the negative contributions from the cross charged-uncharged correlations. The C2v symmetry of the amine headgroup hinders clustering, which favors cross correlations with the tail atoms. This is opposite to alkanols where the symmetry of the hydroxyl headgroup favors clustering and hinders cross correlations with the alkyl tail. This competition between charged and uncharged atomic groups appears as a general mechanism to explain the existence of scattering prepeaks, including their position and amplitude.

Accuracy and Reproducibility of Lipari-Szabo Order Parameters From Molecular Dynamics

The Lipari-Szabo generalized order parameter probes the picosecond to nanosecond time scale motions of a protein and is useful for rationalizing a multitude of biological processes such as protein recognition and ligand binding. Although these fast motions are an important and intrinsic property of proteins, it remains unclear what simulation conditions are most suitable to reproduce methyl symmetry axis side chain order parameter data (Saxis2) from molecular dynamics simulations. In this study, we show that, while Saxis2 tends to converge within tens of nanoseconds, it is essential to run 10 to 20 replicas starting from configurations close to the experimental structure to obtain the best agreement with experimental Saxis2 values. Additionally, in a comparison of force fields, AMBER ff14SB outperforms CHARMM36m in accurately capturing these fast time scale motions, and we suggest that the origin of this performance gap is likely attributed to differences in side chain torsional parametrization and not due to differences in the global protein conformations sampled by the force fields. This study provides insight into obtaining accurate and reproducible Saxis2 values from molecular simulations and underscores the necessity of using replica simulations to compute equilibrium properties.

Force Fields for Deep Eutectic Mixtures: Application to Structure, Thermodynamics and 2D-Infrared Spectroscopy

Parametrizing energy functions for ionic systems can be challenging. Here, the total energy function for an eutectic system consisting of water, SCN-, K+ and acetamide is improved vis-a-vis experimentally measured properties. Given the importance of electrostatic interactions, two different types of models are considered: the first (model M0) uses atom-centered multipole whereas the other two (models M1 and M2) are based on fluctuating minimal distributed charges (fMDCM) that respond to geometrical changes of SCN-. The Lennard-Jones parameters of the anion are adjusted to best reproduce experimentally known hydration free energies and densities, which are matched to within a few percent for the final models irrespective of the electrostatic model. Molecular dynamics simulations of the eutectic mixtures with varying water content (between 0 and 100%) yield radial distribution functions and frequency correlation functions for the CN-stretch vibration. Comparison with experiments indicates that models based on fMDCM are considerably more consistent than those using multipoles. Computed viscosities from models M1 and M2 are within 30% of measured values and their change with increasing water content is consistent with experiments. This is not the case for model M0.

Predicting the Antifungal Activity of Small Organic Compounds on Aspergillus niger Mold using Molecular Dynamics Simulations

Atomistic models of the plasma membrane of the pathogenic mold Aspergillus niger are developed. These models are described with an empirical molecular mechanical (MM) force field in combination with molecular dynamics (MD) simulations. The solvated plasma membrane models are brought into contact with 35 small organic compounds to observe their impact on a variety of membrane properties. All compounds are added at a constant total mass of 1% of the membrane mass. In addition, the ability of these compounds to inhibit the pathogenic cell growth of mold has been measured. Diffusion of compounds into the membrane model is readily observed during MD simulations. Changes in membrane properties found in simulations are not found to correlate with measured antifungal activities of compounds, suggesting that MD simulations of up to 1 μs are not sufficiently long to adequately describe compound-induced membrane disruption. However, properties related to the position and orientation of compounds relative to the membrane surface as well as hydrogen bonds formed between the compounds and the membrane show clear trends that correlate well with measured activities. A combination of these properties enables an activity prediction of compounds in good agreement with measurements. Activity is found predominantly for compounds that can be decomposed into a single continuous hydrophobic and hydrophilic moiety. Such active compounds can be energetically inserted most favorably into the membrane. These insertions destabilize the membrane by disrupting the internal membrane hydrogen bond network and by sliding between neighboring lipids, thereby separating them.

