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

An in-silico approach to identify bioactive phytochemicals from Houttuynia cordata Thunb. As potential inhibitors of human glutathione reductase

Cellular infections are central to the etiology of various diseases, notably cancer and malaria. Counteracting cellular oxidative stress via the inhibition of glutathione reductase (GR) has emerged as a promising therapeutic strategy. Houttuynia cordata, a medicinal plant known for its potent antioxidant properties, has been the focus of our investigation. In this study, we conducted comprehensive in silico analyses involving the phytochemical constituents of H. cordata to identify potential natural GR inhibitors. Our methodological approach encompassed multiple in silico techniques, including molecular docking, molecular dynamics simulations, MMPBSA analysis, and dynamic cross-correlation analysis. Out of 13 docked phytochemicals, Quercetin, Quercitrin, and Sesamin emerged as particularly noteworthy due to their exceptional binding affinities for GR. Notably, our investigation demonstrated that Quercetin and Sesamin exhibited promising outcomes compared to the well-established pharmaceutical agent N-acetylcysteine (NAC). Molecular dynamics analyses provided insights into the ability of these phytochemicals to induce structural compaction and stabilization of the GR protein, as evidenced by changes in radius of gyration and solvent-accessible surface area. Moreover, MMPBSA analysis highlighted the crucial roles of specific residues, namely Gly27, Gly28, Ser51, His52, and Val61, in mediating essential interactions with these phytochemicals. Furthermore, an assessment of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADME-Tox) profiles underscored the favourable drug-like attributes of these phytochemicals. Thus, the current findings underscore the immense potential of Houttuynia cordata phytochemicals as potent antioxidants with the capacity to combat a spectrum of maladies, including malaria and cancer. This study not only unveils novel therapeutic avenues but also underscores the distinctive outcomes and paramount significance of harnessing H. cordata phytochemicals for their efficacious antioxidant properties.

Hydropathic AF-2 variants in the androgen receptor gene among androgen insensitivity patients

BACKGROUND

Androgen insensitivity syndrome (AIS) is a common condition among individuals with differences of sexual development (DSD) and results from germline allelic variants in the androgen receptor (AR) gene. Understanding the phenotypic consequences of AR allelic variants that disrupt the activation function 2 (AF2) region is essential to grasping its clinical significance.

OBJECTIVES

This study aims to provide insights into the phenotypic characteristics and clinical impact of AR mutations affecting the AF2 region in AIS patients. We achieve this by reviewing reported AR variants in the AF2 region among individuals with AIS, including identifying a new phenotype associated with the c.2138T>C variant (p.Leu713Pro) in the AR gene.

MATERIALS AND METHODS

We comprehensively reviewed AR variants within the AF2 region reported in AIS and applied molecular dynamics simulations to assess the impact of the p.Leu713Pro variant on protein dynamics.

RESULTS

Our review of reported AR variants in the AF2 region revealed a spectrum of phenotypic outcomes in AIS patients. Molecular dynamics simulations indicated that the p.Leu713Pro variant significantly alters the local dynamics of the AR protein and disrupts the correlation and covariance between variables.

DISCUSSION

The diverse phenotypic presentations observed among individuals with AR variants in the AF2 region highlight the complexity of AIS. The altered protein dynamics resulting from the p.Leu713Pro variant further emphasize the importance of the AF2 region in AR function.

CONCLUSION

Our study provides valuable insights into AR mutations' phenotypic characteristics and clinical impact on the AF2 region in AIS. Moreover, the disruption of protein dynamics underscores the significance of the AF2 region in AR function and its role in the pathogenesis of AIS.

Unraveling atomic-scale mechanisms of GDP extraction catalyzed by SOS1 in KRAS-G12 and KRAS-D12 oncogenes

The guanine exchange factor SOS1 plays a pivotal role in the positive feedback regulation of the KRAS signaling pathway. Recently, the regulation of KRAS-SOS1 interactions and KRAS downstream effector proteins has emerged as a key focus in the development of therapies targeting KRAS-driven cancers. However, the detailed dynamic mechanisms underlying SOS1-catalyzed GDP extraction and the impact of KRAS mutations remain largely unexplored. In this study, we unveil and describe in atomic detail the primary mechanisms by which SOS1 facilitates GDP extraction from KRAS oncogenes. For GDP-bound wild-type KRAS (KRAS-G12), four critical amino acids (Lys811, Glu812, Lys939, and Glu942) are identified as essential for the catalytic function of SOS1. Notably, the KRAS-G12D mutation (KRAS-D12) significantly accelerates the rate of GDP extraction. The molecular basis of this enhancement are attributed to hydrogen bonding interactions between the mutant residue Asp12 and a positively charged pocket in the intrinsically disordered region (residues 807-818), comprising Ser807, Trp809, Thr810, and Lys811. These findings provide novel insights into SOS1-KRAS interactions and offer a foundation for developing anti-cancer strategies aimed at disrupting these mechanisms.

Akkiraju P, Dokuparthi SK, Hussain S, Enaganti S. Molecular dynamics simulation analysis of a modelled spermidine synthase from Yersinia pseudotuberculosis docked with cyclohexylamine

The gram-negative bacterium Yersinia pestis is the causative agent of plague 1 and has been responsible for major pandemics in the past. Therefore, it is of interest to document the molecular docking and simulation analysis of spermidine synthase from Yersinia pseudotuberculosis with cyclohexylamine. The sequence and structure analysis showed an abundance of Leu, Val, Gly, Glu and Ala, the least presence of Trp and Cys, higher negatively charged residues and a GRAVY score of -0.125, suggesting the stability of the protein. The cyclohexylamine conformer 4-fluorocyclohexan-1-amine (CID 21027526) showed optimal binding features (-4.7 kcal/mol). Moreover, molecular dynamics simulation confirmed the stability of the ligand binding pocket for further validation and consideration in drug design and development.

Large scale investigation of GPCR molecular dynamics data uncovers allosteric sites and lateral gateways

G protein-coupled receptors (GPCRs) constitute a functionally diverse protein family and are targets for a broad spectrum of pharmaceuticals. Technological progress in X-ray crystallography and cryogenic electron microscopy has enabled extensive, high-resolution structural characterisation of GPCRs in different conformational states. However, as highly dynamic events underlie GPCR signalling, a complete understanding of GPCR functionality requires insights into their conformational dynamics. Here, we present a large dataset of molecular dynamics simulations covering 60% of currently available GPCR structures. Our analysis reveals extensive local "breathing" motions of the receptor on a nano- to microsecond timescale and provides access to numerous previously unexplored receptor conformational states. Furthermore, we reveal that receptor flexibility impacts the shape of allosteric drug binding sites, which frequently adopt partially or completely closed states in the absence of a molecular modulator. We demonstrate that exploring membrane lipid dynamics and their interaction with GPCRs is an efficient approach to expose such hidden allosteric sites and even lateral ligand entrance gateways. The obtained insights and generated dataset on conformations, allosteric sites and lateral entrance gates in GPCRs allows us to better understand the functionality of these receptors and opens new therapeutic avenues for drug-targeting strategies.

Size-Dependent, Topology-Regulated, pH-Change-Tolerable, and Reversible Self-Assembly of Ultrasmall Nanoparticles

The multiscale ordering of colloidal nanoparticles (NPs) endows materials with diverse functions and performances. The controllable and predictable assembly of NPs is essential for the new generation of materials science. This study presents a topology-regulated self-assembly approach in an aqueous environment, utilizing polysorbate 20 (Tween-20) and ultrasmall gold nanoparticles (2, 4, and 8 nm AuNPs). The self-assembly process was governed by polyvalent hydrogen bonding interactions between the amphiphilic Tween-20 and tiopronin-capped NPs, with the amphipathic nature of Tween-20 primarily dictating the transformation from 1D to 3D structures. Notably, the NP size influences the assembly process, with the 2 nm particles demonstrating a well-regulated, pH-stable, and reversible assembly capability. Our findings provide a straightforward approach for controlling the assembly of simple nanoparticles and molecules into higher dimensional nano/microstructures, and close the knowledge gap in how NP size affects interactions within the assembly dynamics.

