Practical considerations for building GROMOS-compatible small-molecule topologies

Unraveling the Molecular Mechanisms of Alcohol-Mediated Skin Permeation Enhancement: Insights from Molecular Dynamics Simulations

The application of alcohols as permeation enhancers in pharmaceutical and cosmetic formulations has attracted considerable attention, owing to their skin permeation-enhancing effect. Nonetheless, the elucidation of the fundamental mechanisms underlying the skin permeation-enhancing effect remains elusive. In this study, molecular dynamics (MD) simulations were employed to investigate the effect of 1,2-propanediol (1,2-PDO), 1,2-butanediol (1,2-BDO), and ethanol (EtOH) on the stratum corneum (SC) model membrane. The results showed that the effect of alcohols on the SC model membrane displayed a concentration-dependent nature. The alcohols can interact with SC lipids and exhibit a remarkable ability to selectively extract free fatty acid (FFA) molecules from the SC model membrane and make the SC looser. Meanwhile, 1,2-BDO and EtOH can penetrate into SC lipid bilayers at higher concentrations, leading to the formation of continuous hydrophilic defects in SC. The FFA extraction and the formation of continuous hydrophilic defects induced ceramide (CER) tail chains to become more disordered and fluid and also weakened the hydrogen bonding (H-bonding) network among SC lipids. Both the FFA extraction and the continuous hydrophilic defect formation endowed alcohols with the permeation-enhancing effect. The constrained simulations revealed that the free energy barriers decreased for the permeation of the hydrophilic model molecule (COL) across the SC model membranes containing alcohols, particularly for 1,2-BDO and EtOH. The possible permeation-enhancing mechanisms of alcohols were proposed correspondingly. This work not only provided a deep understanding of the transdermal permeation-enhancing behavior of alcohols at the molecular level but also provided necessary reference information for designing effective transdermal drug delivery systems in applications.

Theoretical models of staurosporine and analogs uncover detailed structural information in biological solution

Staurosporine and its analogs (STA-analogs) are indolocarbazoles (ICZs) compounds able to inhibit kinase proteins in a non-specific way, while present antimicrobial and cytostatic properties. The knowledge of molecular features associated to the complexation, including the ligand shape in solution and thermodynamics of complexation, is substantial to the development of new bioactive ICZs with improved therapeutic properties. In this context, the empirical approach of GROMOS force field is able to accurately reproduce condensed phase physicochemical properties of molecular systems after parameterization. Hence, through parameterization under GROMOS force field and molecular simulations, we assessed STA-analogs dynamics in aqueous solution, as well as its interaction with water to probe conformational and structural features involved in complexation to therapeutic targets. The coexistence of multiple conformers observed in simulations, and confirmed by metadynamics calculations, expanding the conformational space knowledge of these ligands with potential implications in understanding the ligand conformational selection during complexation. Also, changes in availability to H-bonding concerning the different substituents and water can reflect on effects at complexation free energy due to variation at the desolvation energetic costs. Based on these results, we expect the obtained structural data provide systemic framework for rational chemical modification of STA-analogs.

Identifying potent inhibitory phytocompounds from Lagerstroemia speciosa against SARS-Coronavirus-2: structure-based virtual screening

The ongoing spillover of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) calls for expedited countermeasure through developing therapeutics from natural reservoirs and/or the use of less time-consuming drug discovery methodologies. This study aims to apply these approaches to identify potential blockers of the virus from the longstanding medicinal herb, Lagerstroemia speciosa, through comprehensive computational-based screening. Nineteen out of 22 L. speciosa phytochemicals were selected on the basis of their pharmacokinetic properties. SARS-CoV-2 Main protease (Mpro), RNA-directed RNA polymerase (RdRp), Envelope viroporin protein (Evp) and receptor-binding domain of Spike glycoprotein (S-RBD), as well as the human receptor Angiotensin-converting enzyme-2 (hACE2) were chosen as targets. The screening was performed by molecular docking, followed by 100-ns molecular dynamic simulations and free energy calculations. 24-Methylene cycloartanol acetate (24MCA) was found as the best inhibitor for both Evp and RdRp, and sitosterol acetate (SA) as the best hit for Mpro, S-RBD and hACE2. Dynamic simulations, binding mode analyses, free energy terms and share of key amino acids in protein-drug interactions confirmed the stable binding of these phytocompounds to the hotspot sites on the target proteins. With their possible multi-targeting capability, the introduced phytoligands might offer promising lead compounds for persistent fight with the rapidly evolving coronavirus. Therefore, experimental verification of their safety and efficacy is recommended.

DFT, ADME studies and evaluation of the binding with HSA and MAO-B inhibitory potential of protoberberine alkaloids from Guatteria friesiana: theoretical insights of promising candidates for the treatment of Parkinson's disease

CONTEXT

Parkinson's disease is a chronic neurodegenerative condition that has no cure, characterized by the progressive degeneration of specific brain cells responsible for producing dopamine, a crucial neurotransmitter for controlling movement and muscle coordination. Parkinson's disease is estimated to affect around 1% of the world's population over the age of 60, but it can be diagnosed at younger ages. One of the treatment strategies for Parkinson's disease involves the use of drugs that aim to increase dopamine levels or simulate the action of dopamine in the brain. A class of commonly prescribed drugs are the so-called monoamine oxidase B (MAO-B) inhibitors due to the fact that this enzyme is responsible for metabolizing dopamine, thus reducing its levels in the brain. Studies have shown that berberine-derived alkaloids have the ability to selectively inhibit MAO-B activity, resulting in increased dopamine availability in the brain. In this context, berberine derivatives 13-hydroxy-discretinine and 7,8-dihydro-8-hydroxypalmatine, isolated from Guatteria friesiana, were evaluated via density functional theory followed by ADME studies, docking and molecular dynamic simulations with MAO-B, aiming to evaluate their anti-Parkinson potential, which have not been reported yet. Docking simulations with HSA were carried out aiming to evaluate the transport of these molecules through the circulatory system.