Computational design and evaluation of a polyvalent vaccine for viral nervous necrosis (VNN) in fish to combat Betanodavirus infection

Viral nervous necrosis (VNN) poses a significant threat to the aquaculture industry, causing substantial losses and economic burdens. The disease, attributed to nervous necrosis viruses within the Betanodavirus genus, is particularly pervasive in the Mediterranean region, affecting various fish species across all production stages with mortality rates reaching 100%. Developing effective preventive measures against VNN is imperative. In this study, we employed rigorous immunoinformatics techniques to design a novel multi-epitope vaccine targeting VNN. Five RNA-directed RNA polymerases, crucial to the lifecycle of Betanodavirus, were selected as vaccine targets. The antigenicity and favorable physicochemical properties of these proteins were confirmed, and epitope mapping identified cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte epitopes essential for eliciting a robust immune response. The selected epitopes, characterized by high antigenicity, non-allergenicity, and non-toxicity, were further enhanced by adding PADRE sequences and hBD adjuvants to increase immunogenicity. Two vaccine constructs were developed by linking epitopes using appropriate linkers, demonstrating high antigenicity, solubility, and stability. Molecular dynamics simulations revealed stable interactions between the vaccine constructs and Toll-like receptors (TLRs), essential for pathogen recognition and immune response activation in fish. Notably, vaccine construct V2 exhibited superior stability and binding affinity with TLR8, suggesting its potential as a promising candidate for VNN prevention. Overall, our study presents a comprehensive approach to VNN vaccine design utilizing immunoinformatics, offering safe, immunogenic, and effective solutions across multiple Betanodavirus species. Further experimental validation in model animals is recommended to fully assess the vaccine's efficacy. This research contributes to improved vaccine development against diverse fish pathogens by addressing emerging challenges and individualized immunization requirements in aquaculture.

Disruption of PHF6 Peptide Aggregation from Tau Protein: Mechanisms of Palmatine Chloride in Preventing Early PHF6 Aggregation

The formation of neurofibrillary tangles (NFTs), composed of tau protein aggregates, is a hallmark of neurodegenerative diseases known as tauopathies, including Alzheimer's disease (AD). NFTs consist of paired helical filaments (PHFs) of tau protein with a dominant β-sheet secondary structure. Within these PHFs, the PHF6 hexapeptide (Val306-Gln-Ile-Val-Tyr-Lys311) has been commonly highlighted as a key site for tau protein nucleation. Palmatine chloride (PC) has been identified as an inhibitor of PHF6 aggregation, capable of reducing aggregation propensity at submicromolar concentrations. In pursuit of novel anti-AD drugs targeting early tau aggregation stages, we conducted an in silico study to elucidate PC's mechanism of action during PHF6 aggregation. Our observations suggest that while PHF6 can still initiate self-aggregation in the presence of PC, PC molecules subtly influence PHF6 aggregation dynamics, favoring smaller aggregates over larger complexes. The study underlined the key roles of aromatic rings in PC binding to different PHF6 aggregates by interacting through π-π stacking with the PHF6 Tyr310 side chain. The presence of aromatic rings in compounds to be able to inhibit the earlier complexation phase seems to be essential. These in silico findings lay a foundation for the design of compounds that could intervene in resolving the neurotoxicity of protein aggregates in AD.

Indole-core inhibitors of influenza a neuraminidase: iterative medicinal chemistry and molecular modeling

Influenza viruses that cause seasonal and pandemic flu are a permanent health threat. The surface glycoprotein, neuraminidase, is crucial for the infectivity of the virus and therefore an attractive target for flu drug discovery campaigns. We have designed and synthesized more than 40 3-indolinone derivatives. We mainly investigated the role of substituents at the 2 position of the core as well as the introduction of substituents or a nitrogen atom in the fused phenyl ring of the core for inhibition of influenza virus neuraminidase activity and replication in vitro and in vivo. After evaluating the compounds for their ability to inhibit the viral neuraminidase, six potent inhibitors 3c, 3e, 7c, 12o, 12v, 18d were progressed to evaluate for cytotoxicity and inhibition of influenza virus A/PR/8/34 replication in in MDCK cells. Two hit compounds 3e and 12o were tested in an animal model of influenza virus infection. Molecular mechanism of the 3-indolinone derivatives interactions with the neuraminidase was revealed in molecular dynamic simulations. Proposed inhibitors bind to the 430-cavity that is different from the conventional binding site of commercial compounds. The most promising 3-indolinone inhibitors demonstrate stronger interactions with the neuraminidase in molecular models that supports proposed binding site.

