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

Structural insights into the inhibition mechanism of fungal GWT1 by manogepix

Glycosylphosphatidylinositol (GPI) acyltransferase is crucial for the synthesis of GPI-anchored proteins. Targeting the fungal glycosylphosphatidylinositol acyltransferase GWT1 by manogepix is a promising antifungal strategy. However, the inhibitory mechanism of manogepix remains unclear. Here, we present cryo-EM structures of yeast GWT1 bound to the substrate (palmitoyl-CoA) and inhibitor (manogepix) at 3.3 Å and 3.5 Å, respectively. GWT1 adopts a unique fold with 13 transmembrane (TM) helixes. The palmitoyl-CoA inserts into the chamber among TM4, 5, 6, 7, and 12. The crucial residues (D145 and K155) located on the loop between TM4 and TM5 potentially bind to the GPI precursor, contributing to substrate recognition and catalysis, respectively. The antifungal drug, manogepix, occupies the hydrophobic cavity of the palmitoyl-CoA binding site, suggesting a competitive inhibitory mechanism. Structural analysis of resistance mutations elucidates the drug specificity and selectivity. These findings pave the way for the development of potent and selective antifungal drugs targeting GWT1.

Molecular Mechanisms of Methamphetamine-Induced Addiction via TAAR1 Activation

Trace amine-associated receptor 1 (TAAR1), a member of the trace amine receptor family, recognizes various trace amines in the brain, including endogenous β-phenylethylamine (PEA) and methamphetamine (METH). TAAR1 is a novel target for several neurological disorders, including schizophrenia, depression, and substance abuse. Herein, we report the structure of the human TAAR1-Gs protein complex bound to METH. Using functional studies, we reveal the molecular basis of METH recognition by TAAR1, and potential mechanisms underlying the selectivity of TAAR1 for different ligands. Molecular dynamics simulations further elucidated possible mechanisms for the binding of chiral amphetamine (AMPH)-like psychoactive drugs to TAAR1. Additionally, we discovered a hydrophobic core on the transmembrane helices (TM), TM5 and TM6, explaining the unique mechanism of TAAR1 activation. These findings reveal the ligand recognition pattern and activation mechanism of TAAR1, which has important implications for the development of next-generation treatments for substance abuse and various neurological disorders.

Integrative Network Pharmacology, Molecular Docking, and Dynamics Simulations Reveal the Mechanisms of Cinnamomum tamala in Diabetic Nephropathy Treatment: An In Silico Study

Diabetic nephropathy (DN) is a serious diabetes-related complication leading to kidney damage. Cinnamomum tamala (CT), traditionally used in managing diabetes and kidney disorders, has shown potential in treating DN, although its active compounds and mechanisms are not fully understood. This study aims to identify CT's bioactive compounds and explore their therapeutic mechanisms in DN. Active compounds in CT were identified using the Indian Medicinal Plants, Phytochemicals and Therapeutics database, and their potential targets were predicted with PharmMapper. DN-related targets were sourced from GeneCards, and therapeutic targets were identified by intersecting the compound-target and disease-target data. Bioinformatics analyses, including the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment studies, were performed on these targets. A protein-protein interaction network was constructed using STRING and Cytoscape. Molecular docking and dynamics simulations validated the most promising compound-target interactions. Six active compounds in CT were identified, along with 347 potential therapeutic targets, of which 70 were DN-relevant. Key targets like MMP9, EGFR, and AKT1 were highlighted, and the PPAR and PI3K-AKT signaling pathways were identified as the primary mechanisms through which CT may treat DN. CT shows promise in treating DN by modulating key pathways related to cellular development, inflammation, and metabolism.

Unraveling energy transfer and fluorescence quenching dynamics in biomolecular complexes: a comprehensive study of imiquimod-rifampicin interaction

In nature, numerous biomolecules are implicated in charge transfer (CT) and energy transfer (ET) mechanisms crucial for fundamental processes such as photosynthesis. Unveiling these mechanisms is pertinent to multiple disciplines including chemistry, engineering and biochemistry. This article presents a detailed study involving two molecules forming a model system with efficient ET properties. Specifically, their complex exhibits dark quenching phenomena arising from fluorescence resonance energy transfer (FRET) from the donor (imiquimod) to the acceptor (rifampicin). In addition, the energy transfer properties were also elucidated by considering the two forms of rifampicin (RIF), non-ionic and zwitter-ionic in the solution. Supplemented by spectroscopic findings, molecular dynamics simulations and time dependent density functional theory (TD-DFT) calculations conclusively validate the ET properties from imiquimod (IMQ) to RIF forms. Interestingly, these ET processes were found to be associated with pi-pi and hydrogen bond interactions. Their contribution was observed to depend upon the non-ionic and zwitter-ionic form of RIF.

Short-Term Exposure to Foodborne Xenoestrogens Affects Breast Cancer Cell Morphology and Motility Relevant for Metastatic Behavior In Vitro

Breast cancer is highly susceptible to metastasis formation. During the time of disease progression, tumor pathophysiology can be impacted by endogenous factors, like hormonal status, as well as by environmental exposures, such as those related to diet and lifestyle. New lines of evidence point toward a potential role for foodborne endocrine disruptive chemicals in this respect; however, mechanistic understanding remains limited. At the molecular level, crucial steps toward metastasis formation include cell structural changes, alteration of adhesion, and reorganization of cytoskeletal proteins involved in motility. Hence, this study investigates the potential of dietary xenoestrogens to impact selected aspects of breast cancer cell mechanotransduction. Taking the onset of the metastatic cascade as a model, experiments focused on cell-matrix adhesion, single-cell migration, and adaptation of cell morphology. Dietary mycoestrogens alternariol (AOH, 1 μM) and α-zearalenol (α-ZEL, 10 nM), soy isoflavone genistein (GEN, 1 μM), and food packaging plasticizer bisphenol A (BPA, 10 nM) were applied as single compounds or in mixtures. Pursuing the hypothesis that endocrine active molecules could affect cell functions beyond the estrogen receptor-dependent cascade, experiments were performed comparing the MCF-7 cell line to the triple negative breast cancer cells MDA MB-231. Indeed, the four compounds functionally affected the motility and the adhesion of both cell types. These responses were coherent with rearrangements of the actin cytoskeleton and with the modulation of the expression of integrin β1 and cathepsin D. Mechanistically, molecular dynamics simulations confirmed a potential interaction with fragments of the α1 and β1 integrin subunits. In sum, dietary xenoestrogens proved effective in modifying the motility and adhesion of breast cancer cells, as predictive end points for metastatic behavior in vitro. These effects were measurable after short incubation times (1 or 8 h) and contribute to shed novel light on the activity of compounds with hormonal mimicry potential in breast cancer progression.

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Ionizable Cationic Lipids and Helper Lipids Synergistically Contribute to RNA Packing and Protection in Lipid-Based Nanomaterials

Lipid-based nanomaterials are used as a common delivery vehicle for RNA therapeutics. They typically include a formulation containing ionizable cationic lipids, cholesterol, phospholipids, and a small molar fraction of PEGylated lipids. The ionizable cationic lipids are considered a crucial element of the formulation for the way they mediate interactions with the anionic RNA as a function of pH. Here, we show, by means of molecular dynamics simulation of lipid formulations containing two different ionizable cationic lipids (DLinDMA and DLinDAP), that the direct interactions of those lipids with RNA, taken alone, may not be sufficient to determine the level of protection and packaging of mRNA. Our simulations help and highlight how the collective behavior of the lipids in the formulation, which determines the ability to envelop the RNA, and the level of hydration of the lipid-RNA interface may also play a significant role. This allows the drawing of a hypothesis about the experimentally observed differences in the transfection efficiency of the two ionizable cationic lipids.

The Quality of Embedding Charges Is Critical for Convergence of Many-Body Expansions When BSSE Is Absent

There is conflicting evidence in the literature concerning the benefits of charge embedding on the convergence of many-body expansions (MBEs). Using a systematic series of water and ion-water clusters of varying size, this study indicates that the effects of charge embedding can be masked by basis set superposition error (BSSE). When BSSE is removed, this study demonstrates that charge embedding can significantly accelerate MBE convergence, where the electrostatically embedded two-body method, EE-MBE(2), can often yield accuracy close to the four-body method, MBE(4). Contrary to previous studies on smaller systems, this work shows that the performance of EE-MBE is highly sensitive to the charge model, with the best performance obtained when the natural population analysis (NPA) charge model is used and generated at the same level of theory used in the subsystem and supersystem calculations. It was demonstrated that the "3c" composite method, PBEh-3c, yields NPA atomic charges that are in excellent agreement with those obtained from supersystem density functional theory calculations. The linear-scaling X-Polarization method provides a more general approach to estimating these supersystem QM atomic charges, but its performance depends on how the fragments are defined.