METHODS

The 3D structures of the berberine-derived alkaloids were modeled via the DFT approach at B3LYP-D3(BJ)/6-311 + + G(2df, 2pd) theory level using Gaussian 09 software. Solvation free energies were determined through Truhlar's solvation model. MEP and ALIE maps were generated with Multiwfn software. Autodock Vina software was used for molecular docking simulations and analysis of the interactions in the binding sites. The 3D structure of MAO-B was obtained from the Protein Data Bank website under PDB code 2V5Z. For the interaction of studied alkaloids with human serum albumin (HSA) drug sites, 3D structures with PDB codes 2BXD, 2BXG, and 4L9K were used. Molecular dynamics simulations were carried out using GROMACS 2019.4 software, with the GROMOS 53A6 force field at 100 ns simulation time. The estimation of the ligand's binding free energies was obtained via molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method.

Long-range communication between transmembrane- and nucleotide-binding domains does not depend on drug binding to mutant P-glycoprotein

In this study, the impact of four P-gp mutations (G185V, G830V, F978A and ΔF335) on drug-binding and efflux-related signal-transmission mechanism was comprehensively evaluated in the presence of ligands within the drug-binding pocket (DBP), experimentally related with changes in their drug efflux profiles. The severe repacking of the transmembrane helices (TMH), induced by mutations and exacerbated by the presence of ligands, indicates that P-gp is sensitive to perturbations in the transmembrane region. Alterations on drug-binding were also observed as a consequence of the TMH repacking, but were not always correlated with alterations on ligands binding mode and/or binding affinity. Finally, and although all P-gp variants holo systems showed considerable changes in the intracellular coupling helices/nucleotide-binding domain (ICH-NBD) interactions, they seem to be primarily induced by the mutation itself rather than by the presence of ligands within the DBP. The data further suggest that the changes in drug efflux experimentally reported are mostly related with changes on drug specificity rather than effects on signal-transmission mechanism. We also hypothesize that an increase in the drug-binding affinity may also be related with the decreased drug efflux, while minor changes in binding affinities are possibly related with the increased drug efflux observed in transfected cells.Communicated by Ramaswamy H. Sarma.

A Drug Repurposing Approach to Identify Therapeutics by Screening Pathogen Box Exploiting SARS-CoV-2 Main Protease

Coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus -2 (SARS-CoV-2) and is responsible for a higher degree of morbidity and mortality worldwide. There is a smaller number of approved therapeutics available to target the SARS-CoV-2 virus, and the virus is evolving at a fast pace. So, there is a continuous need for new therapeutics to combat COVID-19. The main protease (Mpro ) enzyme of SARS-CoV-2 is essential for replication and transcription of the viral genome, thus could be a potent target for the treatment of COVID-19. In the present study, we performed an in-silico screening analysis of 400 diverse bioactive inhibitors with proven antibacterial and antiviral properties against Mpro drug target. Ten compounds showed a higher binding affinity for Mpro than the reference compound (N3), with desired physicochemical properties. Furthermore, in-depth docking and superimposition revealed that three compounds (MMV1782211, MMV1782220, and MMV1578574) are actively interacting with the catalytic domain of Mpro . In addition, the molecular dynamics simulation study showed a solid and stable interaction of MMV178221-Mpro complex compared to the other two molecules (MMV1782220, and MMV1578574). In line with this observation, MM/PBSA free energy calculation also demonstrated the highest binding free energy of -115.8 kJ/mol for MMV178221-Mpro compound. In conclusion, the present in silico analysis revealed MMV1782211 as a possible and potent molecule to target the Mpro and must be explored in vitro and in vivo to combat the COVID-19.

Modeling the structure and reactivity landscapes of a pyrazole-ammonium ionic derivative using wavefunction-dependent characteristics and screening for potential anti-inflammatory activity

Spectroscopic investigations of 1-phenyl -2,3-dimethyl-5-oxo-1,2-dihydro-1H-pyrazol-4-ammonium 2[(2-carboxyphenyl) disulfanyl]benzoate (PACB) reported experimentally and theoretically. NH-O interaction is observed and there is a very large downshift for NH-O stretching frequency. Reactive sites are identified from the chemical and electronic properties. For PACB the maximum repulsion was around H33, H55 and H57 atom. LOL shows red regions between C-C and blue around C atoms are surrounded by a delocalized electron cloud. The red ring is a hallmark of electron density depletion from the NCI plot due to electrostatic repulsion and its existences suggests that coordination sphere for PACB is minimally strained around the central ion. Atomic contact energy values and high score of the docking results obtained propose that, PACB may have inhibitory properties and have a significant function in pharmacological chemistry. Molecular dynamics simulation was performed to validate the stability of the title compound with the Bovine thrombin-activatable fibrinolysis inhibitor protein.Communicated by Ramaswamy H. Sarma.

In silico analysis of a novel protein in CAR T- cell therapy for the treatment of hematologic cancer through molecular modelling, docking, and dynamics approach

Cellular therapy has emerged as a key tool in the treatment of hematological malignancies. An advanced cell therapy known as chimeric antigen receptor T cell therapy (CAR T-cell therapy) has been approved by the United States Food and Drug Administration (FDA) as KYMRIAH by Novartis and YESCARTA by Gilead/Kite pharma in the year 2017. A chimeric receptor is composed of an extracellular antigen recognition site along with some co-stimulating and signalling domains. On the whole, it turns out to be one of the most potent receptors on T cells targeting a specific type of cancer cell based on its antigenic marker. CD19 CAR T-cell therapy is the first clinically approved therapy for lymphoma with remarkable results in complete remission of B cell lymphoblastic leukemia up to 90%. The high rate of effectiveness of the CAR T-cell therapy against B-ALL justifies the investigation and application of this therapy for fatal diseases like all types of hematological malignancies. The most critical aspect of chimeric receptor therapy is designing and building an artificial receptor that is specific to a given type of cancer. For this reason, the in silico technique is an appropriate model to investigate the integrity and effectiveness of the engineered chimeric receptor prior to commencing in vitro experiments followed by clinical trials. This computerized experimental study aids in predicting the molecular mechanism of chimeric protein and how it interacts with both ligands. We have anticipated various features of the chimeric protein in terms of qualitative analysis (structure, protein modelling, physiological properties) and functional analysis (antigenicity, allergenicity, its receptor-ligand binding ability, involving signalling pathways). Furthermore, the reliability and validation of the binding mode of the chimeric protein against receptors were performed through a complex molecular dynamics simulation for a 100 ns timeframe in an aqueous environment. The obtained simulation study showed that CD30 was a better approachable marker as compared to CD20 due to its better binding energy score and also binding conformations stability.

