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

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

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

Investigating the impact of SOD1 mutations on amyotrophic lateral sclerosis progression and potential drug repurposing through in silico analysis

Superoxide dismutase 1 (SOD1) is a vital enzyme responsible for attenuating oxidative stress through its ability to facilitate the dismutation of the superoxide radical into oxygen and hydrogen peroxide. The progressive loss of motor neurons characterize amyotrophic lateral sclerosis (ALS), a crippling neurodegenerative disease that is caused by mutations in the SOD1 gene. In this study, in silico mutational analysis was performed to study the various mutations, the pathogenicity and stability ΔΔG (binding free energy) of the variant of SOD1. x in the protein variant analysis showed a considerable destabilizing effect with a ΔΔG value of -4.2 kcal/mol, signifying a notable impact on protein stability. Molecular dynamics simulations were conducted on both wild-type and C146R mutant SOD1. RMSD profiles indicated that both maintained consistent structural conformation over time. Additionally, virtual screening of 3067 FDA-approved drugs against the mutant SOD1 identified two potential binders, Tucatinib (51039094) and Regorafenib (11167602), which interacted with Leu106, similar to the control drug, Ebselen. Further simulations assessed the dynamic properties of SOD1 in monomeric and dimeric forms while bound to these compounds. 11167602 maintained stable interaction with the monomeric SOD1 mutant, whereas 51039094 and Ebselen dissociated from the monomeric protein's binding site. However, all three compounds were stably bound to the dimeric SOD1. MM/GBSA analysis revealed similar negative binding free energies for 11167602 and 51039094, identifying them as strong binders due to their interaction with Cys111. Experimental validation, including in vitro, cell-based, and in vivo assays are essential to confirm these candidates before advancing to clinical trials.

Discovery of Potent Kappa Opioid Receptor Agonists Derived from Akuammicine

Akuammicine (1), an alkaloid isolated from Picralima nitida, is an agonist of the kappa opioid receptor (κOR). To establish structure-activity relationships (SARs) for this structurally unique κOR ligand, a collection of semisynthetic derivatives was synthesized. Evaluating these derivatives for their ability to activate the κOR and mu opioid receptor (μOR) revealed key SAR trends and identified derivatives with enhanced κOR potency. Most notably, substitutions to the C10 position of the aryl ring led to a > 200-fold improvement in κOR potency and nearly complete selectivity for the κOR. A selection of the most potent ligands was shown to possess differing abilities recruitment of β-Arrestin-2 to the κOR, indicating they have distinct signaling properties from each other and existing κOR ligands. The discovery of these κOR agonists underscores the potential of using natural products to identify new classes of potent and selective ligands and provides new tools to probe the κOR.

Potent and Selective Human 5-HT2B Serotonin Receptor Antagonists: 4'-Cyano-(N)-methanocarba-adenosines by Synthetic Serendipity

Rigidified nucleoside derivatives with (N)-methanocarba replacement of ribose have been repurposed as peripheral subtype-selective 5-HT2B serotonin receptor antagonists for heart and lung fibrosis and intestinal/vascular conditions. 4'-Cyano derivative 40 (MRS8209; Ki, 4.27 nM) was 47-fold (human binding, but not rat and mouse) and 724-fold (functionally) selective at 5-HT2BR, compared to antitarget 5-HT2CR, and predicted to form a stable receptor complex using docking and molecular dynamics. 4'-Cyano substituents enhanced 5-HT2BR affinity (typically 4-5-fold compared to 4'-CH2OH), depending on an N6 group larger than methyl. Asymmetric N6 groups (4'-cyano-2-halo derivatives 33-35 and 37) provided potent 5-HT2BR Ki values (7-22 nM). A 4'-CH2CN substituent was less effective than 4'-CN at increasing 5-HT2BR affinity, while a 4'-CHF2 group produced high 5-HT2B affinity/selectivity. A 2-benzylthio-adenine group with unsubstituted 6-NH2 shifted the typical selectivity pattern toward potent 5-HT2C binding. Thus, the SAR suggests that N6-cyclopentyl-4'-cyano modifications are promising, with an interdependence among the substituent positions.

Understanding the Directed Evolution of a Natural-like Efficient Artificial Metalloenzyme

The artificial metalloenzyme containing iridium in place of iron along with four directed evolution mutations C317G, T213G, L69V, and V254L in a natural cytochrome P450 presents an important milestone in merging the extraordinary efficiency of biocatalysts with the versatility of small molecule chemical catalysts in catalyzing a new-to-nature carbene insertion reaction. This is a show-stopper enzyme, as it exhibits a catalytic efficiency similar to that of natural enzymes. Despite this remarkable discovery, there is no mechanistic and structural understanding as to why it displays extraordinary efficiency after the incorporation of the four active site mutations by directed evolution methods, which so far has been intractable to any experimental methods. In this study, we have deciphered how directed evolution mutations gradually alter the protein conformational ensemble to populate a catalytically active conformation to boost a multistep catalysis in a natural-like artificial metalloenzyme using large-scale molecular dynamics simulations, rigorous quantum chemical (QM), and multiscale quantum chemical/molecular mechanics (QM/MM) calculations. It reveals how evolution precisely positions the cofactor-substrate in an unusual but effective orientation within a reshaped active site in the catalytically active conformation stabilized by C-H···π interactions from more ordered mutated L69V and V254L residues to achieve preferential transition state stabilization compared to the ground state. This work essentially tracks down in atomistic detail the shift in the conformational ensemble of the highly active conformation from the less efficient single mutant to the most efficient quadruple mutant and offers valuable insights for designing better enzymes. The active conformation correctly reproduces the experimental barrier height and also accounts for the catalytic effect, which is in good agreement with experimental observations. Moreover, this conformation features an unusual bonding interaction in a metal-carbene species that preferentially stabilizes the rate-determining formation of an iridium porphyrin carbene intermediate to render the observed high catalytic rate acceleration. Our study provides crucial insights into the underlying rationale for directed evolution, reports the major catalytic role of nonelectrostatic interactions in enzyme catalysis different from the electrostatic model, and suggests a crucial principle toward designing enzymes with natural efficiency.