Single-molecule imaging and molecular dynamics simulations reveal early activation of the MET receptor in cells

Embedding of cell-surface receptors into a membrane defines their dynamics but also complicates experimental characterization of their signaling complexes. The hepatocyte growth factor receptor MET is a receptor tyrosine kinase involved in cellular processes such as proliferation, migration, and survival. It is also targeted by the pathogen Listeria monocytogenes, whose invasion protein, internalin B (InlB), binds to MET, forming a signaling dimer that triggers pathogen internalization. Here we use an integrative structural biology approach, combining molecular dynamics simulations and single-molecule Förster resonance energy transfer (smFRET) in cells, to investigate the early stages of MET activation. Our simulations show that InlB binding stabilizes MET in a conformation that promotes dimer formation. smFRET reveals that the in situ dimer structure closely resembles one of two previously published crystal structures, though with key differences. This study refines our understanding of MET activation and provides a methodological framework for studying other plasma membrane receptors.

AI-assisted generation and in-depth in-silico evaluation of potential inhibitor targeting aurora kinase A (AURKA): An anticancer discovery exploiting synthetic lethality approach

Genetic alterations are lead causative agents behind the complex pathologies of cancers which render all treatments unarmed. Such alterations in oncogenes can be treated by direct inhibition by specific drugs while alteration in tumor suppressor genes mediating loss of function is challenging to treat. Identification of synthetic lethal partners to specific tumor suppressor genes and mediating their inhibition can be a potential approach to deal with loss of function mutations. Aurora kinase A (AURKA) has been established as an effective synthetic lethal partner of several tumor suppressor genes and is overexpressed in cancerous conditions, mediating adverse pathologies. The present AI-assisted study deals with the generation of novel inhibitor compounds against AURKA and the exhaustive evaluation of the best compound using molecular docking, molecular dynamic simulation, MM/PBSA, and QM/MMGBSA-based analysis. Out of the 200 novel compounds generated using features of ATP binding pocket of AURKA and previously reported inhibitor, compound 1 (4-{5-fluoro-6-[(1Z)-3-hydrazinyl-3-oxo-2-phenylprop-1-en-1-yl]pyridin-2-yl}benzoic acid) was identified as the most potent candidate with high negative binding energy of -10.4 kcal/mol in molecular docking analysis. The molecular dynamic simulation analysis resulted in major conformational changes in the conserved DFG motif and loop 277-291 of AURKA in the apo-AURKA compared to AURKA-compound 1 complex thus maintaining open ATP binding cavity in apo-form and inhibiting the entry of ATP to its binding site in complex form. The free energy landscape displayed a persistence of folded states of the enzyme in complex form. The MM/PBSA revealed effective Gibb's free energy of binding of -11 kcal/mol for compound 1 inhibiting AURKA. The QM/MMGBSA analysis resulted in a significantly high negative binding energy of -13.98 kcal/mol proving significant inhibition potential of compound 1 against AURKA. Therefore, further in-vitro investigation can provide a novel effective, and safe treatment against a wide range of cancers by targeting a well-established cancer target AURKA.

Apigenin promotes cell death in NCI-H23 cells by upregulation of PTEN: potential involvement of the binding of apigenin with WWP2 protein

The tumour suppressor protein PTEN is often down-regulated in non-small cell lung cancer. A major protein promoting the lowering of the PTEN protein is WWP2. Polyphenols have been shown to promote the expression of tumour suppressor genes like PTEN. We carry out the study to check for the ability of apigenin to bind with the WWP2 protein using in-silico investigation comprising docking and simulation. We checked for the cytotoxic effect of apigenin upon the non-small cell lung cancer cell line NCI-H23. We checked the PTEN expression status at the gene and protein levels. The expression levels of the apoptotic regulators BCL2, BAX and CASPASE3 genes along with the activity levels of the caspase-3 protein were checked. The ultrastructure of the cells was analysed. Our Autodock analysis showed that apigenin bound favourably with the WWP2 protein. Molecular dynamics simulation revealed that apigenin increased the parameters of RMSD, Rg and SASA when bound with the WWP2 protein. The protein-ligand complex had hydrogen bonding and majorly van der Wal's interactions. PCA analysis revealed greater fluctuations in the apigenin-bound state of the protein. The mutant form of the WWP2 revealed similar results in the presence of apigenin. Apigenin showed efficacy against the NCI-H23 cell line and promoted PTEN protein levels, lowered BCL2 gene expression and up-regulated BAX and CASPASE3 gene expression. Increased caspase-3 activity and ultra-structural analysis revealed the occurrence of apoptosis. Thus the binding of apigenin with WWP2 could promote PTEN protein levels and lead to apoptotic activity in NCI-H23 cells.Communicated by Ramaswamy H. Sarma.