Non-monotonic composition dependence of the breakdown of Stokes-Einstein relation for water in aqueous solutions of ethanol and 1-propanol: explanation using translational jump-diffusion approach

A series of experimental and simulation studies examined the validity of the Stokes-Einstein relationship (SER) of water in binary water/alcohol mixtures of different mixture compositions. These studies revealed a strong non-monotonic composition dependence of the SER with maxima at the specific alcohol mole fraction where the non-idealities of the thermodynamic and transport properties are observed. The translational jump-diffusion (TJD) approach elucidated the breakdown of the SER in pure supercooled water as caused by the jump translation of molecules. The breakdown of SER in the supercooled water/methanol binary mixture was successfully explained using the same TJD approach. To further generalize the picture, here we focus on the non-monotonic composition dependence of SER breakdown of water in two water/alcohol mixtures (water/ethanol and water/propanol) for a broad temperature range. In agreement with previous studies, maximum breakdown of SER is observed for the mixture with alcohol mole fraction x = 0.2. Diffusion of the water molecules at the maximum SER breakdown point is largely contributed by jump-diffusion. The residual-diffusion, obtained by subtracting the jump-diffusion from the total diffusion, approximately follows the SER for different compositions and temperatures. We also performed hydrogen (H-)bond dynamics and observed that the contribution of jump-diffusion is proportional to the total free energy of activation of breaking all H-bonds that exist around a molecule. This study, therefore, suggests that the more a molecule is trapped by H-bonding, the more likely it is to diffuse through the jump-diffusion mechanism, eventually leading to an increasing degree of SER breakdown.

Functional-Group Effect of Ligand Molecules on the Aggregation of Gold Nanoparticles: A Molecular Dynamics Simulation Study

In this paper, atomistic molecular dynamics simulations are performed for the systems consisting of functionalized gold nanoparticles (NPs) in a toluene medium. Gold NPs are coated with ligand molecules that have different terminal groups, that is, polar carboxyl (COOH), hydroxyl (OH), amine (NH₂), and nonpolar methyl (CH₃). These functional groups are selected to understand the relation between the aggregation behavior of functionalized gold NPs in toluene and the polarity of terminal groups of ligand molecules. The center-of-mass distances between NP pairs, the radial distribution functions, the mean square displacements, the radius of gyration, and the number of hydrogen bonds (H-bond) between ligand molecules are computed. Our simulation results indicate that functionalized gold NPs exhibit different aggregation/dispersion behaviors depending upon the terminal group of ligands.

In silico and in vitro study of Mycobacterium tuberculosis H37Rv uncharacterized protein (RipD): an insight on tuberculosis therapeutics

Tuberculosis caused by Mycobacterium tuberculosis (Mtb) is responsible for the highest global health problem, with the deaths of millions of people. With prevalence of multiple drug resistance (MDR) strains and extended therapeutic times, it is important to discover small molecule inhibitors against novel hypothetical proteins of the pathogen. In this study, a virtual screening protocol was carried out against MtbH37Rv hypothetical protein RipD (Rv1566c) for the identification of potential small molecule inhibitors. The 3D model of the protein structure binding site was used for virtual screening (VS) of inhibitors from the Pathogen Box, followed by its validation through a molecular docking study. The stability of the protein-ligand complex was assessed using a 150 ns molecular dynamics simulation. MM-PBSA and MM-GBSA are the two approaches that were used to perform the trajectory analysis and determine the binding free energies, respectively. The ligand binding was observed to be stable across the entire time frame with an approximate binding free energy of -22.9916 kcal/mol. The drug-likeness of the inhibitors along with a potential anti-tuberculosis compound was validated by ADMET prediction software. Furthermore, a CFU inhibition assay was used to validate the best hit compound's in vitro inhibitory efficacy against a non-pathogenic Mycobacterium smegmatis MC2155 under low nutrient culture conditions. The study reported that the compound proposed in our study (Pathogen Box ID: MMV687700) will be useful for the identification of potential inhibitors against Mtb in future.

Umbrella Sampling Simulations of Carbon Nanoparticles Crossing Immiscible Solvents

We use molecular dynamics to compute the free energy of carbon nanoparticles crossing a hydrophobic–hydrophilic interface. The simulations are performed on a biphasic system consisting of immiscible solvents (i.e., cyclohexane and water). We solvate a carbon nanoparticle into the cyclohexane layer and use a pull force to drive the nanoparticle into water, passing over the interface. Next, we accumulate a series of umbrella sampling simulations along the path of the nanoparticle and compute the solvation free energy with respect to the two solvents. We apply the method on three carbon nanoparticles (i.e., a carbon nanocone, a nanotube, and a graphene nanosheet). In addition, we record the water-accessible surface area of the nanoparticles during the umbrella simulations. Although we detect complete wetting of the external surface of the nanoparticles, the internal surface of the nanotube becomes partially wet, whereas that of the nanocone remains dry. This is due to the nanoconfinement of the particular nanoparticles, which shields the hydrophobic interactions encountered inside the pores. We show that cyclohexane molecules remain attached on the concave surface of the nanotube or the nanocone without being disturbed by the water molecules entering the cavity.

In Silico Evaluation of Binding of 2-Deoxy-D-Glucose with Mpro of nCoV to Combat COVID-19