Heavy-boundary mode patterning and dynamics of topological phonons in polymer chains and supramolecular lattices on surfaces

In topological band theory, phonon boundary modes consequence of a topologically non-trivial  band structure feature desirable properties for atomically-precise technologies, such as robustness against defects, waveguiding, and one-way transport. These topological phonon boundary modes remain to be studied both theoretically and experimentally in synthetic materials, such as polymers and supramolecular assemblies at the atomistic level under thermal fluctuations. Here we show by means of molecular simulations, that surface-confined Su-Schrieffer-Heeger (SSH) phonon analogue models express robust topological phonon boundary modes at heavy boundaries and under thermal fluctuations. The resulting bulk-heavy boundary correspondence enables patterning of boundary modes in polymer chains and weakly-interacting supramolecular lattices. Moreover, we show that upon excitation of a single molecule, propagation along heavy-boundary modes differs from free boundary modes. Our work is an entry to topological vibrations in supramolecular systems, and may find applications in the patterning of phonon circuits and realization of Hall effect phonon analogues at the molecular scale.

A putative mycobacterial GDP-mannose dependent α-mannosyltransferase Rv0225 acts as PimC: an in-silico study

The complex cell envelope of pathogenic mycobacteria provides a strong barrier against the host immune system and various antibiotics. Phosphatidyl-myo-inositol mannosides (PIMs), lipomannan (LM), and lipoarabinomannan (LAM) are structurally important elements of mycobacterial cell envelope and also play crucial roles in modulating the host immune functions. At the cytoplasmic side of the mycobacterial inner membrane, phosphatidyl-myo-inositol (PI) is mannosylated by α-mannosyltransferases PimA and PimB' to synthesize PIM2 using GDP-mannose (GDPM) as the mannose donor. This PIM2 compound is acylated to synthesize Ac1/2PIM2, which is further mannosylated by an unknown enzyme PimC to produce Ac1/2PIM3. Synthesis of LM/LAM or higher PIM compounds (Ac1/2PIM4 / Ac1/2PIM5 / Ac1/2PIM6) requires polyprenol-phosphate-mannose (PPM) as the mannose donor and takes place at the periplasmic side of the mycobacterial inner membrane. Previously, a GDPM-dependent α-mannosyltransferase RvD2-ORF1 was identified as the PimC in Mycobacterium tuberculosis CDC1551 (Mtb CDC1551). However, its counterpart was missing in most other mycobacterial strains. Bioinformatic analyses, molecular docking, and molecular dynamics (MD) simulations in this study indicate that Rv0225, an essential protein of Mycobacterium tuberculosis H37Rv, is a GDPM-binding α-mannosyltransferase. The predicted structure of Rv0225 showed similarities with mycobacterial proteins PimA, PimB', and PimC of Mtb CDC1551. Further molecular docking and MD simulations also suggest that Ac1/2PIM2 can bind to Rv0225 and showed similar dynamic patterns as the glycolipid substrates of PimA and PimB'. The binding of Ac1PIM3 caused opening and closing motions of Rv0225, a phenomenon also observed in the case of PimA. Overall, the computational analyses suggest that Rv0225 may play the role of PimC in mycobacteria.

Multiscale simulation of liquid chromatography: Effective diffusion in macro-mesoporous beds and the B-term of the plate height equation

We performed multiscale simulations of analyte sorption and diffusion in hierarchical porosity models of monolithic silica columns for reversed-phase liquid chromatography to investigate how the mean mesopore size of the chromatographic bed and the analyte-specific interaction with the chromatographic interface influence the analyte diffusivity at various length scales. The reproduced experimental conditions comprised the retention of six analyte compounds of low to moderate solute polarity on a silica-based, endcapped, C18 stationary phase with water‒acetonitrile and water-methanol mobile phases whose elution strength was varied via the volumetric solvent ratio. Detailed information about the analyte-specific interfacial dynamics received from molecular dynamics simulations was incorporated through appropriate linker schemes into Brownian dynamics diffusion simulations in three hierarchical porosity models received from physical reconstructions of silica monoliths with a mean macropore size of 1.23 µm and mean mesopore sizes of 12.3, 21.3, or 25.7 nm. The mean mesopore size was found to have a similar influence on the effective mesopore diffusivity as the analyte polarity and the mobile-phase elution strength, which together determine the analyte residence time on a column. A smaller mesopore size attenuated the increase of the effective mesopore diffusivity with increasing mobile-phase elution strength significantly. The effective bed diffusivity was limited by the analyte residence time rather than by morphological details of the mesopore space. The stronger an analyte was retained by the chromatographic interface inside the mesopores, the slower became the mass transfer between the pore space hierarchies and the lower was the effective bed diffusivity. The B-terms of the plate height equation were finally generated with the bed diffusivities and phase-based retention factors derived from the hierarchical porosity models using additional information about the stationary-phase limit obtained from the analysis of analyte-bonded phase contacts. The B-terms highlight analyte- and mobile phase-specific behavior relevant to isocratic and gradient elution conditions in chromatographic practice. In particular, U-shaped B-term curves are observed due to the dominating contribution of the retention factor and the bed diffusivity to the B-term at low and high elution strength of the mobile phase, respectively.

Kinetic Implications of IP6 Anion Binding on the Molecular Switch of the HIV-1 Capsid Assembly

HIV-1 capsid proteins (CA) self-assemble into a fullerene-shaped capsid, enabling cellular transport and nuclear entry of the viral genome. A structural switch comprising the Thr-Val-Gly-Gly (TVGG) motif either assumes a disordered coil or a 310 helix conformation to regulate hexamer or pentamer assembly, respectively. The cellular polyanion inositol hexakisphosphate (IP6) binds to a positively charged pore of CA capsomers rich in arginine and lysine residues mediated by electrostatic interactions. Both IP6 binding and TVGG coil-to-helix transition are essential for pentamer formation. However, the connection between IP6 binding and TVGG conformational switch remains unclear. Using extensive atomistic simulations, we show that IP6 imparts structural order at the central ring, which results in multiple kinetically controlled events leading to the coil- to-helix conformational change of the TVGG motif. IP6 facilitates the helix-to-coil transition by allowing the formation of intermediate conformations. Our results identify the key kinetic role of IP6 in HIV-1 pentamer formation.