Design of stimuli-responsive minimalist heptad surfactants for stable emulsions

Peptide surfactants have been extensively investigated with various applications in detergents, foods, and pharmaceutics due to their biodegradability, biocompatibility, and customizable structures. Traditional peptide surfactants are often designed in a head-to-tail fashion mimicking chemical surfactants. Alternatively, a side-by-side design pattern based on heptad repeats offers an approach to designing peptide surfactants. However, minimalist peptide design using a single heptad for stabilizing interfaces remains largely unexplored. Here, we design four heptad surfactants (AM1.2, 6H, 6H7K, and HK) responsive to metal ions and compare their emulsification performance with a three-heptad peptide, AM1. Among them, the HK peptide generates emulsions exhibiting good stability over months. We further optimize factors such as buffering salts, ionic strength, and emulsion dilutions to uncover their impacts on emulsion properties. Our findings deepen the understanding of emulsion properties and provide practical insights for characterizing peptide-based emulsions, paving the way for their broader utilization in diverse applications.

Dynamic formation of the protein-lipid prefusion complex

Synaptic vesicles (SVs) fuse with the presynaptic membrane (PM) to release neuronal transmitters. The SV protein synaptotagmin 1 (Syt1) serves as a Ca2+ sensor for evoked fusion. Syt1 is thought to trigger fusion by penetrating the PM upon Ca2+ binding; however, the mechanistic detail of this process is still debated. Syt1 interacts with the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) complex, a coiled-coil four-helical bundle that enables the SV-PM attachment. The SNARE-associated protein complexin (Cpx) promotes Ca2+-dependent fusion, possibly interacting with Syt1. We employed all-atom molecular dynamics to investigate the formation of the Syt1-SNARE-Cpx complex interacting with the lipid bilayers of the PM and SVs. Our simulations demonstrated that the PM-Syt1-SNARE-Cpx complex can transition to a "dead-end" state, wherein Syt1 attaches tightly to the PM but does not immerse into it, as opposed to a prefusion state, which has the tips of the Ca2+-bound C2 domains of Syt1 inserted into the PM. Our simulations unraveled the sequence of Syt1 conformational transitions, including the simultaneous docking of Syt1 to the SNARE-Cpx bundle and the PM, followed by Ca2+ chelation and the penetration of the tips of Syt1 domains into the PM, leading to the prefusion state of the protein-lipid complex. Importantly, we found that direct Syt1-Cpx interactions are required to promote these transitions. Thus, we developed the all-atom dynamic model of the conformational transitions that lead to the formation of the prefusion PM-Syt1-SNARE-Cpx complex. Our simulations also revealed an alternative dead-end state of the protein-lipid complex that can be formed if this pathway is disrupted.

Exploration of Tertiary Structure in Sequence-Defined Polymers Using Molecular Dynamics Simulations

Peptoids are a class of sequence-defined biomimetic polymers with peptide-like backbones and side chains located on backbone nitrogens rather than alpha carbons. These materials demonstrate a strong ability for precise control of single-chain structure, multiunit self-assembly, and macromolecular assembly through careful tuning of sequence due to the diversity of available side chains, although the driving forces behind these assemblies are often not understood. Prior experimental work has shown that linked 15mer peptoids can mimic the protein helical hairpin structure by leveraging the chirality-inducing nature of bulky side chains and hydrophobicity, but there are still gaps in our understanding of the relationship between sequence, stability, and particular secondary or tertiary structure. We present a molecular dynamics (MD) study on the folding behavior of these polymers into hairpins, discussing the differences in structure from sequences with various characteristics in water and acetonitrile, and then compare the handedness preference of common helical motifs between solvents.

Mechanistic insights into the orthogonal functionality of an AHL-mediated quorum-sensing circuit in Yersinia pseudotuberculosis

YpsR, a pivotal regulatory protein in the quorum-sensing (QS) of Yersinia pseudotuberculosis(Y. pstb), is essential for molecular signaling, yet its molecular mechanisms remain poorly understood. Herein, this study systematically investigates the interactions between YpsR and acyl-homoserine lactones (AHLs), shedding light on the selective mechanism of YpsR to various AHL molecules. Using molecular docking and surface plasmon resonance (SPR) analysis, we confirmed YpsR's binding affinities, with the strongest observed for 3OC6-HSL, which notably inhibited Y. pstb growth. Additionally, we engineered a whole-cell biosensor based on YpsR-AHL interaction, which exhibited sensitivity to the signal molecule 3OC6-HSL produced by Y. pstb. Furthermore, key YpsR residues (S32, Y50, W54, D67) involved in AHL binding were identified and validated. Overall, this research elucidates the mechanisms of QS signal recognition in Y. pstb, providing valuable insights that support the development of diagnostic tools for detecting Y. pstb infections.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

Cosolvent Molecular Dynamics Applied to DPP4, DPP8 and DPP9: Reproduction of Important Binding Features and Use in Inhibitor Design

We present our efforts in computational drug design against dipeptidyl peptidase 4 (DPP4), DPP8 and DPP9. We applied cosolvent molecular dynamics (MD) simulations to these three protein targets of interest. Our primary motivation is the growing interest in DPP8 and DPP9 as emerging drug targets. Due to the high similarity between DPP4, DPP8 and DPP9, DPP4 was also included in these analyses. The cosolvent molecular dynamics simulations reproduce key ligand binding features and known binding pockets, while also highlighting interesting fragment positions for future ligand optimization. The resulting fragment maps from the cosolvent molecular dynamics are freely available for use in future research (https://github.com/UAMC-Olivier/DPP489_cosolvent_MD/). Detailed instructions for easy visualization of the fragment maps are provided, ensuring that the results are usable by both computational and medicinal chemists. Additionally, we used the fragment maps to search for the binding pockets with significant potential using an algorithmic approach combining top fragment locations. To discover novel binding scaffolds, a limited pharmacophore screening was performed, where the pharmacophores were based on the analyses of the cosolvent simulations. Unfortunately, inhibitory potencies were in the higher micromolar range, but we optimized the resulting scaffolds in silico using relative binding free energy calculations for future inhibitor design and synthesis.

Elucidation of the noncovalent interactions driving enzyme activity guides branching enzyme engineering for α-glucan modification

Branching enzymes (BEs) confer to α-glucans, the primary energy-storage reservoir in nature, a variety of features, like slow digestion. The full catalytic cycle of BEs can be divided in six steps, namely two covalent catalytic steps involving glycosylation and transglycosylation, and four noncatalytic steps involving substrate binding and transfers (SBTs). Despite the ever-growing wealth of biochemical and structural information on BEs, clear mechanistic insights into SBTs from an industrial-performance perspective are still missing. Here, we report a Rhodothermus profundi BE (RpBE) endowed with twice as much enzymatic activity as the Rhodothermus obamensis BE currently used in industry. Furthermore, we focus on the SBTs for RpBE by means of large-scale computations supported by experiment. Engineering of the crucial positions responsible for the initial substrate-binding step improves enzymatic activity significantly, while offering a possibility to customize product types. In addition, we show that the high-efficiency substrate-transfer steps preceding glycosylation and transglycosylation are the main reason for the remarkable enzymatic activity of RpBE, suggestive of engineering directions for the BE family.

Probing the Origins of the Disorder-to-Order Transition of a Modified Cholesterol in Ternary Lipid Bilayers

In a recent study, spectroscopic observations of modified cholesterol in both lipid-coated nanoparticles and liposomes provided evidence for a disorder-to-order orientational transition with increasing temperature. Below a critical temperature, in a membrane composed of modified cholesterol, saturated (DPPC) lipid, and anionic (DOPS) lipid, a roughly equal population of head-out and head-in conformations was observed. Surprisingly, as temperature was increased the modified cholesterol presented an abrupt transition to a population of all head-in orientations. Additionally, when saturated DPPC lipids were replaced by unsaturated DOPC the disorder-to-order transition was eliminated. To gain insight into this curious transition, we use all-atom molecular dynamics simulations to characterize the structure and fluctuations of lipid bilayers composed of saturated and unsaturated lipids, in the presence of normal and modified cholesterol. Free energy differences between head-out and head-in conformations are computed as a function of varying lipid membrane composition for normal and modified cholesterol. In bilayers primarily composed of DPPC, the orientation of modified cholesterol is observed to depend sensitively on the orientation of the surrounding normal or modified cholesterol molecules, suggesting cooperative Ising-like interactions favoring an ordered state. In bilayers primarily composed of DOPC, spontaneous flip-flop of modified cholesterol is observed, consistent with the measured small free energy barrier separating the head-in and head-out orientations. This combined experimental and computational study effectively characterizes the orientational dimorphism and provides novel insight into the fundamental nature of cholesterol interactions in membrane.