Exploring ligands that target von Willebrand factor selectively under oxidizing conditions through docking and molecular dynamics simulations

The blood protein von Willebrand factor (VWF) is a large multimeric protein that, when activated, binds to blood platelets, tethering them to the site of vascular injury and initiating blood coagulation. This process is critical for the normal hemostatic response, but especially under inflammatory conditions, it is thought to be a major player in pathological thrombus formation. For this reason, VWF has been the target for the development of anti-thrombotic therapeutics. However, it is challenging to prevent pathological thrombus formation while still allowing normal physiological blood coagulation, as currently available anti-thrombotic therapeutics are known to cause unwanted bleeding, in particular intracranial hemorrhage. This work explores the possibility of inhibiting VWF selectively under the inflammatory conditions present during pathological thrombus formation. In particular, the A2 domain of VWF is known to inhibit the neighboring A1 domain from binding to the platelet surface receptor GpIbα, and this auto-inhibitory mechanism has been shown to be removed by oxidizing agents released during inflammation. Hence, finding drug molecules that bind at the interface between A1 and A2 only under oxidizing conditions could restore such an auto-inhibitory mechanism. Here, by using a combination of computational docking, molecular dynamics simulations, and free energy perturbation calculations, a ligand from the ZINC15 database was identified that binds at the A1A2 interface, with the interaction being stronger under oxidizing conditions. The results provide a framework for the discovery of drug molecules that bind to a protein selectively in the presence of inflammatory conditions.

Pathogenic G6PD variants: Different clinical pictures arise from different missense mutations in the same codon

G6PD deficiency results from mutations in the X-linked G6PD gene. More than 200 variants are associated with enzyme deficiency: each one of them may either cause predisposition to haemolytic anaemia triggered by exogenous agents (class B variants), or may cause a chronic haemolytic disorder (class A variants). Genotype-phenotype correlations are subtle. We report a rare G6PD variant, discovered in a baby presenting with severe jaundice and haemolytic anaemia since birth: the mutation of this class A variant was found to be p.(Arg454Pro). Two variants affecting the same codon were already known: G6PD Union, p.(Arg454Cys), and G6PD Andalus, p.(Arg454His). Both these class B variants and our class A variant exhibit severe G6PD deficiency. By molecular dynamics simulations, we performed a comparative analysis of the three mutants and of the wild-type G6PD. We found that the tetrameric structure of the enzyme is not perturbed in any of the variants; instead, loss of the positively charged Arg residue causes marked variant-specific rearrangement of hydrogen bonds, and it influences interactions with the substrates G6P and NADP. These findings explain severe deficiency of enzyme activity and may account for p.(Arg454Pro) expressing a more severe clinical phenotype.

Engineered odorant receptors illuminate the basis of odour discrimination

How the olfactory system detects and distinguishes odorants with diverse physicochemical properties and molecular configurations remains poorly understood. Vertebrate animals perceive odours through G protein-coupled odorant receptors (ORs)1. In humans, around 400 ORs enable the sense of smell. The OR family comprises two main classes: class I ORs are tuned to carboxylic acids whereas class II ORs, which represent most of the human repertoire, respond to a wide variety of odorants2. A fundamental challenge in understanding olfaction is the inability to visualize odorant binding to ORs. Here we uncover molecular properties of odorant-OR interactions by using engineered ORs crafted using a consensus protein design strategy3. Because such consensus ORs (consORs) are derived from the 17 major subfamilies of human ORs, they provide a template for modelling individual native ORs with high sequence and structural homology. The biochemical tractability of consORs enabled the determination of four cryogenic electron microscopy structures of distinct consORs with specific ligand recognition properties. The structure of a class I consOR, consOR51, showed high structural similarity to the native human receptor OR51E2 and generated a homology model of a related member of the human OR51 family with high predictive power. Structures of three class II consORs revealed distinct modes of odorant-binding and activation mechanisms between class I and class II ORs. Thus, the structures of consORs lay the groundwork for understanding molecular recognition of odorants by the OR superfamily.