COVID-19 has threatened the existence of humanity andthis infection occurs due to SARS-CoV-2 or novel coronavirus, was first reported in Wuhan, China. Therefore, there is a need to find a promising drug to cure the people suffering from the infection. The second wave of this viral infection was shaking the world in the first half of 2021. Drugs Controllers of India has allowed the emergency use of 2-deoxy-D-glucose (2DG) in 2021 for patients suffering from this viral infection. The potentiality of 2-deoxy-D-glucose to intervene in D-glucose metabolism exists and energy deprivation is an effective parameter to inhibit cancer cell development. Once 2DG arrives in the cells, it becomes phosphorylated to 2-deoxy-D-glucose-6-phosphate (2-DG6P), a charged molecule expressively captured inside the cells. On the other hand, 2DG lacks the ability to convert into fructose-6-phosphate, resulting in a hampering of the activity of both glucose-6-phosphate isomerase and hexokinase, and finally causing cell death. Hence, the potential and effectiveness of 2DG with the main protease (Mpro) of novel coronavirus (nCoV) should be investigated using the molecular docking and molecular dynamics (MD) simulations. The ability of 2DG to inhibit the Mpro of nCoV is compared with 2-deoxyglucose (2DAG), an acyclic molecule, and 2-deoxy-D-ribose (2DR). The binding energy of the molecules with the Mpro of nCoV is calculated using molecular docking and superimposed analysis data is obtained. The binding energy of 2DG, 2DR and 2DAG was −2.40, −2.22 and −2.88 kcal/mol respectively. Although the molecular docking does not provide reliable information, therefore, the binding affinity can be confirmed by molecular dynamics simulations. Various trajectories such as Rg, RMSD, RMSF, and hydrogen bonds are obtained from the molecular dynamics (MD) simulations. 2DG was found to be a better inhibitor than the 2DAG and 2DR based on the results obtained from the MD simulations at 300 K. Furthermore, temperature-dependent MD simulations of the Mpro of nCoV with promising 2DG was performed at 295, 310 and 315 K, and the effective binding with the Mpro of nCoV occurred at 295 K. With the use of DFT calculations, optimized geometry and localization of electron density of the frontier molecular orbitals were calculated.

Molecular dynamics: a powerful tool for studying the medicinal chemistry of ion channel modulators

Molecular dynamics (MD) simulations allow researchers to investigate the behavior of desired biological targets at ever-decreasing costs with ever-increasing precision. Among the biological macromolecules, ion channels are remarkable transmembrane proteins, capable of performing special biological processes and revealing a complex regulatory matrix, including modulation by small molecules, either endogenous or exogenous. Recently, given the developments in ion channel structure determination and accessibility of bio-computational techniques, MD and related tools are becoming increasingly popular in the intense research area regarding ligand-channel interactions. This review synthesizes and presents the most important fields of MD involvement in investigating channel-molecule interactions, including, but not limited to, deciphering the binding modes of ligands to their ion channel targets and the mechanisms through which chemical compounds exert their effect on channel function. Special attention is devoted to the importance of more elaborate methods, such as free energy calculations, while principles regarding drug design and discovery are highlighted. Several technical aspects involving the creation and simulation of channel-molecule MD systems (ligand parameterization, proper membrane setup, system building, etc.) are also presented.

Identification of new alpha-synuclein fibrillogenesis inhibitor using in silico structure-based virtual screening

Abnormal aggregation and accumulation of alpha-synuclein (αSN) in existing neurons is associated with Parkinson's disease (PD) as one of the age-related neurodegenerative disorders. Inhibition of αSN fibrillogenesis could be considered as a solution for PD diseases treatment. Here, virtual screening (VS) approach was used to investigate available ligands in PubChem library with structural similarity with Dihydromyricetin (DHM) (as a recently introduced suitable candidate for designing of novel antiPD drugs) against aggregation of αSN chains. Primary screening identified 314 promising molecules for αSN monomer, which were further analyzed in details by their binding energy and binding modes through molecular docking method. Evidently, the compound with PubChem ID of 100968625 displayed the lowest free binding energy with ΔG⁰ = -7.1 kcal.mol^-1 and was selected for further analysis using molecular dynamics (MD) simulation method. Analysis of MD trajectories showed that molecules of the selected ligand interact with αSN trimer via H-bond interaction and destabilize the compact structure of αSN trimer. Further, prompt in vivo testing to validate the antiPD inhibition efficiency by this molecule can save lives.

On the Consistency of the Exfoliation Free Energy of Graphenes by Molecular Simulations

Monolayer graphene is now produced at significant yields, by liquid phase exfoliation of graphites in solvents. This has increased the interest in molecular simulation studies to give new insights in the field. We use decoupling simulations to compute the exfoliation free energy of graphenes in a liquid environment. Starting from a bilayer graphene configuration, we decouple the Van der Waals interactions of a graphene monolayer in the presence of saline water. Then, we introduce the monolayer back into water by coupling its interactions with water molecules and ions. A different approach to compute the graphene exfoliation free energy is to use umbrella sampling. We apply umbrella sampling after pulling the graphene monolayer on the shear direction up to a distance from a bilayer. We show that the decoupling and umbrella methods give highly consistent free energy results for three bilayer graphene samples with different size. This strongly suggests that the systems in both methods remain closely in equilibrium as we move between the states before and after the exfoliation. Therefore, the amount of nonequilibrium work needed to peel the two layers apart is minimized efficiently.

Mutations in passive residues modulate 3D-structure of NDM (New Delhi metallo-β-lactamase) protein that endue in drug resistance: a MD simulation approach

The ability of antimicrobial resistance developed by bacteria enhanced the complexity of bacterial treatment leading a serious threat to human health. Production of β-lactamase by bacteria that inactivates β-lactam is a generic cause of resistance. One such β-lactamase enzyme is New Delhi Metallo-β-lactamase (NDM) which is recently reported to have clinically more importance and recognized as an antibiotic resistance marker. Mutations in active and passive residues of NDM protein play a fateful role in the substrate and inhibitor specificity. In this study, in silico point mutations of residues near the active site and flexible regions of protein were investigated. Hybrid modelling and molecular dynamics (MD) simulations were carried to build up the mutant models and monitored structural stability. Molecular docking results articulated that mutant proteins had lesser binding affinities with methicillin, oxacillin and doripenem drugs. Further, to scrutinize the structural alterations and rescore the binding energies per-residue basis, MD simulations of wildtype (WT) and mutant (MT) NDM proteins with methicillin, oxacillin and doripenem were performed. Our results demonstrated that mutations in N193A, S217A, G219A and T262A residues led to protein destabilization and amend their binding affinities with methicillin, oxacillin and doripenem. The present study exploited computational approaches which displayed differential binding of drugs with WT and MT NDM proteins that confer resistance to oxacillin and doripenem. The study features the significance of passive residues, thus provides a clue to accelerate the process of designing an ergastic antibiotic against NDM protein. Communicated by Ramaswamy H. Sarma.