Supercritical density fluctuations and structural heterogeneity in supercooled water-glycerol microdroplets

Recent experiments and theoretical studies strongly indicate that water exhibits a liquid-liquid phase transition (LLPT) in the supercooled domain. An open question is how the LLPT of water can affect the properties of aqueous solutions. Here, we study the structural and thermodynamic properties of supercooled glycerol-water microdroplets at dilute conditions (χg = 3.2% glycerol mole fraction). The combination of rapid evaporative cooling with femtosecond X-ray scattering allows us to outrun crystallization and gain access to the deeply supercooled regime down to T = 229.3 K. We find that the density fluctuations of the glycerol-water solution or, equivalently, its isothermal compressibility, κT, increases upon cooling. This is confirmed by molecular dynamics simulations, which indicate that the presence of glycerol shifts the temperature of maximum κT from T = 230 K in pure water down to T = 223 K in the solution. Our findings elucidate the interplay between the complex behavior of water, including its LLPT, and the properties of aqueous solutions at low temperatures, which can have practical consequences in cryogenic biological applications and cryopreservation techniques.

Isolation of phytoconstituents from an extract of Murraya paniculata with cytotoxicity and antioxidant activities and in silico evaluation of their potential to bind to aldose reductase (AKR1B1)

The study on Murraya paniculata (Orange Jasmine) stem bark extract found it to have antioxidant and cytotoxic proper-ties. The structures of the isolated phytoconstituents were determined using NMR spectroscopy. Compounds were evaluated for their potential to be aldose reductase inhibitors using molecular docking and dynamics (MD) simulations. Phytochemical screening of methanolic crude extract was performed from which different fractions of the extract were screened for antioxidant activity using the DPPH radical scavenging method and cytotoxicity using the brine shrimp lethality bioassay. The aqueous fraction showed strong antioxidant activity as compared to the standard butylated hy-droxytoluene, whereas pet ether, dichloromethane, chloroform and methanolic extract exhibited moderate antioxidant activity. Activities in the DPPH assay ranged from 17 to 63 µg/ml and all fractions showed cytotoxic activity. Five identified phytochemical compounds (1-5) include ergosterol endoperoxide (1), the coumarin derivatives 7-methoxy-8-(3-methylbut-2-enyl)-1-benzopyran-2-one (2) and 5,7-dimethoxy-8-(3-methylbut-2-enyl)-1-benzopyran-2-one (3) and a mixture of β-sitosterol (4), and stigmasterol (5). Among them ergosterol endoperoxide has been isolated from the stem bark of the M. paniculata for the first time. MD simulations of the identified compounds indicated their potential to bind to the aldose reductase (AKR1B1) protein. Predicted binding affinities of the compounds based on the site identification the ligand competitive saturation (SILCS) technology was -15.04, -8.85, -9.83, -11.95, and -11.75 kcal/mol for 1 through 5, respectively. The present results are anticipated to lead to further study of the activities of the five compounds including experimental evaluation of their inter-actions with AKR1B1.

Multi-omics and in-silico approach reveals AURKA, AURKB, and RSAD2 as therapeutic biomarkers in OSCC progression

Oral squamous cell carcinoma (OSCC), a prevalent form of head and neck cancer, poses a significant health challenge with limited improvements in patient outcomes over the years. Its development is influenced by a complex interplay of genetic alterations and environmental factors. While progress has been made in understanding the molecular mechanisms driving OSCC, pinpointing critical molecular markers and potential drug candidates has proven elusive. This study uniquely endeavors to conduct a meta-analysis to unveil therapeutic genes responsible for OSCC tumorigenesis. A multi-omics approach identified 951 differentially expressed genes (DEGs) associated with OSCC by analyzing microarray data from the NCBI GEO database. Weighted gene co-expression network analysis (WGCNA) detected a significant hub gene module comprising 805 genes, followed by the construction of protein-protein interaction network resulting in two small clusters of 7 gene-encoded proteins each. These clusters were filtered out based on top 10 significant pathways and gene ontology terms to identify six key target proteins with elevated expression levels, acting as potential therapeutic biomarkers for OSCC. Notably, RSAD2 emerged as a novel biomarker linked to OSCC progression. Furthermore, we identified potential inhibitors targeting AURKA, AURKB, and RSAD2 proteins and validated their interactions through molecular dynamics simulation studies. The simulations confirmed the stability of receptor-ligand complexes, suggesting ZINC03839281, ZINC04026167, and ZINC00718292 compounds hold promise as potential inhibitors for therapeutically targeting AURKA, AURKB, and RSAD2 as significant OSCC biomarkers. We recommend further comprehensive studies, including experimental and preclinical investigations, to validate the effectiveness of these lead compounds for OSCC treatment.

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

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

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

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

Multi-method computational evaluation of the inhibitors against leucine-rich repeat kinase 2 G2019S mutant for Parkinson's disease

Leucine-rich repeat kinase 2 G2019S mutant (LRRK2 G2019S) is a potential target for Parkinson's disease therapy. In this work, the computational evaluation of the LRRK2 G2019S inhibitors was conducted via a combined approach which contains a preliminary screening of a large database of compounds via similarity and pharmacophore, a secondary selection via structure-based affinity prediction and molecular docking, and a rescoring treatment for the final selection. MD simulations and MM/GBSA calculations were performed to check the agreement between different prediction methods for these inhibitors. 331 experimental ligands were collected, and 170 were used to build the structure-activity relationship. Eight representative ligand structural models were employed in similarity searching and pharmacophore screening over 14 million compounds. The process for selecting proper molecular descriptors provides a successful sample which can be used as a general strategy in QSAR modelling. The rescoring used in this work presents an alternative useful treatment for ranking and selection.

Catalytic mechanism, computational design, and crystal structure of a highly specific and efficient benzoylecgonine hydrolase

Enzyme therapy for cocaine detoxification should break down both cocaine and its primary toxic metabolite, benzoylecgonine (BZE), which is also the main form of cocaine contaminant in the environment. An ideal BZE-metabolizing enzyme (BZEase) is expected to be highly efficient and selective in BZE hydrolysis. Here, BZEase4 was engineered from bacterial cocaine esterase (CocE) by our reactant state-based enzyme design theories (RED), which has a 34,977-fold improved substrate discrimination between BZE and the neurotransmitter acetylcholine (ACh), compared with wild-type CocE. Under the physiological concentrations of BZE and ACh, the reaction velocity of BZEase4 against BZE is 2.25 × 106-fold higher than it against ACh, suggesting BZEase4 has extremely high substrate selectivity for BZE over ACh to minimize the potential cholinergic side-effects. This study provides additional evidence supporting the further development of BZEase4 toward a promising therapeutic for cocaine overdose, a potentially effective and eco-friendly enzymatic method for BZE degradation in the environment.