Molecular permeation through large pore channels: computational approaches and insights

Computational methods such as molecular dynamics (MD) have illuminated how single-atom ions permeate membrane channels and how selectivity among them is achieved. Much less is understood about molecular permeation through eukaryotic channels that mediate the flux of small molecules (e.g. connexins, pannexins, LRRC8s, CALHMs). Here we describe computational methods that have been profitably employed to explore the movements of molecules through wide pores, revealing mechanistic insights, guiding experiments, and suggesting testable hypotheses. This review illustrates MD techniques such as voltage-driven flux, potential of mean force, and mean first-passage-time calculations, as applied to molecular permeation through wide pores. These techniques have enabled detailed and quantitative modeling of molecular interactions and movement of permeants at the atomic level. We highlight novel contributors to the transit of molecules through these wide pathways. In particular, the flexibility and anisotropic nature of permeant molecules, coupled with the dynamics of pore-lining residues, lead to bespoke permeation dynamics. As more eukaryotic large-pore channel structures and functional data become available, these insights and approaches will be important for understanding the physical principles underlying molecular permeation and as guides for experimental design.

On the Control of Directionality of Myosin

The origin of the unique directionality of myosin has been a problem of fundamental and practical importance. This work establishes in a conclusive way that the directionality is controlled by tuning the barrier for the rate-determining step, namely, the ADP release step. This conclusion is based on exploring the molecular origin behind the reverse directionality of myosins V and VI and the determination of the origin of the change in the barriers of the ADP release for the forward and backward motions. Our investigation is performed by combining different simulation methods such as steer molecular dynamics (SMD), umbrella sampling, renormalization method, and automated path searching method. It is found that in the case of myosin V, the ADP release from the postrigor (trailing head) state overcomes a lower barrier than the prepowerstroke (leading head) state, which is also evident from experimental observation. In the case of myosin VI, we noticed a different trend when compared to myosin V. Since the directionality of myosins V and VI follows a reverse trend, we conclude that such differences in the directionality are controlled by the free energy barrier for the ADP release. Overall, the proof that the directionality of myosin is determined by the activation barrier of the rate-determining step in the cycle, rather than by some unspecified dynamical effects, has general importance.

Introductory Tutorials for Simulating Protein Dynamics with GROMACS

Atomistic molecular dynamics (MD) simulations have become an indispensable tool for investigating the structure, dynamics, and energetics of biomolecules. Continual optimization of software algorithms and hardware has enabled investigators to access biologically relevant time scales in feasible amounts of computing time. Given the widespread use and utility of MD simulations, there is considerable interest in learning essential skills in performing them. Here, we present a set of introductory tutorials for performing MD simulations of proteins in the popular, open-source GROMACS package. Three exercises are detailed, including simulating a single protein, setting up a protein complex, and performing umbrella sampling simulations to model the unfolding of a short polypeptide. Essential features and input settings are illustrated throughout. The purpose of these tutorials is to provide new users with a general understanding of foundational workflows, from which they can design their own simulations.

Buffer Screening of Protein Formulations Using a Coarse-Grained Protocol Based on Medicinal Chemistry Interactions

In drug and vaccine development, the designed protein formulation should be highly stable against the temperature, pH, buffer, excipients, and other environmental settings. Similarly, in a sensing unit, one needs to know how strongly two biomolecules bind to guide the design of the biorecognition unit accordingly. Typically, the community performs a series of experiments to thoroughly examine the parameter space, the so-called design-of-experiment (DoE) method, to identify the optimal formulation conditions. Unfortunately, extensive physical testing entails high costs, repeatability issues, and a lack of in-depth knowledge of the underlying mechanisms that affect the final outcome. To address these challenges, we developed a physics-based simulation protocol for buffer screening of protein formulations. We are introducing a coarse-grained molecular simulation protocol that consists of six different interactions. The so-called medicinal chemistry interactions (electrostatics, hydrophobicity, hydrogen bonding propensity, disulfide bonding, and water-water) are based on the physical nature of the protein's amino acid and the partitioning/polarity of any other chemical constituent. The protocol is applied in immunoglobulin-based monoclonal antibodies. We have analyzed the protein behavior as a function of acidity (pH) to discover the isoelectric point by solving the Poisson-Boltzmann equation in a mesoscale grid. To identify the conditions under which the protein oligomerizes in a given buffer, pH, temperature, and ionic strength, we are performing dissipative particle dynamics (DPD) simulations. The protocol allows researchers to reach the high time/space scales required to study protein formulations in their full complexity. Combined with the disruptive protein folding artificial intelligence (AI) algorithms that have been recently developed, the protocol creates a powerful digital framework for cultivating advanced pharmaceutical and biological applications.

Exploring novel natural compound-based therapies for Duchenne muscular dystrophy management: insights from network pharmacology, QSAR modeling, molecular dynamics, and free energy calculations

Muscular dystrophies encompass a heterogeneous group of rare neuromuscular diseases characterized by progressive muscle degeneration and weakness. Among these, Duchenne muscular dystrophy (DMD) stands out as one of the most severe forms. The present study employs an integrative approach combining network pharmacology, quantitative structure-activity relationship (QSAR) modeling, molecular dynamics (MD) simulations, and free energy calculations to identify potential therapeutic targets and natural compounds for DMD. Upon analyzing the GSE38417 dataset, it was found that individuals with DMD exhibited 290 upregulated differentially expressed genes (DEGs) compared to healthy controls. By utilizing gene ontology (GO) and protein-protein interaction (PPI) network analysis, this study provides insights into the functional roles of the identified DEGs, identifying ten hub genes that play a critical role in the pathology of DMD. These key genes include DMD, TTN, PLEC, DTNA, PKP2, SLC24A, FBXO32, SNTA1, SMAD3, and NOS1. Furthermore, through the use of ligand-based pharmacophore modeling and virtual screening, three natural compounds were identified as potential inhibitors. Among these, compounds 3874518 and 12314417 have demonstrated significant promise as an inhibitor of the SMAD3 protein, a crucial factor in the fibrotic and inflammatory mechanisms associated with DMD. The therapeutic potential of the compounds was further supported by molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis. These findings suggest that the compounds are viable candidates for experimental validation against DMD.

Regulatory Role of IL6 in Immune-Related Adverse Events during Checkpoint Inhibitor Treatment in Melanoma

The landscape of clinical management for metastatic melanoma (MM) and other solid tumors has been modernized by the advent of immune checkpoint inhibitors (ICI), including programmed cell death-1 (PD-1), programmed cell death-ligand 1 (PD-L1), and cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitors. While these agents demonstrate efficacy in suppressing tumor growth, they also lead to immune-related adverse events (irAEs), resulting in the exacerbation of autoimmune diseases such as rheumatoid arthritis (RA), ulcerative colitis (UC), and Crohn's disease (CD). The immune checkpoint inhibitors offer promising advancements in the treatment of melanoma and other cancers, but they also present significant challenges related to irAEs and autoimmune diseases. Ongoing research is crucial to better understand these challenges and develop strategies for mitigating adverse effects while maximizing therapeutic benefits. In this manuscript, we addressed this challenge using network-based approaches by constructing and analyzing the molecular and signaling networks associated with tumor-immune crosstalk. Our analysis revealed that IL6 is the key regulator responsible for irAEs during ICI therapies. Furthermore, we conducted an integrative network and molecular-level analysis, including virtual screening, of drug libraries, such as the Collection of Open Natural Products (COCONUT) and the Zinc15 FDA-approved library, to identify potential IL6 inhibitors. Subsequently, the compound amprenavir was identified as the best molecule that may disrupt essential interactions between IL6 and IL6R, which are responsible for initiating the signaling cascades underlying irAEs in ICI therapies.