New quinoxalin-1,3,4-oxadiazole derivatives: Synthesis, characterization, in vitro biological evaluations, and molecular modeling studies

A new series of quinoxalin-1,3,4-oxadiazole (10a-l) derivatives was synthesized and evaluated against some metabolic enzymes including human carbonic anhydrase (hCA) isoenzymes I and II (carbonic anhydrases I and II), cholinesterase (acetylcholinesterase and butyrylcholinesterase), and α-glucosidase. Obtained data revealed that all the synthesized compounds were more potent as compared with the used standard inhibitors against studied target enzymes. Among the synthesized compounds, 4-fluoro derivative (10f) against hCA I, 4-chloro derivative (10i) against hCA II, 3-fluoro derivative (10e) against acetylcholinesterase and butyrylcholinesterase, and 3-bromo derivative (10k) against α-glucosidase were the most potent compounds with inhibitory activity around 1.8- to 7.37-fold better than standard inhibitors. Furthermore, docking studies of these compounds were performed at the active site of their target enzymes.

Quantitative proteomics and bioinformatics analyses reveal the protective effects of cyanidin-3-O-glucoside and its metabolite protocatechuic acid against 2-amino-3-methylimidazo[4,5-f]quinoline (IQ)-induced cytotoxicity in HepG2 cells via apoptosis-related pathways

The aim of this study was to investigate the mechanism of action of cyanidin-3-O-glucoside (C3G) and its metabolite protocatechuic acid (PCA) mediated protection against 2-amino-3-methylimidazo[4,5-f]quinoline (IQ)-induced cytotoxicity in HepG2 cells. The effects of C3G and PCA on cell viability, LDH release and apoptosis in IQ-induced HepG2 cells were evaluated using CCK-8, LDH release and flow cytometry assays, respectively. TMT-based proteomics was utilized to characterize the proteins and pathways associated with the improvement after C3G and PCA treatment. Results showed that exposure to IQ significantly increased cytotoxicity and apoptosis in HepG2 cells, which were alleviated by C3G and PCA. C3G was more effective than PCA in protecting HepG2 cells against IQ-induced cytotoxicity and regulating the related signaling pathways. Proteomics and bioinformatics analyses and Western blot validation revealed that apoptosis-related signaling pathways played pivotal roles in protecting against the cytotoxicity of IQ by C3G, and XIAP was identified as the target protein. Molecular docking proved that C3G had strong binding affinity to XIAP and hindered the binding of IQ to the BIR3 domain of XIAP, resulting in the inhibition of apoptosis. Our findings suggested that C3G has potential as a preventive food ingredient to prevent carcinogenic risk of heterocyclic aromatic amines.

Docking and molecular dynamics predicted B-DNA and dihydropyrimidinone selenoesters interactions elucidating antiproliferative effects on breast adenocarcinoma cells

Dihydropyrimidinones have demonstrated different biological activities including anticancer properties. Cytotoxic potential and antiproliferative potential of new dihydropyrimidinone-derived selenoesters (Se-DHPM) compounds were assessed in vitro against the breast adenocarcinoma cells (MCF-7). Among the eight Se-DHPM compounds tested just 49A and 49F were the most cytotoxic for MCF-7 and the most selective for the non-tumor strain (McCoy) and reduced cell viability in a time- and concentration-dependent manner. Compounds 49A and 49F increased the rate of cell death due to apoptosis and necrosis comparatively to the control, however only the 49F showed antiproliferative potential, reducing the number of colonies formed. In the molecular assay 49A interacts with CT-DNA and caused hyperchromism while 49F caused a hypochromic effect. The intercalation test revealed that the two compounds caused destabilization in the CT-DNA molecule. This effect was evidenced by the loss of fluorescence when the compounds competed and caused the displacement of propidium iodide. Simulations (docking and molecular dynamics) using B-DNA brought a greater understanding of ligand-B-DNA interactions. Furthermore, they predicted that the compounds act as minor groove ligands that are stabilized through hydrogen bonds and hydrophobic interactions. However, the form of interaction foreseen for 49A was more energetically favorable and had more stable hydrogen bonds during the simulation time. Despite some violations foreseen in the ADMET for 49F, the set of other results point to this Se-DHPM as a promising leader compound with anti-tumor potential for breast cancer.Communicated by Ramaswamy H. Sarma.

Repurposing of approved drug molecules for viral infectious diseases: a molecular modelling approach

The identification of new viral drugs has become a task of paramount significance due to the frequent occurrence of viral infections and especially during the current pandemic. Despite the recent advancements, the development of antiviral drugs has not made parallel progress. Reduction of time frame and cost of the drug development process is the major advantage of drug repurposing. Therefore, in this study, a drug repurposing strategy using molecular modelling techniques, i.e. biological activity prediction, virtual screening, and molecular dynamics simulation was employed to find promising repurposing candidates for viral infectious diseases. The biological activities of non-redundant (4171) drug molecules were predicted using PASS analysis, and 1401 drug molecules were selected which showed antiviral activities in the analysis. These drug molecules were subjected to virtual screening against the selected non-structural viral proteins. A series of filters, i.e. top 10 drug molecules based on binding affinity, mean value of binding affinity, visual inspection of protein-drug complexes, and number of H-bond between protein and drug molecules were used to narrow down the drug molecules. Molecular dynamics simulation analysis was carried out to validate the intrinsic atomic interactions and binding conformations of protein-drug complexes. The binding free energies of drug molecules were assessed by employing MMPBSA analysis. Finally, nine drug molecules were prioritized, as promising repurposing candidates with the potential to inhibit the selected non-structural viral proteins.Communicated by Ramaswamy H. Sarma.

Molecular and functional characterization of spotted snakehead NOD1 with an emphasis on structural insights into iE-DAP binding motifs employing advanced bioinformatic tools

Nucleotide-binding and oligomerization domain (NOD)-like receptors (NLRs) are cytosolic receptors implicated in recognition of intracellular pathogen associated molecular patterns (PAMPs) and danger associated molecular patterns (DAMPs). Depending upon their effector binding domain (EBD) at the C-terminal, the NLRs are categorized into NLRA, NLRB, NLRC, NLRP and NLRX. NOD1 is a pivotal player in immune responses against bacterial and viral invasions and interacts with pathogens via C-terminal leucine rich repeat (LRR) domain. This study aims at characterizing NOD1 in an economically important teleost of the Indian subcontinent, spotted snakehead Channa punctata. The understanding of pathogen-receptor interaction in teleosts is still obscure. In light of this, combinatorial approach involving protein modeling, docking, MD simulation and binding free energy calculation were employed to identify key motifs involved in binding iE-DAP. In silico analysis revealed that NOD1 consists of 943 amino acids comprising of one caspase recruitment domain (CARD) at N-terminal, one central NACHT domain and nine leucine rich repeat (LRR) regions at C-terminal. Structural dynamics study showed that the C-terminal β-sheet LRR4-7 region is involved in iE-DAP binding. NOD1 was ubiquitously and constitutively expressed in all tissues studied. Differential expression profile of NOD1 induced by Aeromonas hydrophila infection was also investigated. Lymphoid organs and phagocytes of infected spotted snakehead showed significant downregulation of NOD1 expression. The current study thus gives an insight into structural and functional dynamics of NOD1 which might have future prospect for structure-based drug designing in teleosts.Communicated by Ramaswamy H. Sarma.