The effect of cysteine oxidation on conformational changes of SARS-CoV-2 spike protein using atomistic simulations

The SARS-CoV-2 Spike (S) protein plays a central role in viral entry into host cells, making it a key target for therapeutic interventions. Oxidative stress, often triggered during viral infections, can cause oxidation of cysteine in this protein. Here we investigate the impact of cysteine oxidation, specifically the formation of cysteic acid, on the conformational dynamics of the SARS-CoV-2 S protein using atomistic simulations. In particular, we examine how cysteine oxidation influences the transitions of the S protein's receptor-binding domain (RBD) between "down" (inaccessible) and "up" (accessible) states, which are critical for host cell receptor engagement. Using solvent-accessible surface area (SASA) analysis, we identify key cysteine residues susceptible to oxidation. The results of targeted molecular dynamics (TMD) and umbrella sampling (US) simulations reveal that oxidation reduces the energy barrier for RBD transitions by approximately 30 kJ mol-1, facilitating conformational changes and potentially enhancing viral infectivity. Furthermore, we analyze the interactions between oxidized cysteine residues and glycans, as well as alterations in hydrogen bonds and salt bridges. Our results show that oxidation disrupts normal RBD dynamics, influencing the energy landscape of conformational transitions. Our work provides novel insights into the role of cysteine oxidation in modulating the structural dynamics of the SARS-CoV-2 S protein, highlighting potential targets for antiviral strategies aimed at reducing oxidative stress or modifying post-translational changes. These findings contribute to a deeper understanding of viral infectivity and pathogenesis under oxidative conditions.

Molecular mechanism of type ib MET inhibitors and their potential for CNS tumors

The emergence of targeted therapies for MET exon 14 (METex14) skipping mutations has significantly changed the treatment landscape for NSCLC and other solid tumors. The skipping of METex14 results in activating the MET-HGF pathway and promoting tumor cell proliferation, migration, and preventing apoptosis. Type Ib MET inhibitors, designed to selectively target the "DFG-in" conformation of MET, characteristically bind to the ATP-binding pocket of MET in a U-shaped conformation, extending into the solvent-accessible region and interact strongly with residue Y1230 through π-π interactions, have shown remarkable efficacy in treating METex14-altered NSCLC, including cases with brain metastases (BMs). Notably, vebreltinib and capmatinib have demonstrated superior blood-brain barrier (BBB) permeability in both computational and experimental models, highlighting their potential for treating the central nervous system (CNS) metastases. P-glycoprotein (P-gp) is highly expressed in the BBB, which limits the brain uptake of many highly lipophilic drugs. Despite challenges posed by P-gp mediated efflux, vebreltinib has emerged as a promising candidate for CNS treatment due to its favorable pharmacokinetic profile and minimal susceptibility to P-gp efflux. This study underscores the importance of molecular dynamics simulations in predicting drug efficacy and BBB penetration, providing valuable insights for the development of CNS-targeted metastases therapies.

Long-Chain Cyclic Arylguanidines as Multifunctional Serotonin Receptor Ligands with Antiproliferative Activity

Recent investigations have shown serotonin's stimulatory effect on several types of cancers and carcinoid tumors. Nowadays there has been a significant increase in interest in 5-HT7 and 5-HT5A receptors in the context of cancer treatment. The possible role of 5-HT6R in the pathogenesis and progression of glioma remains an interesting and relatively unexplored issue. We developed a new group of long-chain 2-aminoquinazoline sulfonamides as new multifunctional serotonin receptor ligands, focused on 5-HT6R. The chosen group was further evaluated for antiproliferative effects on 1321N1 astrocytoma cells, along with U87MG, U-251, and LN-229 glioblastoma cell lines. Certain compounds were subjected to in vitro absorption, distribution, metabolism, excretion, and toxicity (ADMET) testing, for assessing factors such as lipophilicity, plasma protein binding, phospholipid affinity, potential for drug-drug interactions (DDI), membrane permeability (PAMPA), metabolic stability, and hepatotoxicity. Additionally, in vivo testing was performed using the Danio rerio model. The developed group includes the selective 5-HT6R antagonist PP 15, dual ligand for 5-HT1AR/5-HT6R PP 13, and dual ligand for 5-HT5AR/5-HT6R PP 10. The use of multifunctional ligands was associated with high anticancer activity both against selected glioma cell lines and other cancers (IC50 < 25 μM).

Toward Computation-Guided Design of Tunable Organic-Inorganic CdS Quantum Dot Binary Superlattices

Combining the advantages of structural programmability in sequence-defined biomimetic molecules and the controllable packing geometry in nanoparticle superlattices, we demonstrate a self-assembled organic-inorganic superlattice whose structure can be altered with the slightest change in the sequence of the organic counterpart. Here, oleate-coated CdS quantum dots (QDs) form a square-packed superlattice with a 1:1 molar equivalence of a diblock amphiphilic peptoid (Nbrpe6Dig) in chloroform. In contrast, no apparent structure is observed in the organic solvent alone. Based on theoretical evidence, we show that the assembly is a binary superlattice where both the CdS QDs and the peptoids serve as building blocks and further predict a correlation between the superlattice structure and the peptoid sequence. The computationally guided prediction is validated by experiments where superlattice transformation is observed with modified peptoids. The mechanism identified in our work inspires new ways to control and tune organic-inorganic hybrid nanomaterial self-assembly.

CHARMM-GUI EnzyDocker for Protein-Ligand Docking of Multiple Reactive States along a Reaction Coordinate in Enzymes

Enzymes play crucial roles in all biological systems by catalyzing a myriad of chemical reactions. These reactions range from simple one-step processes to intricate multistep cascades. Predicting mechanistically appropriate binding modes along a reaction pathway for substrate, product, and all reaction intermediates and transition states is a daunting task. To address this challenge, special docking programs like EnzyDock have been developed. Yet, running such docking simulations is complicated due to the nature of multistep enzyme processes. This work presents CHARMM-GUI EnzyDocker, a web-based cyberinfrastructure designed to streamline the preparation and running of EnzyDock docking simulations. The development of EnzyDocker has been achieved through integration of existing CHARMM-GUI modules, such as PDB Reader and Manipulator, Ligand Designer, and QM/MM Interfacer. In addition, new functionalities have been developed to facilitate a one-stop preparation of multistate and multiscale docking systems and enable interactive and intuitive ligand modifications and flexible protein residues selections. A simple setup related to multiligand docking is automatized through intuitive user interfaces. EnzyDocker offers support for standard classical docking and QM/MM docking with CHARMM built-in semiempirical engines. Automated consensus restraints for incorporating experimental knowledge into the docking are facilitated via a maximum common substructure algorithm. To illustrate the robustness of EnzyDocker, we conducted docking simulations of three enzyme systems: dihydrofolate reductase, SARS-CoV-2 Mpro, and the diterpene synthase CotB2. In addition, we have created four tutorial videos about these systems, which can be found at https://www.charmm-gui.org/demo/enzydock. EnzyDocker is expected to be a valuable and accessible web-based tool that simplifies and accelerates the setup process for multistate docking for enzymes.

Computer-aided drug repurposing & discovery for Hepatitis B capsid protein

The primary objective of this study is to harness computer-aided drug repurposing (CADR) techniques to identify existing FDA-approved drugs that can potentially disrupt the assembly of the Hepatitis B Virus (HBV) core protein (HBcAg), an essential process in the virus's life cycle. By targeting this critical step, our study aims to expand the repertoire of therapeutic options for managing chronic Hepatitis B infection, a major global health challenge. Utilizing a combination of computational methods, including the CavityPlus server for ability to analyze druggable protein cavities and extract pharmacophore features and LigandScout for pharmacophore-based virtual screening of a vast library of FDA-approved drugs was conducted. Molecular dynamic simulation (MDS) was employed to evaluate the stability of HBcAg, complexed with Heteroaryldihydropyrimidine (HAP) and statins exhibiting particularly strong binding energies and conformational compatibility. Our approach focused on identifying pharmacophore features that align with known HBcAg inhibitors. The study identified several promising candidates, including Ciclopirox olamine, Voriconazole, Enasidenib, and statins, demonstrating potential interactions with HBc protein residues. Molecular docking further validated these interactions. The significance of these findings lies in their potential to offer new, effective therapeutic strategies for HBV treatment, particularly as alternatives to current therapies that often suffer from issues of viral resistance and adverse side effects. MDS analysis verified the robustness of HAP and statins by showing a high level of binding energies and compatibility with HBcAg. Our results provide a foundation for further experimental validation and underscore the utility of computer-aided drug repurposing as a rapid, cost-effective approach to drug discovery in antiviral research. This study contributes to our understanding of HBV biology and opens avenues for developing novel anti-HBV therapies based on repurposed drugs. The highlighted compound may also enhance the challenges of drug resistance when used as a combination therapy.