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

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

Leukotriene B4 receptor 1 (BLT1) activation by leukotriene B4 (LTB4) and E resolvins (RvE1 and RvE2)

Leukotriene B4 (LTB4) is a lipid inflammatory mediator derived from arachidonic acid (AA). Leukotriene B4 receptor 1 (BLT1), a G protein-coupled receptor (GPCR), is a receptor of LTB4. Nonetheless, the resolution of inflammation is driven by specialized pro-resolving lipid mediators (SPMs) such as resolvins E1 (RvE1) and E2 (RvE2). Both resolvins are derived from omega-3 fatty acid eicosapentaenoic acid (EPA). Here, long-term molecular dynamics simulations (MD) were performed to investigate the activation of the BLT1 receptor using two pro-resolution agonists (RvE1 and RvE2) and an inflammatory agonist (LTB4). We have analyzed the receptor's activation state, electrostatic interactions, and the binding affinity the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach. The results showed that LTB4 and RvE1 have kept the receptor in an active state by higher simulation time. MD showed that the ligand-receptor interactions occurred mainly through residues H94, R156, and R267. The MMPBSA calculations showed residues R156 and R267 were the two mainly hotspots. Our MMPBSA results were compatible with experimental results from other studies. Overall, the results from this study provide new insights into the activation mechanisms of the BLT1 receptor, reinforcing the role of critical residues and interactions in the binding of pro-resolution and pro-inflammatory agonists.

Molecular Mechanism of the β3AR Agonist Activity of a β-Blocker

Development of subtype-selective drugs for G protein-coupled receptors poses a significant challenge due to high similarity between subtypes, as exemplified by the three β-adrenergic receptors (βARs). The β3AR agonists show promise for treating the overactive bladder or preterm birth, but their potential is hindered by off-target activation of β1AR and β2AR. Interestingly, several β-blockers, which are antagonists of the β1ARs and β2ARs, have been reported to exhibit agonist activity at the β3AR. However, the molecular mechanism remains elusive. Understanding the underlying mechanism should facilitate the development of β3AR agonists with improved selectivity and reduced off-target effects. In this work, we determined the structures of human β3AR in complex with the endogenous agonist epinephrine or with a synthetic β3AR agonist carazolol, which is also a high-affinity β-blocker. Structure comparison, mutagenesis studies and molecular dynamics simulations revealed that the differences on the flexibility of D3.32 directly contribute to carazolol's distinct activities as an antagonist for the β2AR and an agonist for the β3AR. The process is also indirectly influenced by the extracellular loops (ECL), especially ECL1. Taken together, these results provide key guidance for development of selective β3AR agonists, paving the way for new therapeutic opportunities.

Targeting Yes-Associated Protein (YAP) in Breast Cancer: In Silico Molecular Dynamics, Luminescence-Based In Vitro, and In Vivo Validation of Rauvolfia tetraphylla-Derived Inhibitors

The study aims to elucidate the pharmacological mechanism of Rauvolfia tetraphylla against breast cancer through a comprehensive, multi-faceted approach. This includes molecular docking, molecular dynamics, and experimental validation. Initial screening via ADME analysis and network pharmacology identified key compounds and potential targets. Protein-protein interaction (PPI) network analysis pinpointed Yes-associated protein-1 (YAP) as a crucial target. Molecular docking revealed that three compounds-ajmaline, reserpine, and serpentine-exhibited strong binding affinities with YAP, with scores of -6.5 to -6.7 kcal/mol. Molecular dynamics simulations were conducted to assess the stability of these interactions further. Experimental validation showed R. tetraphylla inhibited breast cancer cell proliferation, with an IC50 of 348.69 μg/mL, while demonstrating cytoprotective effects on Vero cells (IC50: 1056.23 μg/mL). Migration assays indicated an 88.5% reduction in cell migration, and increased ROS levels signaled elevated stress in cancer cells. Apoptosis was confirmed by AO/EtBr staining. In vivo validation in a DMBA-induced mouse model confirmed significant tumor growth inhibition, supported by changes in YAP expression and histopathological analysis. These findings highlight R. tetraphylla as a promising therapeutic candidate against breast cancer, offering insights into its mechanisms and potential for future drug development and clinical applications.

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

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

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

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

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

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

Side-chain-induced changes in aminated chitosan: Insights from molecular dynamics simulations

Chitosan is a functional polymer with diverse applications in biomedicine, agriculture, water treatment, and beyond. Via derivatization of pristine chitosan, its functionality can be tailored to desired applications, e.g. immobilization of biomolecules. Here, we performed molecular dynamics simulations of three aminated chitosan polymers, where one, two, and three long-distanced side chains have been incorporated. These polymers have been previously synthesized and their properties were investigated experimentally, however, the observed dependencies could not be fully explained on the molecular level. Here, we develop a computational protocol for the simulation of functionalized chitosan polymers and perform advanced analysis of their conformational states, intramolecular interactions, and water binding. We demonstrate that intra- and intermolecular forces, especially hydrogen bonds induced by polymer side chain modifications, modulate dihedral angle conformational states of the polymer backbone and interactions with water. We explain the role of the chemical composition of the functionalized chitosans in their tendency to collapse and reveal the key role of the protonation of the amino group near the polymer backbone on the reduction of polymer collapse. We demonstrate that specific binding of water molecules, especially the intermediate water, is more pronounced in the polymer exhibiting such an amino group.

A molecular and computational study of galbanic acid as a regulator of Sirtuin1 pathway in inhibiting lipid accumulation in HepG2 cells

INTRODUCTION

Sirtuin1 (SIRT1) plays a crucial role in the pathophysiology of non-alcoholic fatty liver disease. We investigated the mechanistic role of galbanic acid (Gal) as a regulator of SIRT1 in silico and in vitro.

METHODS

HepG2 cells were treated with Gal in the presence or absence of EX-527, a SIRT1-specific inhibitor, for 24 h. Sirtuin1 gene and protein expression were measured by RT-PCR and Western blotting, respectively. It has been docked to the allosteric reign of SIRT1 (PDB ID: 4ZZJ) to study the effect of Gal on SIRT1, and then the protein and complex molecular dynamic (MD) simulations had been studied in 100 ns.