Novel Dihydropyrimidinone-Derived Selenoesters as Potential Cytotoxic Agents to Human Hepatocellular Carcinoma: Molecular Docking and DNA Fragmentation

BACKGROUND AND OBJECTIVE

Evidence point out promising anticancer activities of Dihydropyrimidinones (DHPM) and organoselenium compounds. This study aimed to evaluate the cytotoxic and antiproliferative potential of DHPM-derived selenoesters (Se-DHPM), as well as their molecular mechanisms of action.

METHODS

Se-DHPM cytotoxicity was evaluated against cancer lines (HeLa, HepG2, and MCF-7) and normal cells (McCoy). HepG2 clonogenic assay allowed verifying antiproliferative effects. The propidium iodide/ orange acridine fluorescence readings showed the type of cell death induced after treatments (72h). Molecular simulations with B-DNA and 49H showed docked positions (AutoDock Vina) and trajectories/energies (GROMACS). In vitro molecular interactions used CT-DNA and 49H applying UV-Vis absorbance and fluorescence. Comet assay evaluated DNA fragmentation of HepG2 cells. Flow cytometry analysis verified HepG2 cell cycle effects. Levels of proteins (β-actin, p53, BAX, HIF-1α, γH2AX, PARP-1, cyclin A, CDK-2, and pRB) were quantified by immunoblotting.

RESULTS

Among Se-DHPM, 49H was selectively cytotoxic to HepG2 cells, reduced cell proliferation, and increased BAX (80%), and p53 (66%) causing apoptosis. Molecular assays revealed 49H inserted in the CT-DNA molecule causing the hypochromic effect. Docking simulations showed H-bonds and hydrophobic interactions, which kept the ligand partially inserted into the DNA minor groove. 49H increased the DNA damage (1.5 fold) and γH2AX level (153%). Besides, treatments reduced PARP-1 (60%) and reduced pRB phosphorylation (21%) as well as decreased cyclin A (46%) arresting cell cycle at the G1 phase.

CONCLUSION

Together all data obtained confirmed the hypothesis of disruptive interactions between Se-DHPM and DNA, thereby highlighting its potential as a new anticancer drug.

Glossary of phytoconstituents: Can these be repurposed against SARS CoV-2? A quick in silico screening of various phytoconstituents from plant Glycyrrhiza glabra with SARS CoV-2 main protease

World is familiar with the viral pathogen Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2). The principle working enzymes of SARS CoV-2 have been identified as main proteases 3Cl pro which act as main regulators for SARS infection. The need for therapy is required immediately pertaining to the vulnerable conditions. Protein-ligand studies are imperative for understanding the functioning of biological interactions as they are crucial in providing a hypothetical origin for the design and unearthing of novel drug targets. Phytoconstituents from Glycyrrhiza glabra, earlier reported to be anticancerous in nature were used as repurposed drugs against SARS CoV-2 main protease 3Clpro. We analyzed the molecular interactions of protein-phytocompounds, by AutoDock Vina 4.2 tools. The best interactions of each algorithm were subjected to molecular dynamic (MD) simulations to have an insight of the molecular dynamic mechanisms involved. Selected phytoconstituents gave a good score for binding affinity with the main protease 6LU7 of SARS CoV-2 as compared to the antiviral drugs already being used in the disease therapy. DehydroglyasperinC(-8.7,-8.1,-6.7,-7.1)kcal/mol, Licochalcone D(-8.4,-8.2,-7.1,-7.9) kcal/mol, Liquiritin(-8.6,-9.0,-7.2,-7.8) kcal/mol have showed energy interactions with 3Clpro better than many FDA approved repurposed drugs; Remdesvir, Favipiravir, and Hydroxychloroquine. MD Simulation also corelates our findings for molecular docking studies.

In Silico Prediction of Permeability Coefficients

In silico simulations of biological systems are of the significant importance to obtain insights on specific processes that experimental protocols have difficulty to elucidate. More particularly, and to ensure that a given molecule is able to reach its cellular target, the development of computational methods able to quickly estimate the cellular permeabilities for small molecules can become an important tool in the early stages of drug development. Herein, a computational protocol for predicting permeability coefficients, concerning both membranes and proteins, is presented and discussed.

Identification of potent Antigen 85C inhibitors of Mycobacterium tuberculosis via in-house lichen library and binding free energy studies Part-II

Tuberculosis remains the cause of mortality throughout the world. Currently, the available anti-tubercular drugs are not effective because of the existence of Multi-Drug resistant tuberculosis (MDR-TB) and Extensively-Drug resistant tuberculosis (XDR-TB). It has, therefore, become necessary to develop novel drugs that inhibit the activity of drug-resistant Mycobacterium tuberculosis. Due to the existence of MDR and XDR-TB, Mtb Ag85C has risen out as a propitious molecular drug target as it has importance in the synthesis of main components of the Mtb cell envelope which are essential for the virulence and survival of Mtb. In a previous paper, we studied a potential drug target by virtual high throughput screening of compounds and in continuation of the study on Mtb Ag85C, we further studied the role of lichen compounds in the inhibition of Ag85C. In the current research work, virtual screening of a lichen compounds library was performed against Ag85C. Further, ADMET analysis was employed to filter out the screened lichen compounds. Bioactivity score and toxicity prediction finalized four lichen compounds i.e. Portentol, Aspicilin, Parietinic acid and Polyporic acid as potential inhibitors of Ag85C. The stability and dynamic behavior of four compounds were analyzed by using Molecular dynamics simulation which indicated that they may be potential inhibitors of Ag85C. Therefore, based on the above results, Portentol, Aspicilin, Parietinic acid and Polyporic acid may be potential drug candidates against Mtb. We suggest that the use of these compounds can minimize the treatment time-period and the various side effects associated with the currently available anti-tubercular drugs.

