Three-state dynamics of zinc(II) complexes yielding significant antidiabetic targets.

Protein Tyrosine Phosphatase 1B (PTP1B), being negative regulator of insulin signaling pathways is considered as potential medicinal target. Selective and targeted inhibitors for PTP1B can impact the therapeutic options available to cure chronic illness such as diabetes. Significant research evidence including computational studies on the role of Zn2+ in binding and inhibiting the catalytic pocket have been reported along with experimental exploration of zinc(II) complexes as potent inhibitors of the enzyme. The current study has employed advanced computational methods to explore the binding and conformational orientation of zinc(II) complexes in the active site of apoenzyme, phosphoenzyme, and TSA 2 of PTP1B. Metal ion modeling was performed for zinc metal center (Zn-OOOO) utilizing a Python based Metal Center Parameter Builder (MCPB.py). The findings of the study suggest that zinc(II) complex binds to structurally and functionally important residues in open and closed conformation as well as in the phosphorylated state of the enzyme. It was observed that when the catalytic cysteine is phosphorylated in a closed conformation, the zinc(II) complex forms significant interactions with PHE182, VAL184, GLY183, and PRO180 while pushing away Q-loop GLN262 which is crucial for the hydrolysis of phosphoenzyme. Subsequently, the reported inhibitor has also demonstrated its potential to function as allosteric modulator of the enzyme occupying catalytic WPD loop residues. The study uncovers putative binding sites of zinc-containing drugs and gives insight into the size and design of such compounds which keeps them accessible and anchored in the vicinity of active site residues. Reported inhibitor offers enhanced selectivity and inhibition in all three states of the enzyme in contrast to zinc ions which can only impede enzyme in the phosphorylated state. In addition to this, investigation of ASP265→GLU265 mutation reveals the role of GLU265 in affecting the flexibility of WPD loop residues highlighting it as loss-of-function mutation. Our results hints towards a metallodrug approach that builds on the research evidence of inhibition effects of Zn2+ in the binding pocket of PTP1B. The findings presented are noteworthy, not just due to their significant relevance for clinical application, but also for the design and synthesis of novel zinc(II) complexes.

Comparative genomics and evolutionary analysis of plant CNGCs.

Comparative genomics and computational biology offer powerful research tools for studying evolutionary mechanisms of organisms, and the identification and characterization of conserved/distant genes and gene families. The plant CNGC gene family encodes evolutionary conserved ion channel proteins involved in important signaling pathways and biological functions. The fundamental ideas and standard procedures for genome-wide identification and evolutionary analysis of plant cyclic nucleotide-gated ion channels employing various software, tools, and online servers have been discussed. In particular, this developed method focused on practical procedures involving the comparative analysis of paralogs and orthologs of CNGC genes in different plant species at different levels including phylogenetic analysis, nomenclature and classification, gene structure, molecular protein evolution, and duplication events as mechanisms of gene family expansion and synteny.

Combined deep learning and molecular docking simulations approach identifies potentially effective FDA approved drugs for repurposing against SARS-CoV-2.

The ongoing pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health. Drug repurposing is a time-efficient approach to finding effective drugs against SARS-CoV-2 in this emergency. Here, we present a robust experimental design combining deep learning with molecular docking experiments to identify the most promising candidates from the list of FDA-approved drugs that can be repurposed to treat COVID-19. We have employed a deep learning-based Drug Target Interaction (DTI) model, called DeepDTA, with few improvements to predict drug-protein binding affinities, represented as KIBA scores, for 2440 FDA-approved and 8168 investigational drugs against 24 SARS-CoV-2 viral proteins. FDA-approved drugs with the highest KIBA scores were selected for molecular docking simulations. We ran around 50,000 docking simulations for 168 selected drugs against 285 total predicted and/or experimentally proven active sites of all 24 SARS-CoV-2 viral proteins. A list of 49 most promising FDA-approved drugs with the best consensus KIBA scores and binding affinity values against selected SARS-CoV-2 viral proteins was generated. Most importantly, 16 drugs including anidulafungin, velpatasvir, glecaprevir, rifapentine, flavin adenine dinucleotide (FAD), terlipressin, and selinexor demonstrated the highest predicted inhibitory potential against key SARS-CoV-2 viral proteins. We further measured the inhibitory activity of 5 compounds (rifapentine, velpatasvir, glecaprevir, anidulafungin, and FAD disodium) on SARS-CoV-2 PLpro using Ubiquitin-Rhodamine 110 Gly fluorescent intensity assay. The highest inhibition of PLpro activity was seen with rifapentine (IC50: 15.18 µM) and FAD disodium (IC50: 12.39 µM), the drugs with high predicted KIBA scores and binding affinities.