Molecular Details of Polyester Decrystallization via Molecular Simulation

Waste polyesters are a potential feedstock for recycled and upcycled products. These polymers are generally semicrystalline, which presents a challenge for chemical and biological recycling to monomers, and thus the thermodynamic work associated with polyester decrystallization is an important consideration in some depolymerization strategies. Here, we use molecular dynamics simulations to calculate the free energy required to decrystallize a single chain from the crystal surface of five commercially and scientifically important, semiaromatic polyesters (PET, PTT, PBT, PEN, and PEF) in water. Our results indicate the decrystallization work ranges from approximately 15 kcal/mol (PEN) to 8 kcal/mol (PEF) per repeat unit for chains in the middle of a crystal surface. The insight gained into the molecular interactions that form the structural basis of semicrystalline synthetic polyesters can guide the pursuit of more efficient plastic processing, which could include catalyst development, optimizing recycling conditions including pretreatment, enzyme and solvent selections, and design of new materials.

Flexibility-Induced Collective Behavior Drives Symmetry Breaking in Discrimination of Undesired Ions

Structure flexibility is essential for the biological function of proteins. At the same time, many proteins need to discriminate ligands with subtle differences, with one example being ion selectivity. Investigating the mechanisms by which flexible proteins achieve such precise discrimination is crucial for advancing our understanding of their functions. In this work, we study transporter KCC4, which undergoes continuous conformation changes during ion transport and can realize K+ over Na+ selectivity. Our findings reveal that the center of the binding site no longer represents a stable equilibrium for the undesired Na+, and its binding mode exhibits bifurcation. Interestingly, protein conformation fluctuation can induce collective behavior throughout the entire binding region, which contributes to this bifurcation. Thus, the symmetry of the binding mode decreases from the inherent T d symmetry to a C2v symmetry, and the binding stability of Na+ is largely reduced. A similar phenomenon is observed in a GPCR, β2-AR, where a less favored ligand forms a biased binding mode with reduced stability. The mechanism underlying the selectivity in such flexible regions could be interpreted as spontaneous symmetry breaking, which may represent a general mechanism by which flexible proteins achieve efficient ligand discrimination.

Exploring the role of quercetin on doxorubicin and lapatinib-mediated cellular and mitochondrial responses using in vitro and in silico studies

Doxorubicin (DOX) and lapatinib (LAP) have been reported to cause liver toxicity. The roles of mitochondrial and cellular responses in DOX and LAP mediated-hepatotoxicity have not been investigated with or without quercetin (QUE) in HepG2 cells sensitive to mitochondrial damage (high-glucose or galactose media) in addition to in silico studies. Our results revealed that cytosolic pathways might play role a in DOX-induced cytotoxicity rather than mitochondria. QUE exacerbated DOX-induced ATP depletion in both environments. Our data also indicated that cytosolic and mitochondrial pathways might play a role in LAP-induced cytotoxicity. Incubating QUE with LAP increased ATP levels in high-glucose media. Therefore, QUE might have protective effect against LAP-induced cytotoxicity resulting from cytosolic pathways. The findings from in vitro experiments that QUE increased DOX or LAP-induced mitochondrial dysfunction were confirmed by the results from in silico studies indicating that QUE incubated with LAP or DOX might increase mitochondrial dysfunction.

Molecular simulations reveal intricate coupling between agonist-bound β-adrenergic receptors and G protein

G protein-coupled receptors (GPCRs) and G proteins transmit signals from hormones and neurotransmitters across cell membranes, initiating downstream signaling and modulating cellular behavior. Using advanced computer modeling and simulation, we identified atomistic-level structural, dynamic, and energetic mechanisms of norepinephrine (NE) and stimulatory G protein (Gs) interactions with β-adrenergic receptors (βARs), crucial GPCRs for heart function regulation and major drug targets. Our analysis revealed distinct binding behaviors of NE within β1AR and β2AR despite identical orthosteric binding pockets. β2AR had an additional binding site, explaining variations in NE binding affinities. Simulations showed significant differences in NE dissociation pathways and receptor interactions with the Gs. β1AR binds Gs more strongly, while β2AR induces greater conformational changes in the α subunit of Gs. Furthermore, GTP and GDP binding to Gs may disrupt coupling between NE and βAR, as well as between βAR and Gs. These findings may aid in designing precise βAR-targeted drugs.

Structural basis for malate-driven, pore lipid-regulated activation of the Arabidopsis vacuolar anion channel ALMT9

In plant cells, ALMTs are key plasma and vacuolar membrane-localized anion channels regulating plant responses to the environment. Vacuolar ALMTs control anion accumulation in plant cells and, in guard cells, they regulate stomata aperture. The activation of vacuolar ALMTs depends on voltage and cytosolic malate, but the underlying molecular mechanisms remain elusive. Here we report the cryo-EM structures of ALMT9 from Arabidopsis thaliana (AtALMT9), a malate-activated vacuolar anion channel, in plugged and unplugged lipid-bound states. In all these states, membrane lipids interact with the ion conduction pathway of AtALMT9. We identify two unplugged states presenting two distinct pore width profiles. Combining structural and functional analysis we identified conserved residues involved in ion conduction and in the pore lipid interaction. Molecular dynamics simulations revealed a peculiar anion conduction mechanism in AtALMT9. We propose a voltage-dependent activation mechanism based on the competition between pore lipids and malate at the cytosolic entrance of the channel.

Phenazine Scaffolds as a Potential Allosteric Inhibitor of LasR Protein in Pseudomonas aeruginosa

Millions of individuals suffer from chronic infections caused by bacterial biofilms, resulting in significant loss of life. Pseudomonas aeruginosa stands out as a major culprit in causing such chronic infections, largely due to its antibiotic resistance. This pathogen poses a considerable threat in healthcare settings, particularly to critically ill and immunocompromised patients. The persistence of chronic and recurrent bacterial infections is often attributed to bacterial biofilms. Therefore, there is an urgent need to discover novel small molecules capable of efficiently eliminating biofilms independent of bacterial growth. In this project, an in silico drug discovery approach was employed to identify nine halogenated-phenazine compounds as allosteric inhibitors of the LasR protein. The LasR is a key transcription factor that triggers other quorum-sensing systems and plays a crucial role in biofilm formation and activation of virulence genes. By inhibiting LasR, specifically targeting its allosteric site, the dimerization of LasR and subsequent biofilm formation could be prevented. Molecular docking and simulations, coupled with binding energy calculations, identified five compounds with potential as anti-biofilm agents. These compounds exhibited higher binding affinities to the distal site, suggesting their structural capability to interact with allosteric site residues of the LasR protein. Based on these findings, it is proposed that these compounds could serve as promising leads for the treatment of biofilm and quorum-sensing-related infections.

Therapeutic Role of Quercetin in Prostate Cancer: A Study of Network Pharmacology, Molecular Docking, and Dynamics Simulation

Prostate cancer (PCa) is a major cause of cancer-related mortality in men. This study explores the anticancer potential of Quercetin, a polyphenolic compound with antioxidant and anti-inflammatory properties, by network pharmacology, molecular docking, and molecular dynamics simulation approaches. Target genes for Quercetin and PCa were identified from the bioinformatics databases MalaCards, Comparative Toxicogenomics Databases, SwissTargetPrediction, and Traditional Chinese Medicine Systems Pharmacology, and the obtained genes were matched using the Venny platform to find out the common genes. We obtained 11 preliminary genes and analyzed them in ShinyGO-0.77 databases to obtain genetic otology data. Then, we constructed a protein-protein interaction network in STRING, which enabled us to identify six hub genes AKT1, EGFR, MMP2, MMP9, PARP1, and ABCG2. Hub genes were analyzed in the TISIDB database for immune cell infiltration. Furthermore, a molecular docking study between the target proteins and Quercetin was performed in the SwissDock databases. Subsequently, we corroborated the docking with molecular dynamics studies using GROMACS software. Gene Ontology and KEGG pathway analyses revealed that Quercetin influences oxidative stress, mitochondrial function, and metalloproteinase activity. Immune cell infiltration analysis highlighted correlations between key genes and specific immune responses, suggesting a modulatory role of Quercetin in the tumor microenvironment. Finally, docking and molecular dynamics analysis showed that Quercetin has a stable interaction with the hub genes. In conclusion, these findings underline the potential of Quercetin to induce apoptosis, inhibit angiogenesis, and suppress metastasis, proposing it as a promising therapeutic tool for the treatment of PCa. However, additional experimental studies are required to translate these findings into clinical practice.