A molecular docking and molecular dynamics simulation study on the interaction between cyanidin-3-O-glucoside and major proteins in cow's milk

The objective of this study was to investigate the molecular interaction and complex stability of four major cow's milk (CM) proteins (α-LA, β-LG, α_s1 -CA, and β-CA) with cyanidin-3-O-glucoside (C3G) using computational methods. The results of molecular docking analysis revealed that hydrogen bond and hydrophobic interaction were the main binding forces to maintain the stability of the C3G-CM protein complexes. Molecular dynamics simulation results showed that all complexes except for C3G-α_s1 -CA were found to reach equilibrium within 50 ns of simulation. α_s1 -CA and β-CA switched to a more compact conformation after binding with C3G. Additionally, the radius of gyration, number of hydrogen bond, radial distribution function, and interaction energy showed that β-CA is the best C3G carrier protein among the four CM proteins. This study can provide valuable information for CM proteins to serve as C3G delivery carriers. PRACTICAL APPLICATIONS: Anthocyanins (ACNs) are flavonoid-based pigments that play an important functional role in regulating human's health. Cow's milk (CM) proteins are the most representative protein-based carriers that can improve the short-term bioavailability and stability of ACNs. Thus, it is important to study the interactions between ACNs and CM proteins at the molecular level for the development of effective ACNs delivery carriers. Our study showed that caseins (α_s1 -CA and β-CA) had more hydrophobic and hydrogen-bonding sites with cyanidin-3-O-glucoside (C3G) than whey proteins using computational methods. Among the four CM proteins, β-CA was the best C3G carrier protein showing the best interaction stability with C3G. Thus, it is helpful for us to screen effective ACNs carriers from multiple protein sources by computational methods.

Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation

BACKGROUND

The vast geographical expansion of novel coronavirus and an increasing number of COVID-19 affected cases have overwhelmed health and public health services. Artificial Intelligence (AI) and Machine Learning (ML) algorithms have extended their major role in tracking disease patterns, and in identifying possible treatments.

OBJECTIVE

This study aims to identify potential COVID-19 protease inhibitors through shape-based Machine Learning assisted by Molecular Docking and Molecular Dynamics simulations.

METHODS

31 Repurposed compounds have been selected targeting the main coronavirus protease (6LU7) and a machine learning approach was employed to generate shape-based molecules starting from the 3D shape to the pharmacophoric features of their seed compound. Ligand-Receptor Docking was performed with Optimized Potential for Liquid Simulations (OPLS) algorithms to identify highaffinity compounds from the list of selected candidates for 6LU7, which were subjected to Molecular Dynamic Simulations followed by ADMET studies and other analyses.

RESULTS

Shape-based Machine learning reported remdesivir, valrubicin, aprepitant, and fulvestrant as the best therapeutic agents with the highest affinity for the target protein. Among the best shape-based compounds, a novel compound identified was not indexed in any chemical databases (PubChem, Zinc, or ChEMBL). Hence, the novel compound was named 'nCorv-EMBS'. Further, toxicity analysis showed nCorv-EMBS to be suitable for further consideration as the main protease inhibitor in COVID-19.

CONCLUSION

Effective ACE-II, GAK, AAK1, and protease 3C blockers can serve as a novel therapeutic approach to block the binding and attachment of the main COVID-19 protease (PDB ID: 6LU7) to the host cell and thus inhibit the infection at AT2 receptors in the lung. The novel compound nCorv- EMBS herein proposed stands as a promising inhibitor to be evaluated further for COVID-19 treatment.

Nitrogen-containing naringenin derivatives for reversing multidrug resistance in cancer

Naringenin (1), isolated from Euphorbia pedroi, was previously derivatized yielding compounds 2-13. In this study, aiming at expanding the pool of analogues of the flavanone core towards better multidrug resistance (MDR) reversal agents, alkylation reactions and chemical modification of the carbonyl moiety was performed (15-39). Compounds structures were assigned mainly by 1D and 2D NMR experiments. Compounds 1-39 were assessed as MDR reversers, in human ABCB1-transfected mouse T-lymphoma cells, overexpressing P-glycoprotein (P-gp). The results revealed that O-methylation at C-7, together with the introduction of nitrogen atoms and aromatic moieties at C-4 or C-4', significantly improved the activity, being compounds 27 and 37 the strongest P-gp modulators and much more active than verapamil. In combination assays, synergistic interactions of selected compounds with doxorubicin substantiated the results. While molecular docking suggested that flavanone derivatives act as competitive modulators, molecular dynamics showed that dimethylation promotes binding to a modulator-binding site. Moreover, flavanones may also interact with a vicinal ATP-binding site in both nucleotide-binding domains, hypothesizing an allosteric mode of action.

Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach

Human G protein-coupled receptors (hGPCRs) are the most frequent targets of Food and Drug Administration (FDA)-approved drugs. Structural bioinformatics, along with molecular simulation, can support structure-based drug design targeting hGPCRs. In this context, several years ago, we developed a hybrid molecular mechanics (MM)/coarse-grained (CG) approach to predict ligand poses in low-resolution hGPCR models. The approach was based on the GROMOS96 43A1 and PRODRG united-atom force fields for the MM part. Here, we present a new MM/CG implementation using, instead, the Amber 14SB and GAFF all-atom potentials for proteins and ligands, respectively. The new implementation outperforms the previous one, as shown by a variety of applications on models of hGPCR/ligand complexes at different resolutions, and it is also more user-friendly. Thus, it emerges as a useful tool to predict poses in low-resolution models and provides insights into ligand binding similarly to all-atom molecular dynamics, albeit at a lower computational cost.