Differentiating human phospholipase A2's activity toward phosphatidylinositol, phosphatidylinositol phosphate and phosphatidylinositol bisphosphate

Phospholipase A2's (PLA2's) constitute a superfamily of enzymes that hydrolyze the sn-2 fatty acyl chain on glycerophospholipids. We have previously reported that each PLA2 Type shows a unique substrate specificity for the molecular species it hydrolyzes, especially the acyl chain that is cleaved from the sn-2 position and to some extent the polar group. However, phosphatidylinositol (PI) and PI phosphates (PIPs) have not been as well studied as substrates as other phospholipids because the PIPs require adaptation of the standard analysis methods, but they are important in vivo. We determined the in vitro activity of the three major types of human PLA2's, namely the cytosolic (c), calcium-independent (i), and secreted (s) PLA2's toward PI, PI-4-phosphate (PI(4)P), and PI-4,5-bisphosphate (PI(4,5)P2). The in vitro assay revealed that Group IVA cPLA2 (GIVA cPLA2) showed relatively high activity toward PI and PI(4)P among the tested PLA2's; nevertheless, the highly hydrophilic headgroup disrupted the interaction between the lipid surface and the enzyme. GIVA cPLA2 and GVIA iPLA2 showed detectable activity toward PI(4,5)P2, but it appeared to be a poorer substrate for all of the PLA2's tested. Furthermore, molecular dynamics (MD) simulations demonstrated that Thr416 and Glu418 of GIVA cPLA2 contribute significantly to accommodating the hydrophilic head groups of PI and PI(4)P, which could explain some selectivity for PI and PI(4)P. These results indicated that GIVA cPLA2 can accommodate PI and PI(4)P in its active site and hydrolyze them, suggesting that the GIVA cPLA2 may best account for the PI and PIP hydrolysis in living cells.

Reorientation of interfacial water molecules during melting of brain sphingomyelin is associated with the phase transition of its C24:1 sphingomyelin lipids

Melting of brain sphingomyelin (bSM) manifests as a broad feature in the DSC curve that encompasses the temperature range of 25 - 45 °C, with two distinguished maxima originating from the phase transitions of two the most abundant components: C24:1 (Tm,1) and C18:0 (Tm,2). While C24:1/C18:0 sphingomyelin transforms from the gel/ripple phase to the fluid/fluid phase, the dynamics of water molecules in the interfacial layer remain completely unknown. Therefore, we carried out a calorimetric (DSC), spectroscopic (temperature-dependent UV-Vis and fluorescence) and MD simulation study of bSM in the absence/presence of Laurdan® (bSM ± L) suspended in Britton-Robinson buffer with three different pH values, 4 (BRB4), 7 (BRB7) and 9 (BRB9), and of comparable ionic strength (I = 100 mM). According to DSC, T̅m, 1 (≈ 34.5 °C/≈ 32.1 °C) and T̅m, 2 (≈ 38.0 °C/≈ 37.2 °C) of bSM suspended in BRB4, BRB7, and BRB9 in the absence/presence of Laurdan® are found to be practically pH-independent. Turbidity-based data (UV-Vis) detected both qualitative and quantitative differences in the response of bSM suspended in BRB4/BRB7/BRB9 (T̅m: ∼ 35 °C/32.0 ± 0.2 °C/36.4 ± 0.4), suggesting an intricate interplay of weakening of van der Waals forces between their hydrocarbon chains and of increased hydration in the polar headgroups region during melting. The temperature-dependent response of Laurdan® reported a discontinuous, pH-dependent change in the reorientation of interfacial water molecules that coincides with the melting of C24:1 lipids (on average, T̅m (LTC/HTC): ≈ 31.8 °C/30.6 °C/30.5 °C). MD simulations elucidated the impact of Laurdan® on a change in the physicochemical properties of bSM lipids and characterized the hydrogen bond network at the interface at 20 °C and 50 °C.

Ergosterol and its metabolites as agonists of Liver X receptor and their anticancer potential in colorectal cancer

Aberrant cholesterol homeostasis is a well-recognized hallmark of cancer and is implicated in metastasis as well as chemotherapeutic resistance, the two major causes of cancer associated mortality. Liver X receptors (LXRs) are the key transcription factors that induce cholesterol efflux via enhancing the expression of ABCA1 and ABCG1. Therefore, a comprehensive analysis of several novel sterols namely ergosta-7,22,24(28)-trien-3β-ol (Erg1), ergosta-5,22,25-trien-3-ol (Erg2), ergosta-5,7,22,24(28)-tetraen-3β-ol (Erg3), and ergosta-7,22-dien-3β-ol (Erg4) as LXR agonists has been performed. Molecular docking studies have shown that these sterols possess higher binding affinities for LXRs as compared to the reference ligands (GW3965 and TO901317) and also formed critical activating interactions. Molecular dynamic (MD) simulations further confirmed that docking complexes made of these sterols possess significant stability. To assess the extent of LXR activation, ABCA1 promoter was cloned into luciferase reporter plasmid and transfected into HCT116 cells. It was observed that treatment with Erg, Erg2 and Erg4 led to a significant LXR activation with an EC50 of 5.64 µM, 4.83 and 3.03 µM respectively. Furthermore, a significant increase in mRNA expression of NR1H2 and LXR target genes i.e. ABCA1, ABCG1 and ApoE was observed upon Erg treatment. Flow cytometric analysis have revealed a significant increase in the accumulation of ABCA1 upon Erg treatment. Cytotoxicity studies conducted on colorectal cancer cell and normal epithelial cell line showed that these sterols are selectively toxic towards cancer cells. Taken together, our findings suggests that ergosterol activates LXRs, have significant anticancer activity and could be a likely candidate to manage aberrant cholesterol homeostasis.

Potential protein kinase inhibitors that target G-quadruplex DNA structures in the human telomeric regions

Telomeric regions contain Guanine-rich sequences arranged in a planar manner and connected by Hoogsteen hydrogen bonds that can fold into G-quadruplex (G4) DNA structures, and can be stabilized by monovalent metal cations. The presence of G4 DNA holds significance in cancer-related processes, especially due to their regulatory potential at transcriptional and translational levels of oncogene and tumor suppressor genes. The objective of this current research is to explore the evolving realm of FDA-approved protein kinase inhibitors, with a specific emphasis on their capacity to stabilize the G4 DNA structures formed at the human telomeric regions. This involves investigating the possibility of repurposing FDA-approved protein kinase inhibitors as a novel approach for targeting multiple cancer types. In this context, we have selected 16 telomeric G4 DNA structures as targets and 71 FDA-approved small-molecule protein kinase inhibitors as ligands. To investigate their binding affinities, molecular docking of human telomeric G4 DNA with nuclear protein kinase inhibitors and their corresponding co-crystalized ligands were performed. We found that Ponatinib and Lapatinib interact with all the selected G4 targets, the binding free energy calculations, and molecular dynamic simulations confirm their binding efficacy and stability. Thus, it is hypothesized that Ponatinib and Lapatinib may stabilize human telomeric G4 DNA in addition to their ability to inhibit BCR-ABL and the other members of the EGFR family. As a result, we also hypothesize that the stabilization of G4 DNA might represent an additional underlying mechanism contributing to their efficacy in exerting anti-cancer effects.

Exploring the antiviral inhibitory activity of Niloticin against the NS2B/NS3 protease of Dengue virus (DENV2)

Dengue virus (DENV2) is the cause of dengue disease and a worldwide health problem. DENV2 replicates in the host cell using polyproteins such as NS3 protease in conjugation with NS2B cofactor, making NS3 protease a promising antiviral drug-target. This study investigated the efficacy of 'Niloticin' against NS2B/NS3-protease. In silico and in vitro analyses were performed which included interaction of niloticin with NS2B/NS3-protease, protein stability and flexibility, mutation effect, betweenness centrality of residues and analysis of cytotoxicity, protein expression and WNV NS3-protease activity. Similar like acyclovir, niloticin forms strong H-bonds and hydrophobic interactions with residues LEU149, ASN152, LYS74, GLY148 and ALA164. The stability of the niloticin-NS2B/NS3-protease complex was found to be stable compared to the apo NS2B/NS3-protease in structural deviation, PCA, compactness and FEL analysis. The IC50 value of niloticin was 0.14 μM in BHK cells based on in vitro cytotoxicity analysis and showed significant activity at 2.5 μM in a concentration-dependent manner. Western blotting and qRT-PCR analyses showed that niloticin reduced DENV2 protein transcription in a dose-dependent manner. Besides, niloticin confirmed the inhibition of NS3-protease by the SensoLyte 440 WNV protease detection kit. These promising results suggest that niloticin could be an effective antiviral drug against DENV2 and other flaviviruses.