RESULTS

The semi-quantitative results of Oil red (p < .03) and TG level (p < .009) showed a significant reduction in lipid accumulation by treatment with Gal. Also, a significant increase was observed in the gene and protein expression of SIRT1 (p < .05). MD studies have shown that the average root mean square deviation (RMSD) was about 0.51 Å for protein structure and 0.66 Å for the complex. The average of radius of gyration (Rg) is 2.33 and 2.32 Å for protein and complex, respectively, and the pattern of root mean square fluctuation (RMSF) was almost similar.

CONCLUSION

Computational studies show that Gal can be a great candidate to use as a SIRT1 ligand because it does not interfere with the structure of the protein, and other experimental studies showed that Gal treatment with SIRT1 inhibitor increases fat accumulation in HepG2 cells.

Computational journey to unveil organophosphorothioate pesticides' metabolism: A focus on chlorpyrifos and CYP2C19 mutational landscape

Organophosphorothioates (OPT) are pesticides impacting human, animal and environmental health. They enter the environment worldwide, primarily due to their application as insecticides. OPTs are mainly neurotoxic upon bioactivation and inhibition of brain and serum acetylcholinesterase (AChE). Although OPTs are meant to target insects, they are potentially toxic to many other species (including humans), posing risks to non-target organisms and ecosystems. Certain cytochromes P450 (CYP) promote OPTs bioactivation, forming the corresponding oxon metabolites, while others catalyse their detoxification. Understanding the molecular basis of such a bivalent fate may help to clarify the toxicity of OPTs in living organisms, with far-reaching consequences to understand their impact on living organisms and improve risk assessment, to cite but a few. However, although crucial, the underpinning mechanisms still lay unclear. Here, a validated computational pipeline revealed the molecular reasons underlying the differential metabolism of chlorpyrifos in humans by CYP2C19, a primal route of detoxification, and its bioactivation by CYP2B6. The analysis drew the diverse occupancy of the CYP pocket and orientation to the heme group as a convincing evidence-based explanation for the opposite transformation. Moreover, this study explored the impact of CYP2C19 mutational landscape giving a blueprint to unveil the molecular basis of OPTs metabolism and toxicological implications from an inter-individual perspective. Taken together, the outcome described for the first time to the best of our knowledge a structural rationale for the bioactivation/detoxification of OPTs improving the current understanding of their toxicity from a molecular standpoint.

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

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

Mechanistic basis for the emergence of EPS1 as a catalyst in salicylic acid biosynthesis of Brassicaceae

Salicylic acid (SA) production in Brassicaceae plants is uniquely accelerated from isochorismate by EPS1, a newly identified enzyme in the BAHD acyltransferase family. We present crystal structures of EPS1 from Arabidopsis thaliana in both its apo and substrate-analog-bound forms. Integrating microsecond-scale molecular dynamics simulations with quantum mechanical cluster modeling, we propose a pericyclic rearrangement lyase mechanism for EPS1. We further reconstitute the isochorismate-derived SA biosynthesis pathway in Saccharomyces cerevisiae, establishing an in vivo platform to examine the impact of active-site residues on EPS1 functionality. Moreover, stable transgenic expression of EPS1 in soybean increases basal SA levels, highlighting the enzyme's potential to enhance defense mechanisms in non-Brassicaceae plants lacking an EPS1 ortholog. Our findings illustrate the evolutionary adaptation of an ancestral enzyme's active site to enable a novel catalytic mechanism that boosts SA production in Brassicaceae plants.

Evaluation of All-Atom and Martini 3 Coarse-Grained Force Fields from the Structural Investigation of Nitroxide Spin Probes and Their Confinement in Beta-Cyclodextrin

Nitroxide radicals have found wide applications as spin labels or probes, and their guest-host interactions with cyclodextrins exhibit enhanced applications in electron spin resonance (ESR) spectroscopy and imaging due to improved biostability toward reducing agents. Although the computational prediction of the guest-host binding has become increasingly common for small ligands, molecular simulations regarding the conformational preferences of hosted spin probes have not been conducted. Here we present molecular dynamics simulations at an atomistic level for a set of four TEMPO (2,2,6,6-tetramethylpiperidine 1-oxyl) spin probes and thereafter develop coarse-grained models compatible with the recent version of the Martini force field (v 3.0) to tackle their encapsulation in the cavity of β-cyclodextrin (βCD) for which experimental ESR data are available. The results indicate that the atomistic descriptions perform well in relation to the structural parameters derived from X-ray diffraction as well as hydrogen bonding and hydrogen patterns and predict that the guest-host complexation is hydrophobically driven by the presence of a methyl group pair of the spin probe at the cavity center of βCD. The spin probe mobility at the binding site reveals the nitroxide group orientation toward the secondary rim of the cyclodextrin and the alternating presence of the two methyl group pairs inside the cavity, features in agreement with the experimental behavior of the ESR parameters. The coarse-grained parameterizations of TEMPO probes and βCD rely on optimizing the bonded and nonbonded parameters with references to the atomistic simulation results, and they are capable of recovering the orientation and location of the spin probe inside the cyclodextrin cavity predicted by the atomistic guest-host complexes. The results suggest the cyclodextrin host-guest system as a powerful validation suite to evaluate new coarse-grained parameterizations of small ligands and future extensions to functionalized cyclodextrins in inclusion complexes.

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

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

Assessing Melting and Solid-Solid Transition Properties of Choline Chloride via Molecular Dynamics Simulations

Choline chloride (ChCl) is used extensively as a hydrogen bond donor in deep eutectic solvents (DESs). However, determining its melting properties experimentally is challenging due to decomposition upon melting, leading to widely varying literature values. Accurate melting properties are crucial for understanding the solid-liquid phase behavior of ChCl-containing DESs. Here, we employ molecular dynamics simulations to compute the phase transitions of ChCl, testing a variety of atomistic force fields. We find that the results are sensitive to the choice of force field, but a melting temperature of 627 K and a melting enthalpy of 7.8 kJ/mol seem most reasonable, in good agreement with some literature values. We suggest these as the likely melting properties of ChCl, though the results are tentative due to limited experimental data for the liquid ChCl phase.