PX-MDsim: a rapid and efficient platform for large-scale construction of polyamide membranes via automated molecular dynamics simulations

Polyamide (PA) membranes have attracted extensive attention due to their excellent separation performance in water treatment through reverse osmosis and nanofiltration processes. Although numerous molecular simulation studies attempt to explore their advantages from the microstructure, large-scale construction and simulation of PA membranes remain challenging, mainly due to the complexity and computational intensity of cross-linking reactions of polymers in molecular dynamics simulations. This paper introduces an automated platform called PX-MDsim for modeling and simulation of PA membranes. PX-MDsim is based on the PXLink framework and extends its applicability to any monomer with amino (-NH2) and carboxyl (-COOH) groups. The platform, combined with the PXLink program, realizes the full-process automated cross-linking simulation from input preparation, initial system construction, force field generation, functional group identification, and charge distribution update. Moreover, the software was used to cross-link m-phenylenediamine and 1,4-bis(3-aminopropyl)piperazine with trimesic acid, respectively, and multiple membrane structures with different cross-linking degrees were obtained. Furthermore, the generated membrane microstructure was analyzed using methods such as pore size distribution and order parameter, and the obtained results verified the applicability and accuracy of PX-MDsim in constructing PA membrane structures. The platform is user-friendly and accessible to researchers without prior expertise in molecular dynamics simulation, and it offers new possibilities for polymer research and applications.

In silico evaluation of N-aryl-1,10-phenanthroline-2-amines as potential inhibitors of T. cruzi GP63 zinc-metalloprotease by docking and molecular dynamics simulations

Based on the in vitro trypanocidal efficacy of previously synthesized N-aryl-1,10-phenanthroline-2-amines (Phen1-20) (aryl = R-phenyl, 1- or 2-naphthyl), we explored the potential interactions of these derivatives as ligands of our comparative model of T. cruzi GP63 (TcGP63). This surface metalloprotease plays a crucial role in parasite adhesion to host cells and aids in cell invasion during T. cruzi infection in Chagas disease. Ligand-protein consensus docking simulations using four GOLD scoring functions revealed that N-(R-phenyl) derivatives (R = CH3, OCH3, CF3, CN, NO2, F, Cl, and Br) presented poses with higher fitness scores than the N-naphthyl ones, with the six para-substituted derivatives (Phen4, p-CH3; Phen7, p-OCH3; Phen10, p-CN; Phen14, p-F; Phen17, p-Cl; and Phen18, p-Br) being more favorable than the ortho or meta ones. Subsequent aqueous molecular dynamics simulation (GROMACS package, CHARMM36 force field, and TIP3P water model) of the ligand-protein complexes for these six top-ranking compounds showed persistent interactions within the TcGP63 active site, primarily through coordination with Zn(II)-cofactor, and H-bonding with catalytic Glu221 and zinc-binding His224. RMSD and RMSF analyses confirmed the stability of these interactions, particularly for compounds with electron-withdrawing groups by inductive effect as R-substituents, such as p-OCH3 (Phen7) and p-CN (Phen10). Binding free energy calculations by the linear interaction energy (LIE) approach corroborated the favorable interactions observed in simulations, highlighting Phen7 and Phen10 as the most promising candidates. This study underscores the potential of N-phenyl-1,10-phenanthroline-2-amines as putative inhibitors targeting the T. cruzi GP63 enzyme.

Organic Modulators Enable Morphological Diversity in Colloidal Crystals Engineered with DNA

Colloidal crystal engineering with DNA is a powerful way of generating a wide variety of crystals spanning over 90 different symmetries. However, in many cases, crystals with well-defined habits are difficult, if not impossible, to make, in part due to rapid crystal defect formation and propagation. This is especially true in the case of face-centered cubic (FCC) structures. Herein, we report a strategy that uses formamide as a chemical modulator to slow down colloidal crystal growth, which decreases defect formation and yields higher-quality crystals. Formamide forms hydrogen bonds with DNA bases and destabilizes the DNA duplex; in the context of colloidal crystallization, formamide leads to the disassembly of undercoordinated particles (defect architectures) and facilitates their reassembly into structures with the maximum number of nearest-neighbor contacts and DNA bonds. When targeting an FCC lattice comprised of DNA-modified spherical 20 nm particles, formamide promotes the formation of its Wulff polyhedron (a truncated octahedron), never observed before in colloidal crystal engineering with DNA. Importantly, kinetic habits, including tetrahedra, octahedra, icosahedra, and decahedra, are also observed depending on formamide concentration.

Hidden complexity of α7 nicotinic acetylcholine receptor desensitization revealed by MD simulations and Markov state modeling

The α7 nicotinic acetylcholine receptor is a pentameric ligand-gated ion channel that plays an important role in neuronal signaling throughout the nervous system. Its implication in neurological disorders and inflammation has spurred the development of numerous compounds that enhance channel activation. However, the therapeutic potential of these compounds has been limited by the characteristically fast desensitization of the α7 receptor. Using recent high-resolution structures from cryo-EM, and all-atom molecular dynamic simulations augmented by Markov state modeling, here we explore the mechanism of α7 receptor desensitization and its implication on allosteric modulation. The results provide a precise characterization of the desensitization gate and illuminate the mechanism of ion-pore opening/closing with an agonist bound. In addition, the simulations reveal the existence of a short-lived, open-channel intermediate between the activated and desensitized states that rationalizes the paradoxical pharmacology of the L247T mutant and may be relevant to type-II allosteric modulation. This analysis provides an interpretation of the signal transduction mechanism and its regulation in α7 receptors.

Rational Design and Synthesis of a Novel Series of Thiosemicarbazone-Containing Quinazoline Derivatives as Potential VEGFR2 Inhibitors

Background/Objectives: Angiogenesis plays a crucial role in tumor development and is a driving force for the aggressiveness of several types of cancer. Our team developed a novel series of thiosemicarbazone-containing quinazoline derivatives, TSC1-TSC10, as potential VEGFR2 inhibitors with proven anti-angiogenic and antiproliferative potential. Methods: The TSC1-TSC10 series was synthesized and characterized by spectral data. Extensive methodology was applied both in vitro (Alamar Blue assay, Scratch assay, CAM assay, and VEGFR2 kinase assay) and in silico (docking studies, MDs, and MM-PBSA) for the confirmation of the biological potential. Results: TSC10 emerged as the most promising compound, with a favorable cytotoxic potential across the cell panel (Ea.Hy296, HaCaT, and A375) in agreement with the in vitro VEGFR2 kinase assay (IC50 = 119 nM). A comparable motility reduction in the vascular endothelial cells to that of the reference drug sorafenib was provided by TSC10, with a similar anti-angiogenic potential in the more complex in ovo model of the CAM assay. The in silico experiments confirmed the successful accommodation of the active site of the kinase domain similar to sorafenib for the entire TSC1-TSC10 series, providing valuable key insight into the complex stability driving force for the evaluated compounds. Conclusions: The in vitro evaluations of the biological potential correlated with the in silico predictions by computer-aided complex simulations provided a solid confirmation of the initial hypothesis for the TSC1-TSC10 series.

N-Branched Tricyclic Guanidines as Novel Melanocortin-3 Receptor Agonists and Melanocortin-4 Receptor Antagonists

The melanocortin receptors are a class of centrally and peripherally expressed G protein-coupled receptors, of which the MC3R and MC4R subtypes are implicated in the regulation of appetite and energy homeostasis and can serve as potential therapeutic targets for disorders such as obesity and cachexia. An unbiased high-throughput mixture-based library screen was implemented to identify novel ligands with an emphasis on the identification of nanomolar-potent agonists of the mouse melanocortin-3 receptor. This screen yielded the discovery of an N-branched tricyclic guanidine scaffold (TPI2408) that contained three nanomolar potent mMC3R agonists and additional compounds that possessed antagonism for the mMC4R. The antagonist character of this scaffold library at the mMC4R was confirmed by a follow-up positional scanning antagonist screen. Additionally, molecular dynamics simulations herein provide mechanistic insight into the polypharmacological characteristics of melanocortin receptors. The disclosed materials have the potential to serve as important tools and SAR scaffolds in the study of melanocortin receptor function.