An in-silico scaffold- hopping approach to design novel inhibitors against gp130: A potential therapeutic application in cancer and Covid-19

An upregulation of the gp130-signalling cascade has been reported in multiple cancers, making gp130 an attractive target for the development of anticancer drugs. An inverted-funnel-like approach was utilised along with various structure-based drug designing strategies to discover and optimise novel potential inhibitors of gp130. The study resulted in the discovery of 2 ligands- 435 and 510, both of which exhibit a very high-binding affinity towards the gp130 D1 domain which controls cytokine recognition and interaction thus being involved in complexation. The two resulting complexes remained stable over time with the ligands maintaining a steady interaction with the target. This inference is drawn from their RMSD, Rg, SASA and RMSF analysis. We also tested the protein folding patterns based on their principal component analysis, energy of surface and landscape. The leads also displayed a more favourable ADMET profile than their parent compounds. The two lead candidates show a better therapeutic profile in comparison to the two existing drugs- bazedoxifene and raloxifene. Both these potential leads can be addressed for their activity in-vitro and can be used as a potential anti-cancer treatment as well as to combat Covid-19 related cytokine storm.

Computational Insights Into the Mechanism of EGCG's Binding and Inhibition of the TDP-43 Aggregation

Misfolding and aggregation of TAR DNA-binding protein, TDP-43, is linked to devastating proteinopathies such as ALS. Therefore, targeting TDP-43's aggregation is significant for therapeutics. Recently, green tea polyphenol, EGCG, was observed to promote non-toxic TDP-43 oligomer formation disallowing TDP-43 aggregation. Here, we investigated if the anti-aggregation effect of EGCG is mediated via EGCG's binding to TDP-43. In silico molecular docking and molecular dynamics (MD) simulation suggest a strong binding of EGCG with TDP-43's aggregation-prone C-terminal domain (CTD). Three replicas, each having 800 ns MD simulation of the EGCG-TDP-43-CTD complex, yielded a high negative binding free energy (ΔG) inferring a stable complex formation. Simulation snapshots show that EGCG forms close and long-lasting contacts with TDP-43's Phe-313 and Ala-341 residues, which were previously identified for monomer recruitment in CTD's aggregation. Notably, stable physical interactions between TDP-43 and EGCG were also detected in vitro using TTC staining and isothermal titration calorimetry which revealed a high-affinity binding site of EGCG on TDP-43 (Kd, 7.8 μM; ΔG, -6.9 kcal/mol). Additionally, TDP-43 co-incubated with EGCG was non-cytotoxic when added to HEK293 cells. In summary, EGCG's binding to TDP-43 and blocking of residues important for aggregation can be a possible mechanism of its anti-aggregation effects on TDP-43.

Repurposing FDA approved drugs against Sterol C-24 methyltransferase of Leishmania donovani: A dual in silico and in vitro approach

Leishmaniasis is a disease caused by the parasite Leishmania donovani affecting populations belonging to developing countries. The present study explores drug repurposing as an innovative strategy to identify new uses for approved clinical drugs, reducing the time and cost required for drug discovery. The three-dimensional structure of Leishmania donovani Sterol C-24 methyltransferase (LdSMT) was modeled and 1615 FDA-approved drugs from the ZINC database were computationally screened to identify the potent leads. Fulvestrant, docetaxel, indocyanine green, and iohexol were shortlisted as potential leads with the highest binding affinity and fitness scores for the concerned pathogenic receptor. Molecular dynamic simulation studies showed that the macromolecular complexes of indocyanine green and iohexol with LdSMT remained stable throughout the simulation and can be further evaluated experimentally for developing an effective drug. The proposed leads have further demonstrated promising safety profiles during cytotoxicity analysis on the J774.A1 macrophage cell line. Mechanistic analysis with these two drugs also revealed significant morphological alterations in the parasite, along with reduced intracellular parasitic load. Overall, this study demonstrates the potential of drug repurposing in identifying new treatments for leishmaniasis and other diseases affecting developing countries, highlighting the importance of considering approved clinical drugs for new applications.

Polymyxin B1 in the Escherichia coli inner membrane: A complex story of protein and lipopolysaccharide-mediated insertion

The rise in multi-drug resistant Gram-negative bacterial infections has led to an increased need for "last-resort" antibiotics such as polymyxins. However, the emergence of polymyxin-resistant strains threatens to bring about a post-antibiotic era. Thus, there is a need to develop new polymyxin-based antibiotics, but a lack of knowledge of the mechanism of action of polymyxins hinders such efforts. It has recently been suggested that polymyxins induce cell lysis of the Gram-negative bacterial inner membrane (IM) by targeting trace amounts of lipopolysaccharide (LPS) localized there. We use multiscale molecular dynamics (MD), including long-timescale coarse-grained (CG) and all-atom (AA) simulations, to investigate the interactions of polymyxin B1 (PMB1) with bacterial IM models containing phospholipids (PLs), small quantities of LPS, and IM proteins. LPS was observed to (transiently) phase separate from PLs at multiple LPS concentrations, and associate with proteins in the IM. PMB1 spontaneously inserted into the IM and localized at the LPS-PL interface, where it cross-linked lipid headgroups via hydrogen bonds, sampling a wide range of interfacial environments. In the presence of membrane proteins, a small number of PMB1 molecules formed interactions with them, in a manner that was modulated by local LPS molecules. Electroporation-driven translocation of PMB1 via water-filled pores was favored at the protein-PL interface, supporting the 'destabilizing' role proteins may have within the IM. Overall, this in-depth characterization of PMB1 modes of interaction reveals how small amounts of mislocalized LPS may play a role in pre-lytic targeting and provides insights that may facilitate rational improvement of polymyxin-based antibiotics.

Flow-based bioconjugation of coumarin phosphatidylethanolamine probes: Optimised synthesis and membrane molecular dynamics studies

A series of phosphatidylethanolamine fluorescent probes head-labelled with 3-carboxycoumarin was prepared by an improved bioconjugation approach through continuous flow synthesis. The established procedure, supported by a design of experiment (DoE) set-up, resulted in a significant reduction in the reaction time compared to the conventional batch method, in addition to a minor yield increase. The characterization of these probes was enhanced by an in-depth molecular dynamics (MD) study of the behaviour of a representative probe of this family, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine labelled with 3-carboxycoumarin (POPE-COUM), in bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/1-stearoyl-2-linoleoyl-sn-glycero-3-phosphocholine (SLPC) 2:1, mimicking the composition of the egg yolk lecithin membranes recently used experimentally by our group to study POPE-COUM as a biomarker of the oxidation state and integrity of large unilamellar vesicles (LUVs). The MD simulations revealed that the coumarin group is oriented towards the bilayer interior, leading to a relatively internal location, in agreement with what is observed in the nitrobenzoxadiazole fluorophore of commercial head-labelled NBD-PE probes. This behaviour is consistent with the previously stated hypothesis that POPE-COUM is entirely located within the LUVs structure. Hence, the delay on the oxidation of the probe in the oxygen radical absorbance capacity (ORAC) assays performed is related with the inaccessibility of the probe until alteration of the LUV structure occurs. Furthermore, our simulations show that POPE-COUM exerts very little global and local perturbation on the host bilayer, as evaluated by key properties of the unlabelled lipids. Together, our findings establish PE-COUM as suitable fluorescent lipid analogue probes.