A computational approach to validate novel drug targets of gentianine from Swertiya chirayita in Plasmodium falciparum

Gentianine is one of the compounds found in the plant Swertiya chirayita that is known for its antimalarial activity. However, its exact molecular mechanism of action is yet to be understood. In our present study, we applied several computational approaches to filter out and determine possible targets of gentianine in Plasmodium falciparum 3D7. Protein-protein networks formed the basis of one of our strategies along with orthologous protein analysis to establish essentiality. Out of 6 essential proteins from unique pathways, haloacid dehalogenase like-hydrolase (PfHAD1), phosphoenolpyruvate carboxykinase (PfPEPCK) and fumarate hydratase (PfFH) were screened as drug targets through this approach. Through our other strategy we established the predicted IC50 (PIC50) value of gentianine with a set of molecular descriptors from 123 Pathogen Box anti-malarial compounds. Afterwards through 2D structural similarity, L-lactate dehydrogenase (PfLDH) was established as another possible target. In our work, we performed in silico docking and analysed the binding of gentianine to the proteins. All of the proteins were reported with favourable binding results and were considered for complex molecular dynamics simulation approach. Our research clears up the molecular mechanism of antimalarial activity of gentianine to some extent paving way for experimental validation of the same in future.

Increased APOE glycosylation plays a key role in the atherogenicity of L5 low-density lipoprotein

Low-density lipoprotein (LDL) is heterogeneous, composed of particles with variable atherogenicity. Electronegative L5 LDL exhibits atherogenic properties in vitro and in vivo, and its levels are elevated in patients with increased cardiovascular risk. Apolipoprotein E (APOE) content is increased in L5, but what role APOE plays in L5 function remains unclear. Here, we characterized the contributions of APOE posttranslational modification to L5's atherogenicity. Using two-dimensional electrophoresis and liquid chromatography-mass spectrometry, we studied APOE's posttranslational modification in L5 from human plasma. APOE structures with various glycan residues were predicted. Molecular docking and molecular dynamics simulation were performed to examine the functional changes of APOE resulting from glycosylation. We also examined the effects of L5 deglycosylation on endothelial cell apoptosis. The glycan sequence N-acetylgalactosamine, galactose, and sialic acid was consistently expressed on serine 94, threonine 194, and threonine 289 of APOE in L5 and was predicted to contribute to L5's negative surface charge and hydrophilicity. The electrostatic force between the negatively charged sialic acid-containing glycan residue of APOE and positively charged amino acids at the receptor-binding area suggested that glycosylation interferes with APOE's attraction to receptors, lipid-binding ability, and lipid transportation and metabolism functions. Importantly, L5 containing glycosylated APOE induced apoptosis in cultured endothelial cells through lectin-like oxidized LDL receptor-1 (LOX-1) signaling, and glycosylation removal from L5 attenuated L5-induced apoptosis. APOE glycosylation may contribute to the atherogenicity of L5 and be a useful biomarker for rapidly quantifying L5.

Antibiotic Uptake Across Gram-Negative Outer Membranes: Better Predictions Towards Better Antibiotics

Crossing the Gram-negative bacterial membrane poses a major barrier to antibiotic development, as many small molecules that can biochemically inhibit key bacterial processes are rendered microbiologically ineffective by their poor cellular uptake. The outer membrane is the major permeability barrier for many drug-like molecules, and the chemical properties that enable efficient uptake into mammalian cells fail to predict bacterial uptake. We have developed a computational method for accurate prospective prediction of outer membrane uptake of drug-like molecules, which we combine with a new medium-throughput experimental assay of outer membrane vesicle swelling. Parallel molecular dynamics simulations of compound uptake through Escherichia coli (E. coli) OmpF are used to successfully and quantitatively predict experimental permeabilities measured via either outer membrane swelling or prior liposome-swelling measurements. These simulations are analyzed using an inhomogeneous solubility-diffusion model to yield predictions of permeability. For most polar molecules we test, outer membrane permeability also correlates well with whole-cell uptake. The ability to accurately predict and measure outer membrane uptake of a wide variety of small molecules will enable simpler determination of which molecular scaffolds and which derivatives are most promising prior to extensive chemical synthesis. It will also assist in formulating a more systematic understanding of the chemical determinants of outer membrane permeability.

ContraDRG: Automatic Partial Charge Prediction by Machine Learning

In recent years, machine learning techniques have been widely used in biomedical research to predict unseen data based on models trained on experimentally derived data. In the current study, we used machine learning algorithms to emulate computationally complex predictions in a reverse engineering-like manner and developed ContraDRG, a software that can be used to predict partial charges for small molecules based on PRODRG and Automated Topology Builder (ATB) predictions. Both tools generate molecular topology files, including the partial atomic charge, by using different procedures. We show that ContraDRG can accurately predict partial charges in a fraction of the time, because it exploits existing complex models with intensive calculations by using machine learning techniques and thus can also be applied for screening projects with large amounts of molecules. We provide ContraDRG as a web server, which can be used to automatically assign partial charges to incoming user-specified molecules by using our machine learning models. In this study, we compared ContraDRG with PRODRG and ATB in regard of predictivity by statistical methods. ContraDRG allows predicting ATB-derived partial charges with an R2 value up to 0.980 and for PRODRG up to 1.00. While ATB requires hours or days for the quantum mechanical accurate calculation and refinements, ContraDRG does its approximation within seconds.

In Silico Characterization of the Binding Modes of Surfactants with Bovine Serum Albumin

The binding interactions of the surfactants: anionic sodium dodecyl sulphate (SDS), cationic cetyltrimethylammonium bromide (CTAB), non-ionic octyl glucoside (OG), and zwitterionic 3-[Hexadecyl(dimethyl)ammonio]-1-propanesulfonate (HPS), with bovine serum albumin (BSA) were investigated by computer simulation. The results disclosed that the surfactants bound stably between hydrophobic subdomain IIA and IIIA where tryptophan-213 residue, an important intrinsic fluorophore in BSA is housed. The interactions of the surfactants with the BSA were electrostatic and hydrophobic interactions. The head-groups of SDS, HPS and OG formed hydrogen bonds with the BSA, while that of CTAB was shielded from intermolecular hydrogen-bonding due to intervening methyl groups. Subsequently, molecular dynamics (MD) simulation of the protein-surfactant complexes revealed that hydrogen bonds formed by OG were stronger than those of SDS and HPS. However, the decomposed force-field energies showed that OG had the least interaction energy with the BSA. In addition to MD simulation, it was found by density functional theory (DFT) that the differences in the coulomb interaction energies can be attributed to charge distribution in the surfactants. Overall, free energies calculated by linear interaction energy (LIE) proved that the binding of each surfactant was dominated by differences between van der Waals interactions in bound and free states.