Graphene or MoS2 nanopores: pore adhesion and protein linearization

Nanopores drilled in materials can electrophoretically drive charged biomolecules to enable their detection. Here, we explore and compare two-dimensional nanopores, graphene and MoS2, in order to unravel their advantages and disadvantages with regard to protein detection. We tuned the protein translocation and its dynamics by the choice and concentration of the surrounding solvent. For this, we used a typical monovalent salt solution, as well as a molecular solution. We assessed, with the aid of atomistic simulations, the efficiency of both nanopores in threading the protein on the basis of measurable ionic current signals. In the case of graphene, the protein adheres on the graphene surface, hindering the translocation under physiological conditions. This stickiness is resolved with the addition of a denaturant by the formation of a hydrophilic cationic layer on the pore surface and the protein can thread the pore in a linearized configuration. On the other hand, the MoS2 nanopores can thread the protein also in a physiological solution, leading to longer passage times, while the degree of protein linearization is lower than in the case of graphene in a molecular solution. We analyze the differences between the two nanopore materials on the basis of the complex molecular interactions between all components, the material, the target protein, and the solvent. We discuss the relevance of the results with respect to controlling the protein dynamics and enhancing the read-out ionic signals in view of an efficient detection of proteins through 2D nanopores.

Insights into Dermal Permeation of Skin Oil Oxidation Products from Enhanced Sampling Molecular Dynamics Simulation

The oxidation of human sebum, a lipid mixture covering our skin, generates a range of volatile and semivolatile carbonyl compounds that contribute largely to indoor air pollution in crowded environments. Kinetic models have been developed to gain a deeper understanding of this complex multiphase chemistry, but they rely partially on rough estimates of kinetic and thermodynamic parameters, especially those describing skin permeation. Here, we employ atomistic molecular dynamics simulations to study the translocation of selected skin oil oxidation products through a model stratum corneum membrane. We find these simulations to be nontrivial, requiring extensive sampling with up to microsecond simulation times, in spite of employing enhanced sampling techniques. We identify the high degree of order and stochastic, long-lived temporal asymmetries in the membrane structure as the leading causes for the slow convergence of the free energy computations. We demonstrate that statistical errors due to insufficient sampling are substantial and propagate to membrane permeabilities. These errors are independent of the enhanced sampling technique employed and very likely independent of the precise membrane model.

A combined in silico approach to design peptide ligands with increased receptor-subtype selectivity

G-protein coupled receptors are major drug targets that change their conformation upon binding of ligands to their extracellular binding pocket to transduce the signal to intracellular G-proteins or arrestins. In drug screening campaigns, computational methods are frequently used to predict binding affinities for chemical compounds in silico before experimental testing. Some of these methods take into consideration the inherent flexibility of the ligand and to some extent also of the receptor. Due to high structural flexibility, peptide ligands are exceptionally difficult to handle and approaches to effectively sample in silico receptor-peptide ligand interactions are limited. Here we describe a pipeline starting from microseconds molecular dynamics simulations of receptor and receptor ligand complexes to find reasonable starting conformations and derive constraints for subsequent flexible docking of peptide ligands, using Rosetta's FlexPepDock approach. We applied this approach to predict binding affinities for dynorphin and its variants to members of the opioid receptor family. Using an ensemble of docking poses, Rosetta's fixbb protein design method explored the sequence space at defined positions, to enhance binding affinities, aiming to increase subtype selectivity towards κ-opioid receptor while decreasing it towards μ-opioid receptor. The results of our computations were validated experimentally in a related study (Zangrandi et al., 2024[1]). Four out of six proposed variants lead to a significant increase in subtype selectivity in favor of κ-opioid receptor, highlighting the potential of our approach to design subtype selective peptide variants. The established workflow may also apply for other receptor types activated by peptide ligands.

Kinetics and Mechanisms of Solar UVB Disinfection of Vesicle-Cloaked Murine Norovirus Clusters and Free Noroviruses

Human norovirus, a major global cause of gastroenteritis, forms vesicle-cloaked virus clusters (known as viral vesicles), showing increased infectivity and persistence in aquatic environments. We investigated UVB disinfection, a key mechanism of solar disinfection commonly employed in developing countries, targeting murine norovirus vesicles and free murine noroviruses as surrogates for human noroviruses. At low viral concentrations of 109 gene copies per liter, viral infectivity loss as quantified by the integrated cell culture-reverse transcription-quantitative polymerase chain reaction (ICC-RT-qPCR) indicated that vesicles were 1.51 to 1.73 times more resistant to disinfection compared to free viruses. Virus inactivation was primarily due to protein damage as quantified by bicinchoninic acid and Western blot assays, and the damage of virus binding to host cells as quantified by RT-qPCR. Molecular simulations predicted that the oxidation of a tyrosine residue in the viral protein 1 prohibited binding. UVB irradiation of viral/vesicle proteins resulted in 1O2 formation as quantified by time-resolved phosphorescence, and for the first time, endogenous 1O2 was confirmed to contribute to virus inactivation by UVB. Our study recognizes the limitation of UVB disinfection of viral vesicles particularly in solar wastewater treatment and advocates for enhanced disinfection strategies to protect public health.

Interleaflet Translocation of Second-Harmonic-Generation-Active Dye Molecules in Phospholipid Bilayers with Transmembrane Pores

Second harmonic generation (SHG) measurements using SHG-active dye molecules have recently attracted attention as a method to detect the formation of pores in phospholipid bilayers. The bilayers, in which the dye molecules are embedded in the outer leaflet, exhibit a noncentrosymmetric structure, generating SHG signals. However, when pores form, these dye molecules translocate through the pores into the inner leaflet, leading to a more centrosymmetric structure and the subsequent loss of the SHG signals. A decrease in the SHG signals has been experimentally observed in membranes subjected to electrical stimuli. However, the characteristics of the interleaflet translocation of SHG-active dye molecules through pores remain unclear, hindering quantitative estimation of the membrane conditions, such as the pore size and density, based on the SHG signal reduction. In this study, we investigated the interleaflet translocation characteristics of Ap3, an SHG-active dye molecule, using molecular dynamics (MD) simulations and two-dimensional random-walk (RW) simulations. The MD simulations revealed that Ap3 molecules only translocate between the leaflets along the pore sidewalls. We determined the lateral diffusion coefficient of Ap3 within the membrane plane and its propensity for interleaflet movement at the pore wall. Based on these movement characteristics, the RW model successfully reproduced the characteristic time scale of the interleaflet translocation observed in the MD simulations. By varying the pore size and density in the RW simulations, we estimated that the characteristic time scale of interleaflet translocation depends on the -0.31 power of the pore radius and the -1.13 power of the pore density. Using these findings, we estimated the number of pores that probably formed in membranes during previous electroporation experiments. These results indicate the potential of optical measurement of the dye molecule movement for the indirect quantitative estimation of the pore size and number, which are challenging to measure optically.

SPONGE-FEP: An Automated Relative Binding Free Energy Calculation Accelerated by Selective Integrated Tempering Sampling

Computer-aided drug discovery (CADD) utilizes computational methods to accelerate the identification and optimization of potential drug candidates. Free energy perturbation (FEP) and thermodynamic integration (TI) play a critical role in predicting differences in protein binding affinities between drug molecules. Here, we implement SPONGE-FEP, which incorporates selective integrated tempering sampling (SITS) to enhance sampling efficiency and contains an automated workflow for relative binding free energy (RBFE) calculations. We first provide an overview of the workflow, which encompasses the generation of a perturbation map, alchemical free energy calculations, and cycle closure analysis. Two case studies were then performed to demonstrate the enhanced sampling of conformational states of ligands and proteins during the alchemical transformation process. The results show that the refined SITS method in SPONGE-FEP can significantly improve the sampling efficiency of rare events and the performance of RBFE predictions. Three series of comparative RBFE tests were conducted to demonstrate the accuracy of SPONGE-FEP, which is comparable to FEP+, using an average computation time of 4 h for a pair of ligands on an A100 GPU device.