Identification of Novel PI3Kα Inhibitor Against Gastric Cancer: QSAR-, Molecular Docking-, and Molecular Dynamics Simulation-Based Analysis

Gastric cancer (GC) is a malignant tumor with global incidence and death ranking fifth and fourth, respectively. GC patients nevertheless have a poor prognosis despite the effectiveness of more advanced chemotherapy and surgical treatment options. The second most frequently mutated gene in GC is PI3Kalpha, a confirmed oncogene that results in abnormal PI3K/AKT/mTOR signaling, causing enhanced translation, proliferation, and survival, and is mutated in 7-25% of GC patients. The protein PI3Kalpha was targeted in the present study by utilizing machine learning (ML), molecular docking, and simulation. A total of 9214 molecules from the DrugBank database were chosen for the first screening. A training set for 6770 compounds tested against PI3Kalpha was assessed to create a quantitative structure-activity relationship-based machine learning model using five different classification algorithms: random forest, random tree, J48 pruned tree, decision stump, and REPTree. Furthermore, consideration was given to the random forest classifier for screening based on its performance index (Kappa statistics, ROC, and MCC). Overall, 1539 of the 9214 drug bank compounds were predicted to be active. Thereafter, three pharmacological filters, Lipinski's rule, Ghose filter, and Veber rule, were applied to test the drug-like properties of the screened compounds. Twenty-six of 1593 compounds showed excellent drug-like properties and were further considered for molecular docking. Thereafter, two compounds were screened as hits because they possessed the molecular docked position with the lowest binding energy and an excellent bonding profile. The binding stability of the selected compounds was further assessed through molecular dynamics simulations for up to 100 ns. Furthermore, compound 1-(3-(2,4-dimethylthiazol-5-YL)-4-oxo-2,4-dihydroindeno[1,2-C]pyrazol-5-YL)-3-(4-methylpiperazin-1-YL) urea was selected as a potential hit in the final screening by analyzing a number of parameters, including the Rg, RMSD, RMSF, H bonding, and SASA profile. Therefore, we conclude that compound 1-(3-(2, 4-dimethylthiazol-5-YL)-4-oxo-2,4-dihydroindeno[1,2-C]pyrazol-5-YL)-3-(4-methylpiperazin-1-YL) urea has efficient inhibitory potential against PI3Kalpha protein and could be utilized for the development of effective drugs against GC.

Effect of two activators on the gating of a K2P channel

TWIK-related potassium channel 1 (TREK1), a two-pore-domain mammalian potassium (K+) channel, regulates the resting potential across cell membranes, presenting a promising therapeutic target for neuropathy treatment. The gating of this channel converges in the conformation of the narrowest part of the pore: the selectivity filter (SF). Various hypotheses explain TREK1 gating modulation, including the dynamics of loops connecting the SF with transmembrane helices and the stability of hydrogen bond (HB) networks adjacent to the SF. Recently, two small molecules (Q6F and Q5F) were reported as activators that affect TREK1 by increasing its open probability in single-channel current measurements. Here, using molecular dynamics simulations, we investigate the effect of these ligands on the previously proposed modulation mechanisms of TREK1 gating compared to the apo channel. Our findings reveal that loop dynamics at the upper region of the SF exhibit only a weak correlation with permeation events/nonpermeation periods, whereas the HB network behind the SF appears more correlated. These nonpermeation periods arise from both distinct mechanisms: a C-type inactivation (resulting from dilation at the top of the SF), which has been described previously, and a carbonyl flipping in an SF binding site. We find that, besides the prevention of C-type inactivation in the channel, the ligands increase the probability of permeation by modulating the dynamics of the carbonyl flipping, influenced by a threonine residue at the bottom of the SF. These results offer insights for rational ligand design to optimize the gating modulation of TREK1 and related K+ channels.

Sorption of PFOS onto polystyrene microplastics potentiates synergistic toxic effects during zebrafish embryogenesis and neurodevelopment

Microplastics (MPs) have become an emerging anthropogenic pollutant, and their ability to sorb contaminants potentially enhances the threats to the ecosystem. Only a few studies are available to understand the combined effects of microplastics and other pollutants. The present study investigated the sorption of perfluorooctane sulfonic acid (PFOS) onto polystyrene microplastics (PS-MPs) at varying concentrations, using molecular dynamics simulation (MDS) to preliminarily explore the adsorption behavior. The MDS results revealed negative interaction energies between PFOS and PS-MPs, underscoring PS-MPs' role as a potential adsorbent for PFOS in an aqueous solution. Thereafter, zebrafish embryos were employed to explore the toxic effects of combined exposure to PS-MPs and PFOS. Fluorescence and Scanning Electron Microscopy (SEM) suggested PS-MP accumulation individually and in combination with PFOS on the embryonic chorion membrane. As a result, the exposed group showed increased inner pore size of the chorionic membrane and accelerated heartbeat, indicating hypoxic conditions and hindered gaseous exchange. PS-MPs aggravated the toxicity of PFOS during larval development manifested by delayed hatching rate, increased mortality, and malformation rate. Additionally, increased ROS accumulation and altered antioxidant enzymatic status were observed in all the exposed groups suggesting perturbation of the redox state. Additionally, co-exposure of zebrafish larvae to PS-MPs and PFOS resulted in an abrupt behavioral response, which decreased AChE activity and altered neurotransmitter levels. Taken together, our results emphasize that PS-MPs can act as a potential vector for PFOS, exerting synergistic toxic effects in the aquatic environment, and hence their health risks cannot be ignored.

Surface plasmon resonance, molecular docking, and molecular dynamics simulation studies of lysozyme interaction with tannic acid

Lysozyme (LZM) is an important enzyme in medicine and industry. Tannic acid (TA) is used in brewing, wine industry, and as a food flavor enhancer. In nutritional and food science, LZM interacts with TA, notably in wine and saliva. This study aimed to investigate the binding interaction between LZM and TA using surface plasmon resonance, molecular docking, and molecular dynamics simulation. Chicken egg white lysozyme (CEWLZM) was applied as a model protein. Tri-N-acetylchitotriose (NAG3), the known inhibitor of CEWLZM, was used in the redocking experiments to determine the precise binding location within the complex. The average binding energies obtained from docking NAG3 and tannic acid to the target structure of CEWLZM were found to be -6.46 ± 0.05 kcal/mol and -7.52 ± 0.39 kcal/mol, respectively. The binding free energy of the CEWLZM-TA complex was then calculated as -27.61 kcal/mol by MMPBSA based on MD simulation trajectories. The observed interactions between the ligands and the lysozyme structure were mainly driven by hydrophobic, van der Waals, and H-bond interactions formed by the active site residues. MD simulations showed consistent and satisfactory binding distances between CEWLZM and TA throughout the analysis. SPR analysis was performed using 1X PBS buffer (pH 7.4) as coupling and running buffers, 30 μL/min as flow rate, and 2.5 mg/mL CEWLZM. Serial concentrations of TA (20-150 μM) were injected through immobilized CEWLZM, and the K D value of CEWLZM-TA binding was obtained as 4.17 × 10-5 M. This study could enhance existing literature and pave the way for future research in food science and oral biology.

Mutational analysis of flavonol synthase of M. pinnata towards enhancement of binding affinity: a computational approach

Millettia pinnata is an important medicinal plant that has been used as a treatment of various diseases due to presence of wide range of pharmacological properties. The plant contains quercetin, kaempferol, karanjin, pongaglabrone, kanjone, kanugin, gammatin, pongaglabol, and other bioflavonoids. Kaempferol is a natural flavonol that shows many pharmacological properties including anti-inflammatory, antioxidant, anticancer, and antidiabetic activities etc. The enzyme flavonol synthase (FLS, EC 1.14.20.6) catalyses the conversion of dihydroflavonols to flavonols, i.e. biosynthesis of kaempferol from dihydrokaempferol. The current work examined the binding affinity-based approach to improve the enzyme catalytic activity using computational methods. Sequential site-directed mutagenesis was used to create four mutants with the goal to increase hydrogen bonds and further improving the ligand (dihydrokaempferol) binding efficiency. Simulations were done to monitor the stability of the mutants followed by molecular docking to confirm interactions with ligand. For structure validation, various dynamic analysis like RMSD, RMSF, ROG, SASA, H-bond, PCA, DCCM, and FEL were performed, which predicts the stability of wild-type (WT) proteins and mutants. The Mutant_2 and Mutant_3 showed maximum H-bonding and better stability than other mutants and WT that proved higher affinity suggesting improved catalysis. Mutant_2 and Mutant_3 exhibited binding affinities of -7.6 and -8.2 kcal/mol, respectively for the ligand. The outcome of present study will provide significant improvement in synthesis of kaempferol and other plant-based flavonoids.Communicated by Ramaswamy H. Sarma.