Elucidating the monoamine oxidase B inhibitory effect of kaurene diterpenoids from Xylopia aethiopica: An in silico approach

Parkinson disease is a neurogenerative disease common in adults and results in different kinds of memory dysfuntions. This study evaluated the monoamine oxidase B (MAO-B) inhibitory potential of kaurane diterpenoids previously isolated from Xylopia aethiopica through comprehensive computational approaches. Molecular docking study and molecular dynamics simulation were used to access the binding mode and interaction of xylopic acid and MAO-B enzyme. The ADMET properties of the phytochemical were evaluated to provide information on its druggability. The molecular docking and molecular dynamics simulation revealed xylopic acid as potential MAO-B inhibitor due to the good binding energy elicited and stability throughout the 100 ns simulation period. The ADMET properties of the ligand showed it as a promising drug candidate. The study recommend further comprehensive in vitro investigation towards the development of xylopic acid as potent MAO-B inhibitor.

Localization, aggregation, and interaction of glycyrrhizic acid with the plasma membrane

Glycyrrhizic acid (GLA) is the most important bioactive constituent of licorize root and exhibits antiviral, antimicrobial, anti-oxidant, anti-inflammatory, anti-allergic, and antitumor activities. GLA has an amphiphilic nature consisting of two hydrophilic and one hydrophobic part, and its mechanism of action could be mediated by its incorporation into the membrane. Furthermore, GLA presents two different forms, protonated (GLA) and deprotonated (GLAD), and has been suggested that their location inside the membrane could be different. Since GLA could be a source against many types of diseases, we have localized the GLA molecule in the presence of a complex membrane and established the detailed interactions of GLA with lipids using all-atom molecular dynamics. Our outcomes sustain that GLA/GLAD tend to locate amid the CHOL oxygen atom and the phospholipid phosphates, preferably perpendicular to the membrane surface, increasing membrane fluidity. Interestingly, GLA and GLAD tend to be surrounded by specific phospholipids, different for each type of molecule. Outstandingly, both GLA and GLAD tend to spontaneously associate in solution forming aggregates, precluding them from inserting into the membrane and, therefore, interacting with it. Consequently, some of the biological properties of GLA/GLAD could be credited to the alteration of the membrane biophysical properties by interacting with specific lipids. However, the formation of an aggregate in solution could hinder its bioactive properties and should be considered a suited vehicle when prepared to be used in biological or clinical assays.

In Silico Design of Peptide Inhibitors Targeting HER2 for Lung Cancer Therapy

BACKGROUND/OBJECTIVES

Human epidermal growth factor receptor 2 (HER2) is overexpressed in several malignancies, such as breast, gastric, ovarian, and lung cancers, where it promotes aggressive tumor proliferation and unfavorable prognosis. Targeting HER2 has thus emerged as a crucial therapeutic strategy, particularly for HER2-positive malignancies. The present study focusses on the design and optimization of peptide inhibitors targeting HER2, utilizing machine learning to identify and enhance peptide candidates with elevated binding affinities. The aim is to provide novel therapeutic options for malignancies linked to HER2 overexpression.

METHODS

This study started with the extraction and structural examination of the HER2 protein, succeeded by designing the peptide sequences derived from essential interaction residues. A machine learning technique (XGBRegressor model) was employed to predict binding affinities, identifying the top 20 peptide possibilities. The candidates underwent further screening via the FreeSASA methodology and binding free energy calculations, resulting in the selection of four primary candidates (pep-17, pep-7, pep-2, and pep-15). Density functional theory (DFT) calculations were utilized to evaluate molecular and reactivity characteristics, while molecular dynamics simulations were performed to investigate inhibitory mechanisms and selectivity effects. Advanced computational methods, such as QM/MM simulations, offered more understanding of peptide-protein interactions.

RESULTS

Among the four principal peptides, pep-7 exhibited the most elevated DFT values (-3386.93 kcal/mol) and the maximum dipole moment (10,761.58 Debye), whereas pep-17 had the lowest DFT value (-5788.49 kcal/mol) and the minimal dipole moment (2654.25 Debye). Molecular dynamics simulations indicated that pep-7 had a steady binding free energy of -12.88 kcal/mol and consistently bound inside the HER2 pocket during a 300 ns simulation. The QM/MM simulations showed that the overall total energy of the system, which combines both QM and MM contributions, remained around -79,000 ± 400 kcal/mol, suggesting that the entire protein-peptide complex was in a stable state, with pep-7 maintaining a strong, well-integrated binding.

CONCLUSIONS

Pep-7 emerged as the most promising therapeutic peptide, displaying strong binding stability, favorable binding free energy, and molecular stability in HER2-overexpressing cancer models. These findings suggest pep-7 as a viable therapeutic candidate for HER2-positive cancers, offering a potential novel treatment strategy against HER2-driven malignancies.

Explicit water-ligand docking, drug-likeness and molecular dynamics simulation analysis to predict the potency of Boerhavia diffusa plant extract against mutant wilms tumor-1 protein responsible for type 4 nephrotic syndrome

Thestructure and function of a protein are closely connected. Changes in a protein structure can impact on its function. Nephrotic syndrome type 4 (NPHS4) is an uncommon genetic condition caused by mutations in the WT1 gene, which codes for the wilms tumor-1 protein. Several studies have discovered that patients with nephrotic syndromes are resistant to steroid therapy and are likely to develop end-stage renal failure. The use of phytochemicals-based therapeutics is in demand due to their high potential and low toxicity. Based on this context, we employed the Autodock raccoon to screen 67 distinct potent phytochemicals from the Boerhavia diffusa (B.diffusa) plant against the wild type and mutant model at position C388R (cysteine is replaced with arginine at position 388) of the C-terminal DNA binding domain of the wilms tumor-1 protein. Out of 67 active compounds, only 10 compounds (lunamarine, kaempferol, boeravinone B, boeravinone E, boeravinone A, boeravinone F, boeravinone J, boeravinone P, boerhaavic acid and 4',7-dihydroxy-3'-methylflavone) were screened based on drug-likeness properties and binding energy for explicit water ligand docking against wild and mutant model of C-terminal DNA binding domain of wilms tumor-1 protein. Consequently, the hydrated form of boeravinone F and boeravinone A demonstrated the highest binding energy against the protein mutant model described above, the binding energies were -9.56 and -8.96 Kcal/mol, respectively. Followed by explicit water ligand docking the microscopic properties of wild type, mutant, mutant-boeravinone F complex, and mutant-boeravinone A complex systems were evaluated using molecular dynamics simulation steps with 100 ns of trajectory. The findings indicate that, due to mutation the mutant model system had decreasing stability and decreasing compactness nature. However, boeravinone A effectively monitored the mutant system's stability and improved compactness nature after binding with the mutant model. Boeravinone A with the mutant model complex system was determined to have the lowest energy point as compared to other studied systems. The study revealed minimal structural alterations and reduced conformational mobility.