Experiment-Guided Refinement of Milestoning Network

Milestoning is an efficient method for calculating rare event kinetics by constructing a continuous-time kinetic network that connects the reactant and product states. Its accuracy depends on both the quality of the underlying force fields and the trajectory sampling. The sampling error can be effectively controlled through various methods. However, the force fields are often not accurate enough, leading to quantitative discrepancies between simulations and experimental data. To address this challenge, we present a refinement approach for Milestoning network based on the maximum caliber (MaxCal), a general variational principle for dynamical systems, to combine simulations and experimental data. The Kullback-Leibler divergence rate between two Milestoning networks is analytically evaluated and minimized as the loss function. Meanwhile, experimental thermodynamic (equilibrium constants) and kinetic (rate constants) data are incorporated as constraints. The use of MaxCal implies that the refined kinetic network is minimally perturbed from the original one while satisfying the experimental constraints. The refined network is expected to align better with available experimental data. The refinement approach is demonstrated using the binding and unbinding dynamics of a series of six small molecule ligands for the model host system, β-cyclodextrin.

Pharmacophore-based identification and in Silico characterization of microbial metabolites as potential modulators of Wnt signaling pathway in colorectal cancer therapy

Aberrant activation of the Wnt/β-catenin signaling pathway, primarily driven by APC mutation and AXIN degradation via Tankyrase, contributes significantly to colorectal cancer (CRC) progression and metastasis. The accumulation of β-catenin, resulting from the dysregulated ubiquitination, underscores the need for alternative therapeutic strategies targeting Tankyrase and β-catenin. This present study explores microbial metabolites as a source of novel anti-cancer agents, leveraging their unique bioactivity and structural diversity, often exhibiting superior target specificity and lower toxicity than synthetic drugs. Through a computational drug discovery pipeline, a large library of 27641 microbial metabolites was initially screened based on multiple drug-likeliness criteria, resulting in the selection of 2527 compounds. Among the screened compounds, an integrated computational workflow comprising molecular docking, molecular dynamic simulations (MDS), MM/PBSA analysis, and Principal component analysis (PCA) identified Terreustoxin I (T1) as a potential Tankyrase inhibitor. In contrast, compound 10- phenyl-[12]-cytochalasin Z16 (B1) demonstrated a strong binding affinity within the β-catenin active site. Under physiological conditions, these lead compounds were evaluated for conformational stability, binding efficacy, and dynamic behavior. Additionally, ADMET profiling, physiochemical properties, and bioactivity score predictions confirmed the identified compounds' pharmacokinetic suitability and reduced toxicity profile. In silico, cytotoxicity predictions showed significant activity against SW480 and HCT90 colorectal cell lines, with additional anti-neoplastic and anti-leukemic properties, strengthening their candidacy as effective anti-cancer agents. These findings provide a foundation for further experimental validation and development of novel CRC therapies with improved safety and efficacy potential.

Machine learning of molecular dynamics simulations provides insights into modulation of viral capsid assembly

An effective approach in the development of novel antivirals is to target the assembly of viral capsids using capsid assembly modulators (CAMs). CAMs targeting hepatitis B virus (HBV) have two major modes of function: they can either accelerate nucleocapsid assembly, retaining its structure, or misdirect it into non-capsid-like particles. Previous molecular dynamics (MD) simulations of early capsid-assembly intermediates showed differences in protein conformations for apo and bound states. Here, we have developed and tested several classification machine learning (ML) models to better distinguish between apo-tetramer intermediates and those bound to accelerating or misdirecting CAMs. Models based on tertiary structural properties of the Cp149 tetramers and their inter-dimer orientation, as well as models based on direct and inverse contact distances between protein residues, were tested. All models distinguished the apo states and the two CAM-bound states with high accuracy. Furthermore, tertiary structure models and residue-distance models highlighted different tetramer regions as important for classification. Both models can be used to better understand structural transitions that govern the assembly of nucleocapsids and to assist the development of more potent CAMs. Finally, we demonstrate the utility of classification ML methods in comparing MD trajectories and describe our ML approaches, which can be extended to other systems of interest.

Mechanistic and structural insights into EstS1 esterase: A potent broad-spectrum phthalate diester degrading enzyme

Phthalate diesters are important pollutants and act as endocrine disruptors. While certain bacterial esterases have been identified for phthalate diesters degradation to monoesters, their structural and mechanistic characteristics remain largely unexplored. Here, we highlight the potential of the thermostable and pH-tolerant EstS1 esterase from Sulfobacillus acidophilus DSM10332 to degrade high molecular weight bis(2-ethylhexyl) phthalate (DEHP) by combining biophysical and biochemical approaches along with high-resolution EstS1 crystal structures of the apo form and with bound substrates, products, and their analogs to elucidate its mechanism. The catalytic tunnel mediates entry and exit of the substrate and product, respectively. The centralized Ser-His-Asp triad performs catalysis by a bi-bi ping-pong mechanism, forming a tetrahedral intermediate. Mutagenesis analysis showed that the Met207Ala mutation abolished DEHP binding at the active site, confirming its essential role in supporting catalysis. These findings underscore EstS1 as a promising tool for advancing technologies aimed at phthalate diesters biodegradation.

Ion coupling and inhibitory mechanisms of the human presynaptic high-affinity choline transporter CHT1

In cholinergic neurons, choline is the precursor of the excitatory neurotransmitter acetylcholine (ACh), which plays a fundamental role in the brain. The high-affinity choline transporter, CHT1, mediates the efficient recycling of choline to facilitate ACh synthesis in the presynapse. Here, we report high-resolution cryoelectron microscopic (cryo-EM) structures of CHT1 in complex with the inhibitors HC-3 and ML352, the substrate choline, and a substrate-free state. Our structures show distinct binding modes of the inhibitors with different chemical structures, revealing their inhibition mechanisms. Additionally, we observed a chloride ion that directly interacts with the substrate choline, thereby stabilizing its binding with CHT1. Two sodium ions, Na2 and Na3, were clearly identified, which we speculate might be involved in substrate binding and conformational transitions, respectively. Our structures provide molecular insights into the coupling mechanism of ion binding with substrate binding and conformational transitions, promoting our understanding of the ion-coupled substrate transport mechanism.

Molecular Dynamics Insights into Water Transport Mechanisms in Polyamide Membranes: Influence of Cross-Linking Degree

Polyamide (PA) membranes are widely utilized in desalination and water treatment applications, yet the mechanisms underlying water transport within these amorphous polymer materials remain insufficiently understood. To gain more insight into these problems on a microscopic scale, we employ molecular dynamics (MD) simulations to analyze the relationship between the structural properties and the water permeation behavior of PA membranes. Two distinct atomistic models of PA membranes are developed by controlling their degrees of cross-linking (DC). We then conducted a comparative analysis on their microscopic structural properties and configurations of water inside the membranes and investigated how these differences lead to different water diffusion coefficients. Our results reveal that the membrane with a lower DC exhibits higher polymer mobility and a more orderly microscopic structure, allowing the formation of pores that can hold larger water clusters as well as more transient passages between pores, both contributing to an increased water diffusion coefficient. From these observations, we can conclude that water permeability within PA membranes is governed by both the morphology of semirigid pores and the oscillatory movements of the polymer chains. Overall, these findings contribute to a deeper understanding of the intricate mechanisms governing water permeation in PA membranes and may inform the design of more efficient membranes for reverse osmosis and other water treatment technologies.

Complementary Peptide Interactions Support the Ultra-Rigidity of Polymers of De Novo Designed Click-Functionalized Bundlemers

Computationally designed 29-residue peptides yield tetra-α-helical bundles with D2 symmetry. The "bundlemers" can be bifunctionally linked via thiol-maleimide cross-links at their N-termini, yielding supramolecular polymers with unusually large, micrometer-scale persistence lengths. To provide a molecularly resolved understanding of these systems, all-atom molecular modeling and simulations of linked bundlemers in explicit solvent are presented. A search over relative orientations of the bundlemers identifies a structure, wherein at the bundlemer-bundlemer interface, interior hydrophobic residues are in contact, and α-helices are aligned with a pseudocontiguous α-helix that spans the interface. Calculation of a potential of mean force confirms that the structure in which the bundlemers are in contact and colinearly aligned is a stable minimum. Analyses of hydrogen bonds and hydrophobic complementarity highlight the complementary interactions at the interface. The molecular insight provided reveals the molecular origins of bundlemer alignment within the supramolecular polymers.