Biased Signaling Agonists Promote Distinct Phosphorylation and Conformational States of the Dopamine D3 Receptor

Biased agonists of G-protein-coupled receptors (GPCRs) have emerged as promising selective modulators of signaling pathways by offering therapeutic advantages over unbiased agonists to minimize side effects. The dopamine D3 receptor (D3R), a pivotal GPCR in the central nervous system, has gained significant attention as a therapeutic target for neurological diseases, including Parkinson's disease (PD), addiction, psychosis, depression, and anxiety. We have recently designed and tested SK609, a G-protein biased D3R selective agonist, and demonstrated its efficacy in reducing motor impairment and improving cognitive effects in a rodent model of PD. The molecular mechanism by which SK609 recruits G-protein but not β-arrestin pathways is poorly understood. Utilizing all-atom molecular dynamics simulations, we investigated the distinct conformational dynamics imparted by SK609 and the reference unbiased agonist Pramipexole (PRX). Results from these studies show that the flexibility of transmembrane 3 is key to unbiased signaling, with a ~30° and ~17° shift in tilt angle in the D3R-Gi and D3R-βarrestin2 complexes, respectively. Additionally, untargeted phosphoproteomics analysis reveals unique phosphorylation sites by SK609 and PRX in D3R. These results suggest that SK609 induces conformational changes and unique phosphorylation patterns that promote interactions with G-proteins and are not conducive for β-arrestin2 recruitment and signaling.

Structural basis for the rescue of hyperexcitable cells by the amyotrophic lateral sclerosis drug Riluzole

Neuronal hyperexcitability is a key element of many neurodegenerative disorders including the motor neuron disease Amyotrophic Lateral Sclerosis (ALS), where it occurs associated with elevated late sodium current (INaL). INaL results from incomplete inactivation of voltage-gated sodium channels (VGSCs) after their opening and shapes physiological membrane excitability. However, dysfunctional increases can cause hyperexcitability-associated diseases. Here we reveal the atypical binding mechanism which explains how the neuroprotective ALS-treatment drug riluzole stabilises VGSCs in their inactivated state to cause the suppression of INaL that leads to reversed cellular overexcitability. Riluzole accumulates in the membrane and enters VGSCs through openings to their membrane-accessible fenestrations. Riluzole binds within these fenestrations to stabilise the inactivated channel state, allowing for the selective allosteric inhibition of INaL without the physical block of Na+ conduction associated with traditional channel pore binding VGSC drugs. We further demonstrate that riluzole can reproduce these effects on a disease variant of the non-neuronal VGSC isoform Nav1.4, where pathologically increased INaL is caused directly by mutation. Overall, we identify a model for VGSC inhibition that produces effects consistent with the inhibitory action of riluzole observed in models of ALS. Our findings will aid future drug design and supports research directed towards riluzole repurposing.

An in silico design method of a peptide bioreceptor for cortisol using molecular modelling techniques

Cortisol is established as a reliable biomarker for stress prompting intensified research in developing wearable sensors to detect it via eccrine sweat. Since cortisol is present in sweat in trace quantities, typically 8-140 ng/mL, developing such biosensors necessitates the design of bioreceptors with appropriate sensitivity and selectivity. In this work, we present a systematic biomimetic methodology and a semi-automated high-throughput screening tool which enables rapid selection of bioreceptors as compared to ab initio design of peptides via computational peptidology. Candidate proteins from databases are selected via molecular docking and ranked according to their binding affinities by conducting automated AutoDock Vina scoring simulations. These candidate proteins are then validated via full atomistic steered molecular dynamics computations including umbrella sampling to estimate the potential of mean force using GROMACS version 2022.6. These explicit molecular dynamic calculations are carried out in an eccrine sweat environment taking into consideration the protein dynamics and solvent effects. Subsequently, we present a candidate baseline peptide bioreceptor selected as a contiguous sequence of amino acids from the selected protein binding pocket favourably interacting with the target ligand (i.e., cortisol) from the active binding site of the proteins and maintaining its tertiary structure. A unique cysteine residue introduced at the N-terminus allows orientation-specific surface immobilization of the peptide onto the gold electrodes and to ensure exposure of the binding site. Comparative binding affinity simulations of this peptide with the target ligand along with commonly interfering species e.g., progesterone, testosterone and glucose are also presented to demonstrate the validity of this proposed peptide as a candidate baseline bioreceptor for future cortisol biosensor development.

Identifying Artifacts from Large Library Docking

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown the hit lists can become dominated by rare artifacts that cheat our scoring functions. Here, we investigate rescoring top-ranked docked molecules with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation as cross-filters. In retrospective studies, this approach deprioritized high-ranking nonbinders for nine targets while leaving true ligands relatively unaffected. We tested the method prospectively against hits from docking against AmpC β-lactamase. We prioritized 128 high-ranking molecules for synthesis and testing, a mixture of 39 molecules flagged as likely cheaters and 89 that were plausible inhibitors. None of the predicted cheating compounds inhibited AmpC detectably, while 57% of the 89 plausible compounds did so. As our libraries continue to grow, deprioritizing docking artifacts by rescoring with orthogonal methods may find wide use.

Low-Basicity 5-HT6 Receptor Ligands from the Group of Cyclic Arylguanidine Derivatives and Their Antiproliferative Activity Evaluation

The serotonin 5-HT6 receptor (5-HT6R), expressed almost exclusively in the brain, affects the Cdk5 signaling as well as the mTOR pathway. Due to the association of 5-HT6R signaling with pathways involved in cancer progression, we decided to check the usefulness of 5-HT6R ligands in the treatment of CNS tumors. For this purpose, a new group of low-base 5-HT6R ligands was developed, belonging to arylsulfonamide derivatives of cyclic arylguanidines. The selected group of molecules was also tested for their antiproliferative activity on astrocytoma (1321N1) and glioblastoma (U87MG, LN-229, U-251) cell lines. Some of the molecules were subjected to ADMET tests in vitro, including lipophilicity, drug binding to plasma proteins, affinity for phospholipids, drug-drug interaction (DDI), the penetration of the membrane (PAMPA), metabolic stability, and hepatotoxicity as well as in vivo cardiotoxicity in the Danio rerio model. Two antagonists with an affinity constant Ki < 50 nM (PR 68Ki = 37 nM) were selected. These compounds were characterized by very high selectivity. An analysis of pharmacokinetic parameters for the lead compound PR 68 confirmed favorable properties for administration, including passive diffusion and acceptable metabolic stability (metabolized in 49%, MLMs). The compound did not exhibit the potential for drug-drug interactions.

In-silico characterization of a hypothetical protein of Sulfobacillus sp. hq2 for degradation of phthalate diesters

Phthalate plasticizers are hazardous compounds capable of causing endocrine disruption, cancers, and developmental disorders. Phthalate diesters are commonly used plasticizers in plastic products (PVC pipes) that leach out into the environment due to changes in temperature, pressure, and pH, posing harmful effects on different life forms. Bioremediation of phthalate diesters utilizing bacterial esterase has been recognized as an efficient approach but few effective esterases capable of degrading a wide range of phthalate diesters have been identified. Further, the thermostability of these esterases is a highly desirable property for their applications in diverse in-situ conditions. In this present in-silico study a hypothetical protein (POB10642.1) as a high-potential esterase from a thermostable strain of Sulfobacillus sp. hq2 has been characterized. Analysis revealed a significant sequence identity of 42.67 % and structural similarity (RMSD 0.557) with known phthalate diester degrading EstS1 esterase and a high Tm range of 55-66 °C. Structural analysis revealed the presence of two cavities on the surface mediating toward the catalytic site forming a catalytic tunnel. The enzyme POB10642.1 has significant molecular docking binding energies in the range of -5.4 to -7.5 kcal/mol with several phthalate diesters, including Diethyl phthalate, Dipropyl phthalate, Dibutyl phthalate, Dipentyl phthalate, Dihexyl phthalate, Benzyl butyl phthalate, Dicyclohexyl phthalate, and Bis(2-ethylhexyl) phthalate. High stability of binding during 100 ns molecular dynamics simulations revealed efficient and stable binding of the enzyme with a wide range of phthalate diesters at its active site, demonstrating the ability of the identified esterase to interact with and degrade diverse phthalate diesters. Therefore, POB10642.1 esterase can be an efficient candidate to be utilized in the development of enzyme-based bioremediation technologies to reduce the toxic levels of phthalate diesters.