Structural mechanisms of human sodium-coupled high-affinity choline transporter CHT1

Mammalian sodium-coupled high-affinity choline transporter CHT1 uptakes choline in cholinergic neurons for acetylcholine synthesis and plays a critical role in cholinergic neurotransmission. Here, we present the high-resolution cryo-EM structures of human CHT1 in apo, substrate- and ion-bound, hemicholinium-3-inhibited, and ML352-inhibited states. These structures represent three distinct conformational states, elucidating the structural basis of the CHT1-mediated choline uptake mechanism. Three ion-binding sites, two for Na+ and one for Cl-, are unambiguously defined in the structures, demonstrating that both ions are indispensable cofactors for high-affinity choline-binding and are likely transported together with the substrate in a 2:1:1 stoichiometry. The two inhibitor-bound CHT1 structures reveal two distinct inhibitory mechanisms and provide a potential structural platform for designing therapeutic drugs to manipulate cholinergic neuron activity. Combined with the functional analysis, this study provides a comprehensive view of the structural mechanisms underlying substrate specificity, substrate/ion co-transport, and drug inhibition of a physiologically important symporter.

Structural basis for ligand recognition of the human hydroxycarboxylic acid receptor HCAR3

Hydroxycarboxylic acid receptor 3 (HCAR3), a class A G-protein-coupled receptor, is an important cellular energy metabolism sensor with a key role in the regulation of lipolysis in humans. HCAR3 is deeply involved in many physiological processes and serves as a valuable target for the treatment of metabolic diseases, tumors, and immune diseases. Here, we report four cryoelectron microscopy (cryo-EM) structures of human HCAR3-Gi1 complexes with or without agonists: the endogenous ligand 3-hydroxyoctanoic acid, the drug niacin, the highly subtype-specific agonist compound 5c (4-(n-propyl)amino-3-nitrobenzoic acid), and the apo form. Together with mutagenesis and functional analyses, we revealed the recognition mechanisms of HCAR3 for different agonists. In addition, the key residues that determine the ligand selectivity between HCAR2 and HCAR3 were also illuminated. Overall, these findings provide a structural basis for the ligand recognition, activation, and selectivity and G-protein coupling mechanisms of HCAR3, which contribute to the design of HCAR3-targeting drugs with high efficacy and selectivity.

Triple-Action Therapy: Combining Machine Learning, Docking, and Dynamics to Combat BRCA1-Mutated Breast Cancer

Breast cancer dominates women's mortality, and among other factors, mutations in the BRCA1 gene are significant risk factors. Several approaches are followed to treat the BRCA1 affected cancer patients. However, specific BRCA1 inhibitors are not available till date due to its structural complexity. In addition, there are several limitations associated with the existing drugs used to treat BRCA1-related breast cancer and some side effects. The side effects include symptoms such as hot flashes, joint pain, nausea, fatigue, hair loss, diarrhea, chills, fever, and others. Therefore, advanced approaches needed that can overcome all the limitations and side effects of the current inhibitors. In this study, we adopted a multistep approach to identify potential inhibitors for BRCA1-mutated breast cancer. We used our developed machine learning models to screen potential inhibitors. Molecular docking approach was carried out for the screened hit compounds with BRCA1 and its mutated forms. Two ligands, β-amyrin and Narirutin, has shown significant performance in multiple scoring schemes such as molecular docking and RF score calculations. Molecular dynamics simulations demonstrated the stability of the complexes formed by β-amyrin and Narirutin with BRCA1, with lower RMSD values and less RMSF fluctuations at the binding site locations. Principal component analysis (PCA) and free energy landscape (FEL) further confirmed the compactness and favorable binding of β-Amyrin and Narirutin to BRCA1. These findings suggest that β-amyrin and Narirutin have potential as therapeutic agents against BRCA1-mutated breast cancer.

First-in-class mitogen-activated protein kinase (MAPK) p38α: MAPK-activated protein kinase 2 dual signal modulator with anti-inflammatory and endothelial-stabilizing properties

We previously identified a small molecule, UM101, predicted to bind to the substrate-binding groove of p38α mitogen-activated protein kinase (MAPK) near the binding site of its proinflammatory substrate, mitogen-activated protein kinase-activated protein kinase (MK)2. UM101 exhibited anti-inflammatory, endothelial-stabilizing, and lung-protective effects. To overcome its limited aqueous solubility and p38α binding affinity, we designed an analog of UM101, GEn-1124, with improved aqueous solubility, stability, and p38α-binding affinity. Compared with UM101, GEn-1124 has 18-fold greater p38α-binding affinity as measured by surface plasmon resonance, 11-fold greater aqueous solubility, enhanced barrier-stabilizing activity in thrombin-stimulated human pulmonary artery endothelial cells in vitro, and greater lung protection in vivo. GEn-1124 improved survival from 10%-40% in murine acute lung injury induced by combined exposure to intratracheal bacterial endotoxin lipopolysaccharide instillation and febrile-range hyperthermia and from 0% to 50% in a mouse influenza pneumonia model. Gene expression analysis by RNASeq in tumor necrosis factor α-treated human pulmonary artery endothelial cells showed that the gene-modifying effects of GEn-1124 were much more restricted to tumor necrosis factor α-inducible genes than those of the catalytic site p38 inhibitor, SB203580. Gene expression pathway analysis, confocal immunofluorescence analysis of p38α and MK2 subcellular trafficking, and surface plasmon resonance analysis of phosphorylated p38α:MK2 binding affinity supports a novel mechanism of action. GEn-1124 destabilizes the activated p38α:MK2 complex and dissociates nuclear export of MK2 and p38α, thereby promoting intranuclear retention and enhanced intranuclear signaling by phosphorylated p38α and accelerated inactivation of p38-free cytosolic MK2 by unopposed phosphatases. SIGNIFICANCE STATEMENT: We describe a novel analog of our first-in-class small molecule modulator of p38α/MK2 signaling targeted to a pocket near the glutamate-aspartate-containing substrate binding domain of p38α, which destabilizes the p38α:MK2 complex without blocking p38 catalytic activity or ablating downstream signaling. The result is a rebalancing of downstream proinflammatory and anti-inflammatory signaling, yielding anti-inflammatory, endothelial-stabilizing, and lung-protective effects with therapeutic potential in acute respiratory distress syndrome.