Probing the orientation and membrane permeation of rhodamine voltage reporters through molecular simulations and free energy calculations

The transmembrane potential of plasma membranes and membrane-bound organelles plays a fundamental role in cellular functions such as signal transduction, ATP synthesis, and homeostasis. Rhodamine voltage reporters (RhoVRs), which operate based on the photoinduced electron transfer (PeT) mechanism, are non-invasive, small-molecule voltage sensors that can detect rapid voltage changes, with some of them specifically targeting the inner mitochondrial membrane. In this work, we conducted extensive molecular dynamics simulations and free-energy calculations to investigate the physicochemical properties governing the orientation as well as membrane permeation barriers of three RhoVRs. Our results indicate that the positioning of the most polarized functional group relative to the hydrophobic molecular wire dictates the alignment of RhoVRs with the membrane normal, thereby, significantly affecting their voltage sensitivity. Free-energy calculations in different membrane systems identify significantly higher barriers against the permeation of RhoVR 1 compared to SPIRIT RhoVR 1, explaining their distinct subcellular localization profiles. Subsequent free-energy calculations of the distinguishing components from the two different RhoVRs provide additional insight into the physicochemical properties governing their membrane permeation. The connection between chemical composition and membrane orientation, as well as permeation behaviors of RhoVRs revealed by our calculations provides general guiding principles for the rational design of PeT-based fluorescent dyes with enhanced voltage sensitivity and desired subcellular distribution.

Martini compatible coarse-grained model of polyethylenimine for pulmonary gene delivery

Pulmonary gene delivery has demonstrated high specificity for respiratory diseases, offering great control on dosage of therapeutics and side effects. On the other hand, intrinsic barriers in pulmonary systems impose new challenges such as crossing the pulmonary surfactant and evading mucus entrapment. Differences in hydrophobicity of plasma membrane and pulmonary surfactant require different chemistries of gene carriers to improve efficacy. Large-scale coarse-grained (CG) molecular dynamics simulations would facilitate the screening of gene carriers and understanding of the molecular mechanisms involved in pulmonary delivery. Among non-viral carriers, polyethyleneimine (PEI) has been a promising candidate that can be synthesized with various molecular weight, degree of branching, and functionalization. In this work, CG models are developed for PEI and its lipid-functionalized form, within the Martini framework, to provide a platform for exploring structure-function relationships of PEI-based pulmonary delivery systems. Special attention is focused on parameterizing the non-bonded interactions associated with CG PEI, to ensure compatibility with Martini proteins, short interfering RNA, and phospholipids that are essential components in pulmonary gene delivery. The non-bonded parameters are validated by comparing all-atom (AA) and CG potential of mean force (PMF) curves, where the root-mean-square deviations between the AA and CG PMF curves are shown to be comparable to or smaller than those reported in Martini literature.

Enzymes in a human cytoplasm model organize into submetabolon complexes

Enzyme-enzyme interactions are fundamental to the function of cells. Their atomistic mechanisms remain elusive mainly due to limitations of in-cell measurements. We address this challenge by atomistically modeling, for a total of ≈80 μs, a slice of the human cell cytoplasm that includes three successive enzymes along the glycolytic pathway: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), and phosphoglycerate mutase (PGM). We tested the model for nonspecific protein stickiness, an artifact of current atomistic force fields in crowded environments. The simulations reveal that the human enzymes co-organize in-cell into transient submetabolon complexes, consistent with previous experimental results. Our data both reiterate known specificity between GAPDH and PGK and reveal extensive direct interactions between GAPDH and PGM. Our simulations further reveal, through force field benchmarking, the critical role of protein solvation in facilitating these enzyme-enzyme interactions. Transient interenzyme interactions with μs lifetime occur repeatedly in our simulations via specific sticky protein surface patches, with interactions often mediated by charged patch residues. Some of the residues that interact frequently with one another lie in or near the active site of the enzymes. We show that some of these patches correspond to a general mode to interact with several partners for promiscuous enzymes like GAPDH. We further show that the non-native yeast PGK is stickier than human PGK in our human cytoplasm model, supporting the idea of evolutionary pressure to reduce sticking. Our cytoplasm modeling paves the way toward capturing the atomistic dynamics of an entire enzymatic pathway in-cell.

Discovery of Fluorescent Probe ABDS-2 for Farnesoid X Receptor Modulator Characterization and Cell-Based Imaging

The farnesoid X receptor (FXR) regulates key physiological processes, such as bile acid homeostasis and lipid metabolism, making it an important target for drug discovery. However, the overactivation of FXR often leads to adverse effects. This study presents the development of a novel fluorescent probe utilizing the computer-aided drug design (CADD) approach to optimize linkers between more potent warhead and FITC fluorescent groups. The probes were designed and assessed via molecular dynamics simulations, and four were selected for synthesis to be evaluated in in vitro biochemical assays. Among these, ABDS-2 exhibited high sensitivity and stability, which demonstrated satisfactory validation in high-throughput screening assays. Furthermore, ABDS-2 facilitated real-time bioimaging to monitor FXR homeostasis at the cellular level, providing spatially resolved insights into molecular interactions critical for cellular function studies. This research underscores the efficiency of CADD in probe design and positions ABDS-2 as a valuable chemical tool for in vitro assays and cellular-level bioimaging.

Energetics of Oligosaccharide Adsorption on Ionic Liquid-Clay Composites

Well-Tempered Metadynamics (WT-MetaD) simulations indicate that composite materials made up of Na-Montmorillonite (Na-MMT) coated with ionic liquids (ILs) having hydrophilic cations serve as good adsorbents for a hexameric (1,4) linked β-D-glucopyranoside (BGLC). Hydrophilic IL cations are effectively coated on the negative charges lining the Na-MMT surface while attracting simultaneously the polar oligosaccharides. In this work we have used two less conventional polyethylene glycol (PEG) based IL cations, [mim2 peg1]2+ and [mim2 peg2]2+, paired with [tf2N]- and Cl- anions. Another strongly hydrophilic ion combination, [C2OHmim][Cl], also showed great promise in effective oligosaccharide adsorption on the Na-MMT surface. The study reveals that the topological polar surface area (TPSA), the octanol-water partition coefficient (log PO/W), the length of the cationic side chain and the Debye screening lengthλ D ${\left({\lambda }_{D}\right)}$ of the IL are some of the most important factors affecting the adsorption of hydrophilic oligosaccharides on the clay-IL composites. Among all the systems studied, [mim2 peg2][tf2N]2 having the highest TPSA and a long screening length emerged as the best adsorbent for the oligosaccharide on the IL-coated clay.

Diffusion-programmed catalysis in nanoporous material

In the realm of heterogeneous catalysis, the diffusion of reactants into catalytically active sites stands as a pivotal determinant influencing both turnover frequency and geometric selectivity in product formation. While accelerated diffusion of reactants can elevate reaction rates, it often entails a compromise in geometric selectivity. Porous catalysts, including metal-organic and covalent organic frameworks, confront formidable obstacles in regulating reactant diffusion rates. Consequently, the chemical functionality of the catalysts typically governs turnover frequency and geometric selectivity. This study presents an approach harnessing diffusion length to achieve improved selectivity and manipulation of reactant-active site residence time at active sites to augment reaction kinetics. Through the deployment of a thin film composed of a porous metal-organic framework catalyst, we illustrate how programming reactant diffusion within a cross-flow microfluidic catalytic reactor can concurrently amplify turnover frequency (exceeding 1000-fold) and enhance geometric selectivity ( ~ 2-fold) relative to conventional nano/microcrystals of catalyst in one-pot reactor. This diffusion-programed strategy represents a robust solution to surmount the constraints imposed by bulk nano/microcrystals of catalysts, marking advancement in the design of porous catalyst-driven organic reactions.