Exploring Druggable Binding Sites on the Class A GPCRs Using the Residue Interaction Network and Site Identification by Ligand Competitive Saturation

G protein-coupled receptors (GPCRs) play a central role in cellular signaling and are linked to many diseases. Accordingly, computational methods to explore potential allosteric sites for this class of proteins to facilitate the identification of potential modulators are needed. Importantly, the availability of rich structural data providing the locations of the orthosteric ligands and allosteric modulators targeting different GPCRs allows for the validation of approaches to identify new allosteric binding sites. Here, we validate the combination of two computational techniques, the residue interaction network (RIN) model and the site identification by ligand competitive saturation (SILCS) method, to predict putative allosteric binding sites of class A GPCRs. RIN analysis identifies hub residues that mediate allosteric signaling within a receptor and have a high capacity to alter receptor dynamics upon ligand binding. The known orthosteric (and allosteric) binding sites of 18 distinct class A GPCRs were successfully predicted by RIN through a dataset of 105 crystal structures (91 ligand-bound, 14 unbound) with up to 77.8% (76.9%) sensitivity, 92.5% (95.3%) specificity, 51.9% (50%) precision, and 86.2% (92.4%) accuracy based on the experimental and theoretical binding site data. Moreover, graph spectral analysis of the residue networks revealed that the proposed sites were located at the interfaces of highly interconnected residue clusters with a high ability to coordinate the functional dynamics. Then, we employed the SILCS-Hotspots method to assess the druggability of the novel sites predicted for 7 distinct class A GPCRs that are critical for a variety of diseases. While the known orthosteric and allosteric binding sites are successfully explored by our approach, numerous putative allosteric sites with the potential to bind drug-like molecules are proposed. The computational approach presented here promises to be a highly effective tool to predict putative allosteric sites of GPCRs to facilitate the design of effective modulators.

Sulfoglycodendron Antivirals with Scalable Architectures and Activities

Many viruses initiate their cell-entry by binding their multisubunit receptors to human heparan sulfate proteoglycans (HSPG) and other molecular components present on cellular membranes. These viral interactions could be blocked and the whole viruses could be eliminated by suitable HSPG-mimetics providing multivalent binding to viral protein receptors. Here, large sulfoglycodendron HSPG-mimetics of different topologies, structures, and sizes were designed to this purpose. Atomistic molecular dynamics simulations were used to examine the ability of these broad-spectrum antivirals to block multiprotein HSPG-receptors in HIV, SARS-CoV-2, HPV, and dengue viruses. To characterize the inhibitory potential of these mimetics, their binding to individual and multiple protein receptors was examined. In particular, vectorial distributions of binding energies between the mimetics and viral protein receptors were introduced and calculated along the simulated trajectories. Space-dependent residual analysis of the mimetic-receptor binding was also performed. This analysis revealed the detailed nature of binding between these antivirals and viral protein receptors and provided evidence that large inhibitors with multivalent binding might act like a molecular glue initiating the self-assembly of protein receptors in enveloped viruses.

Structure-Based Design of CBP/EP300 Degraders: When Cooperativity Overcomes Affinity

We present the development of dCE-2, a structurally novel PROTAC targeting the CREB-binding protein (CBP) and E1A-associated protein (EP300)-two homologous multidomain enzymes crucial for enhancer-mediated transcription. The design of dCE-2 was based on the crystal structure of an in-house bromodomain (BRD) inhibitor featuring a 3-methyl-cinnoline acetyl-lysine mimic acetyl-lysine mimic discovered by high-throughput fragment docking. Our study shows that, despite its modest binding affinity to CBP/EP300-BRD, dCE-2's remarkable protein degradation activity stems from its good cooperativity, which we demonstrate by the characterization of its ternary complex formation both in vitro and in cellulo. Molecular dynamics simulations indicate that in aqueous solvents, this active degrader populates both folded and extended conformations, which are likely to promote cell permeability and ternary complex formation, respectively.

The Evolution of the Acylation Mechanism in β-Lactamase and Rapid Protein Dynamics

β-Lactamases are a class of well-studied enzymes that are known to have existed since billions of years ago, starting as a defense mechanism to stave off competitors and are now enzymes responsible for antibiotic resistance. Using ancestral sequence reconstruction, it is possible to study the crystal structure of a laboratory resurrected 2-3 billion year-old β-lactamase. Comparing the ancestral enzyme to its modern counterpart, a TEM-1 β-lactamase, the structural changes are minor, and it is probable that dynamic effects play an important role in the evolution of function. We used molecular dynamics simulations and employed transition path sampling methods to identify the presence of rate-enhancing dynamics at the femtosecond level in both systems, found that these fast motions are more efficiently coordinated in the modern enzyme, and examined how specific dynamics can pinpoint evolutionary effects that are essential for improving enzymatic catalysis.

Membrane Stabilization of Helical Previtamin D Conformers as Possible Enhancement of Vitamin D Photoproduction

Photoinduced vitamin D formation occurs 10-15-fold faster in phospholipid bilayers (PLB) than in isotropic solution. It has been hypothesized that amphipatic interactions of the PLB with the rotationally flexible previtamin D (Pre) stabilize its helical conformers, enhancing thermal intramolecular [1,7]-hydrogen transfer, forming vitamin D. To test this hypothesis, we carried out molecular dynamics (MD) simulations of Pre in a PLB composed of dipalmitoylphosphatidylcholine (DPPC). We designed a classical force field capable of accurately describing the equilibrium composition of Pre conformers. Using adaptive biasing force MD simulations, we determined the free energy of Pre conformers in isotropic environments (hexane and gas-phase) and in the anisotropic environment of a DPPC PLB. We find a total increase of 25.5% of the population of both helical conformers (+20.5% g+Zg+ and +5% g-Zg-) in DPPC compared to hexane. In view of ab initio simulations, showing that hydrogen transfer occurs in both helical conformers, our study strongly suggests the validity of the initial hypothesis. Regarding the amphipatic interactions of Pre with the PLB, we find that, similar to cholesterol (Chol) and 7-dehydrocholesterol (7-DHC), Pre entertains hydrogen bonds mainly to the carbonyl groups of DPPC and, to a lesser extent, with phosphate oxygen atoms and rarely to water molecules at the interface. We further report order parameters of the Pre/DPPC system, which are slightly smaller than those for Chol/DPPC and 7-DHC/DPPC, but larger than for pure DPPC. This indicates a loss in membrane viscosity upon photochemical ring-opening of 7-DHC to form Pre.

Lipophilic compounds restore function to neurodevelopmental-associated KCNQ3 mutations

A major driver of neuronal hyperexcitability is dysfunction of K+ channels, including voltage-gated KCNQ2/3 channels. Their hyperpolarized midpoint of activation and slow activation and deactivation kinetics produce a current that regulates membrane potential and impedes repetitive firing. Inherited mutations in KCNQ2 and KCNQ3 are linked to a wide spectrum of neurodevelopmental disorders (NDDs), ranging from benign familial neonatal seizures to severe epileptic encephalopathies and autism spectrum disorders. However, the impact of these variants on the molecular mechanisms underlying KCNQ3 channel function remains poorly understood and existing treatments have significant side effects. Here, we use voltage clamp fluorometry, molecular dynamic simulations, and electrophysiology to investigate NDD-associated variants in KCNQ3 channels. We identified two distinctive mechanisms by which loss- and gain-of function NDD-associated mutations in KCNQ3 affect channel gating: one directly affects S4 movement while the other changes S4-to-pore coupling. MD simulations and electrophysiology revealed that polyunsaturated fatty acids (PUFAs) primarily target the voltage-sensing domain in its activated conformation and form a weaker interaction with the channel's pore. Consistently, two such compounds yielded partial and complete functional restoration in R227Q- and R236C-containing channels, respectively. Our results reveal the potential of PUFAs to be developed into therapies for diverse KCNQ3-based channelopathies.

Calculated hydration free energies become less accurate with increases in molecular weight

In order for computer-aided drug design to fulfil its long held promise of delivering new medicines faster and cheaper, extensive development and validation work must be done first. This pertains particularly to molecular dynamics force fields where one important aspect-the hydration free energy (HFE) of small molecules-is often insufficiently analyzed. While most benchmarking studies report excellent accuracies of calculated hydration free energies-usually within 2 kcal/mol of experimental values-we find that deeper analysis reveals significant shortcomings. Herein, we report a dependence of HFE prediction errors on ligand molecular weight-the higher the weight, the bigger the prediction error and the higher the probability the calculated result is erroneous by a large amount. We show that in the drug-like molecular weight region, HFE predictions can easily be off by 5 kcal/mol or more. This is likely to be highly problematic in a drug discovery and development setting. We make our HFE results and molecular descriptors freely and fully available in order to encourage deeper analysis of future molecular dynamics results and facilitate development of the next generation of force fields.