3T-VASP: fast ab-initio electrochemical reactor via multi-scale gradient energy minimization

Ab-initio methods such as density functional theory (DFT) is useful for fundamental atomistic-level study and is widely used across many scientific fields, including for the discovery of electrochemical reaction byproducts. However, many DFT steps may be needed to discover rare electrochemical reaction byproducts, which limits DFT's scalability. In this work, we demonstrate that it is possible to generate many elementary electrochemical reaction byproducts in-silico using just a small number of ab-initio energy minimization steps if it is done in a multi-scale manner, such as via previously reported tiered tensor transform (3T) method. We first demonstrate the algorithm through a simple example of a complex floppy organic molecule passivator binding onto perovskite solar cell surface defect site. We then demonstrate more complex examples by generating hundreds of electrochemical reaction byproducts in lithium-ion battery liquid electrolyte (many are verified in previous experimental studies), with most trajectories completed within 50-100 DFT steps as opposed to more than 10,000 steps typically utilized in an ab-initio molecular dynamics trajectory. This approach requires no machine learning training data generation and can be directly applied on any new chemistries, making it suitable for ab-initio elementary chemical reaction byproduct investigation when temperature dependence is not required.

Design and Synthesis of Triazine-Based Hydrogel for Combined Targeted Doxorubicin Delivery and PI3K Inhibition

Melanoma, an aggressive skin cancer originating from melanocytes, presents substantial challenges due to its high metastatic potential and resistance to conventional therapies. Hydrogels, three-dimensional networks of hydrophilic polymers with high water-retention capacities, offer significant promise for controlled drug delivery applications. In this study, we report the synthesis and characterization of hydrogelators based on the triazine molecular scaffold, which self-assemble into fibrous networks conducive to hydrogel formation. Rheological analysis confirmed their hydrogelation properties, while microscopic techniques including FE-SEM and FEG-TEM provided insights into their morphological networks. The drug delivery capability of these hydrogelators was evaluated using doxorubicin, a widely employed anticancer agent, demonstrating enhanced biocompatibility and reduced side effects compared to free doxorubicin. Additionally, the hydrogelators exhibited inhibitory activity against phosphoinositide 3-kinase (PI3K), a key enzyme frequently mutated in cancer, and also involved in melanoma progression. The dual functionality of this delivery system - controlled drug release and PI3K inhibition - highlights the potential of triazine-based hydrogelators as innovative therapeutic platforms for melanoma treatment.

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

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

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

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

Ordered assemblies of peptide nanoparticles with only positive charge

Surface charge patchiness of different charge types can influence the solution behaviours of colloidal particles and globular proteins. Herein, coiled-coil 'bundlemer' nanoparticles that display only a single type of surface charge (SC) are computationally designed to compare their solution behaviours to mixed charge-type (MC) counterparts with both positively and negatively charged side chains. Nematic and columnar liquid crystal phases are discovered in low concentrations of SC particles, indicative of particle end-to-end stacking into columns combined with lateral electrostatic repulsion between columns, while MC particles with the same net charge and particle shape produced only amorphous, soluble aggregates. Similarly, porous lattices are formed in mixtures of SC/MC particles of opposite charges while MC/MC mixtures of opposite charges produce only amorphous aggregates. The lattice structure is inferred with a machine learning optimization approach. The differences between SC and MC particle behaviours directly show the importance of surface electrostatic patchiness.

In silico study of novel coumarin derivatives as potential agents in the pancreatic cancer treatment

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest diseases. Here are investigated two synthesized and two hypothetical coumarin derivatives, and their capacity to be used in the PDAC targeted treatment. The inhibitory activity of these four molecules against PARP, ATM, and CHK1 proteins responsible for DNA molecule repair was examined by docking and molecular dynamic analysis. ADMET analysis was applied to determine the pharmacokinetic properties of the tested compounds. The applied theoretical approach showed that the biomedical activity of the investigated coumarins is comparable to the inhibitory activity and pharmacokinetic properties of Olaparib, already used in the PDAC treatment.

Rapid Coaggregation of Proteins Without Sequence Similarity: Possible Role of Conformational Complementarity

Despite extensive research on the sequence-determined self-assembly of both pathogenic and nonpathogenic proteins, the question of how the sequence identity would influence the coassembly or cross-seeding of diverse proteins without distinct sequence similarity remains largely unanswered. Here, we demonstrate that the rapid coaggregation of proteins with negligible sequence similarity is fundamentally governed by preferred heteromeric interactions between their partially unfolded states via the gain of additional charge complementarity and hydrophobic interactions. The partial loss of intramolecular interactions and concurrent gain of non-native intrinsically disordered regions with sticky groups become crucial for both aggressive heteromeric primary nucleation and secondary nucleation events. The results signify the direct relevance of sequence-independent conformational cross-talk between diverse proteins to the foundational events required for the growth of biological multiprotein amyloid deposits.

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

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

Modeling the relative response factor of small molecules in positive electrospray ionization

Technological advancements in liquid chromatography (LC) electrospray ionization (ESI) high-resolution mass spectrometry (HRMS) have made it an increasingly popular analytical technique in non-targeted analysis (NTA) of environmental and biological samples. One critical limitation of current methods in NTA is the lack of available analytical standards for many of the compounds detected in biological and environmental samples. Computational approaches can provide estimates of concentrations by modeling the relative response factor of a compound (RRF) expressed as the peak area of a given peak divided by its concentration. In this paper, we explore the application of molecular dynamics (MD) in the development of a computational workflow for predicting RRF. We obtained measurements of RRF for 48 compounds with LC - quadrupole time-of-flight (QTOF) MS and calculated their RRF. We used the CGenFF force field to generate the topologies and GROMACS to conduct the (MD) simulations. We calculated the Lennard-Jones and Coulomb interactions between the analytes and all other molecules in the ESI droplet, which were then sampled to construct a multilinear regression model for predicting RRF using Monte Carlo simulations. The best performing model showed a coefficient of determination (R 2) of 0.82 and a mean absolute error (MAE) of 0.13 log units. This performance is comparable to other predictive models including machine learning models. While there is a need for further evaluation of diverse chemical structures, our approach showed promise in predictions of RRF.

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

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

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

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