Computational identification of potential bioactive compounds from Triphala against alcoholic liver injury by targeting alcohol dehydrogenase

Alcoholic liver injury resulting from excessive alcohol consumption is a significant social concern. Alcohol dehydrogenase (ADH) plays a critical role in the conversion of alcohol to acetaldehyde, leading to tissue damage. The management of alcoholic liver injury encompasses nutritional support and, in severe cases liver transplantation, but potential adverse effects exist, and effective medications are currently unavailable. Natural products with their potential benefits and historical use in traditional medicine emerge as promising alternatives. Triphala, a traditional polyherbal formula demonstrates beneficial effects in addressing diverse health concerns, with a notable impact on treating alcoholic liver damage through enhanced liver metabolism. The present study aims to identify potential active phytocompounds in Triphala targeting ADH to prevent alcoholic liver injury. Screening 119 phytocompounds from the Triphala formulation revealed 62 of them showing binding affinity to the active site of the ADH1B protein. Promising lipid-like molecule from Terminalia bellirica, (4aS, 6aR, 6aR, 6bR, 7R, 8aR, 9R, 10R, 11R, 12aR, 14bS)-7, 10, 11-trihydroxy-9-(hydroxymethyl)-2, 2, 6a, 6b, 9, 12a-hexamethyl-1, 3, 4, 5, 6, 6a, 7, 8, 8a, 10, 11, 12, 13, 14b-tetradecahydropicene-4a-carboxylic acid showed high binding efficiency to a competitive ADH inhibitor, 4-Methylpyrazole. Pharmacokinetic analysis further confirmed the drug-likeness and non-hepatotoxicity of the top-ranked compound. Molecular dynamics simulation and MM-PBSA studies revealed the stability of the docked complexes with minimal fluctuation and consistency of the hydrogen bonds throughout the simulation. Together, computational investigations suggest that (4aS, 6aR, 6aR, 6bR, 7R, 8aR, 9R, 10R, 11R, 12aR, 14bS)-7, 10, 11-trihydroxy-9-(hydroxymethyl)-2, 2, 6a, 6b, 9, 12a-hexamethyl-1, 3, 4, 5, 6, 6a, 7, 8, 8a, 10, 11, 12, 13, 14b-tetradecahydropicene-4a-carboxylic acid from the Triphala formulation holds promise as an ADH inhibitor, suggesting an alternative therapy for alcoholic liver injury.

Crystallographic mining driven computer-guided approach to identify the ASK1 inhibitor likely to perturb the catalytic region

The pathological levels of reactive oxygen species (ROS) and oxidative stress has been recognized as a critical driver for inflammatory disorders. Apoptosis signal-regulating kinase 1 (ASK1) has been reported to be activated by intracellular ROS and its inhibition leads to a down regulation of p38-and JNK-dependent signaling. ASK1 inhibitors are reported to have the potential to treat clinically important inflammatory pathologies including liver, pulmonary and renal disorders. In view of its biological and pathological significance, inhibition of ASK1 with small molecules has been pursued as an attractive strategy to combat human diseases such as non-alcoholic steatohepatitis (NASH). Despite several ASK1 inhibitors being developed, the failure in Phase 3 clinical trials of most advanced candidate selonsertib's, underscores to discover therapeutic agents with diverse chemical moiety. Here, by using structural pharmacophore and enumeration strategy on mining co-crystals of ASK1, different scaffolds were generated to enhance the chemical diversity keeping the critical molecular interaction in the catalytic site intact. A total of 15,772 compounds were generated from diverse chemical scaffolds and were evaluated using a virtual screening pipeline. Based on docking and MM-GBSA scores, a lead candidate, S3C-1-D424 was identified from top hits. A comparative molecular dynamics simulations (MD) of APO, Selonsertib and shortlisted potential candidates combined with pharmacokinetics profiling and thermodynamic analysis, demonstrating their suitability as potential ASK1 inhibitors to explore further for establishment towards hit-to-lead campaign.Communicated by Ramaswamy H. Sarma.

In-silico characterization of a thermophilic serine protease via homology modeling, docking and molecular dynamics simulations

One of the major categories of industrial enzymes, proteases is crucial to the survival of living things. The purpose of this research was to newly thermostable protease from the thermophilum Geobacillus stearothermophilus. With the conserved catalytic tetrad, protease (Protease JJ) is closely related to the serine proteases from the subtilisin S8 peptidase, according to phylogenetic tree analysis. The tertiary structure of Protease JJ was predicted structurally using RoseTTAFold, and it is a sandwich structure overall. Homology modeling validation showed Protease JJ was modeled in X-ray's protein areas, and it has gained a favored Ramachandran graph regarding Phi/Psi angels. Protease JJ showed structure stability through Molecular dynamics simulation in the presence of Tween20 and Methanol in 1% concentration. Also, Protease JJ exhibited thermal stability at 60 to 90 °C so that amino acid exposure of Protease JJ was low and constant throughout the MD simulation. Docking results of Protease JJ with BSA and βcasein were simulated via MD and it was found that Protease JJ could interact with both BSA and βcasein strongly. MM/PBSA analysis showed Protease JJ may be involved via more amino acids with BSA as well as established more interaction hydrogen bonds. Overall, evidence suggests Protease JJ probably has merit for future experimental investigation as a thermostable protease.Communicated by Ramaswamy H. Sarma.

MD simulations for rational design of high-affinity HDAC4 inhibitors - Analysis of non-bonding interaction energies for building new compounds

This study investigates the contributions of non-bonding energy (NBE) to the efficacy of four HDAC4 co-crystallized inhibitors (HA3, 9F4, EBE, and TFG) through 100ns Molecular Dynamics (MD) simulations. These inhibitors contain hydroxamic acid (HA3, 9F4, EBE) or diol (TFG) as zinc-binding groups. In PDBs 2VQJ and 2VQM, the HDAC4 catalytic domain is in the 'open' conformation, while in PDBs 4CBT and 6FYZ, the same is in the 'closed' conformation. We identified HA3 as a weaker inhibitor because of the unfavorable NBE contributions from its carbonyl fragment (FR3) and hydroxamic fragment (FR1). To enhance NBE efficacy, we designed novel HA3 analogs (H01-H16) by introducing diverse fragments (-CF3, 2-hydroxyacetic acid, -NH-CH2-, 5-fluoro-2-phenyl pyrimidine, and chloroquinoline moieties). MD simulations revealed promising analogs (H02, H07, H08, H15) with strong NBEs and stable ligand-zinc retention (2.07-2.33 Å). These analogs exhibited strong relative binding free energies within their catalytic sites, highlighting their potential as novel HDAC4 inhibitors. The current study provides medicinal chemists with insights into non-covalent interactions, identifies key fragments for optimization, and offers a rational design strategy for developing more effective HDAC4 inhibitors.

De novo drug designing coupled with brute force screening and structure guided lead optimization gives highly specific inhibitor of METTL3: a potential cure for Acute Myeloid Leukaemia

Expression of METTL3, a SAM dependent methyltransferase, which deposits m6A on mRNA is linked to poor prognosis in Acute Myeloid Leukaemia and other type of cancers. Down regulation of this epitranscriptomic regulator has been found to inhibit cancer progression. Silencing the methyltransferase activity of METTL3 is a lucrative strategy to design anticancer drugs. In this study 3600 commercially available molecules were screened against METTL3 using brute force screening approach. However, none of these compounds take advantage of the unique Y-shaped binding cavity of the protein, raising the need for de novo drug designing strategies. As such, 125 branched, Y-shaped molecules were designed by "stitching" together the chemical fragments of the best inhibitors that interact strongly with the METTL3 binding pocket. This results in molecules that have the three-dimensional structure and functional groups which enable it to fit in the METTL3 cavity like fingers in a glove, having unprecedented selectivity and binding affinities. The designed compounds were further refined based on Lipinski's rule, docking score and synthetic accessibility. The molecules faring well in these criteria were simulated for 100 ns to check the stability of the protein inhibitor complex followed by binding free energy calculation.Communicated by Ramaswamy H. Sarma.

Dynamics, mechanistic and energetic evaluation of thiazole-thiadiazole compounds in flavin dependent thymidylate synthase of Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a significant global health challenge due to the emergence of drug-resistant strains. This study targets Flavin-dependent thymidylate synthase (ThyX), an essential enzyme in the thymidylate biosynthesis pathway crucial for bacterial DNA replication. We utilized advanced computational techniques, including molecular dynamics (MD) simulations and interaction energy analysis, to examine the binding interactions and stability of various thiazole-thiadiazole compounds with Mtb ThyX. Our results, corroborated by experimental validation, demonstrate that ligand binding enhances ThyX protein stability, with compound 5l exhibiting the strongest stabilizing effect. Root mean square fluctuation (RMSF) data indicate a consistent binding mechanism, while radius of gyration (RG) and solvent accessible surface area (SASA) analyses confirm structural stability. Key interactions with conserved residues such as Glu74, Ser105, Tyr44, and Ser100 were highlighted through hydrogen bonding and cluster analysis, underscoring protein-ligand complex stability. Principal component analysis (PCA) suggests an allosteric regulation mechanism within ThyX, driven by ligand binding, which induces conformational changes. Free energy landscape (FEL) analysis shows rapid stabilization in ligand-bound states. Compound 5l stands out due to its favourable pharmacokinetic properties and safety, making it a promising candidate for anti-tuberculosis drug development.