Structural probing of HapR to identify potent phytochemicals to control Vibrio cholera through integrated computational approaches.

Cholera is a severe small intestine bacterial disease caused by consumption of water and food contaminated with Vibrio cholera. The disease causes watery diarrhea leading to severe dehydration and even death if left untreated. In the past few decades, V. cholerae has emerged as multidrug-resistant enteric pathogen due to its rapid ability to adapt in detrimental environmental conditions. This research study aimed to design inhibitors of a master virulence gene expression regulator, HapR. HapR is critical in regulating the expression of several set of V. cholera virulence genes, quorum-sensing circuits and biofilm formation. A blind docking strategy was employed to infer the natural binding tendency of diverse phytochemicals extracted from medicinal plants by exposing the whole HapR structure to the screening library. Scoring function criteria was applied to prioritize molecules with strong binding affinity (binding energy < -11 kcal/mol) and as such two compounds: Strychnogucine A and Galluflavanone were filtered. Both the compounds were found favourably binding to the conserved dimerization interface of HapR. One rare binding conformation of Strychnogucine A was noticed docked at the elongated cavity formed by α1, α4 and α6 (binding energy of -12.5 kcal/mol). The binding stability of both top leads at dimer interface and elongated cavity was further estimated using long run of molecular dynamics simulations, followed by MMGB/PBSA binding free energy calculations to define the dominance of different binding energies. In a nutshell, this study presents computational evidence on antibacterial potential of phytochemicals capable of directly targeting bacterial virulence and highlight their great capacity to be utilized in the future experimental studies to stop the evolution of antibiotic resistance evolution.

Molecular screening of glycyrrhizin-based inhibitors against ACE2 host receptor of SARS-CoV-2.

The interaction between SARS-CoV-2 Spike protein and angiotensin-converting enzyme 2 (ACE2) is essential to viral attachment and the subsequent fusion process. Interfering with this event represents an attractive avenue for the development of therapeutics and vaccine development. Here, a hybrid approach of ligand- and structure-based virtual screening techniques were employed to disclose similar analogues of a reported antiviral phytochemical, glycyrrhizin, targeting the blockade of ACE2 interaction with the SARS-CoV-2 Spike. A ligand-based similarity search using a stringent cut-off revealed 40 FDA-approved compounds in DrugBank. These filtered hits were screened against ACE2 using a blind docking approach to determine the natural binding tendency of the compounds with ACE2. Three compounds, deslanoside, digitoxin, and digoxin, were reported to show strong binding with ACE2. These compounds bind at the H1-H2 binding pocket, in a manner similar to that of glycyrrhizin which was used as a control. To achieve consistency in the docking results, docking calculations were performed via two sets of docking software that predicted binding energy as ACE2-Deslanoside (AutoDock, -10.3 kcal/mol and DockThor, -9.53 kcal/mol), ACE2-Digitoxin (AutoDock, -10.6 kcal/mol and DockThor, -8.84 kcal/mol), and ACE2-Digoxin (AutoDock, -10.6 kcal/mol and DockThor, -8.81 kcal/mol). The docking results were validated by running molecular simulations in aqueous solution that demonstrated the stability of ACE2 with no major conformational changes in the ligand original binding mode (~ 2 Å average RMSD). Binding interactions remained quite stable with an increased potential for getting stronger as the simulation proceeded. MMGB/PBSA binding free energies were also estimated and these supported the high stability of the complexes compared to the control (~ -50 kcal/mol net MMGB/PBSA binding energy versus ~ -30 kcal/mol). Collectively, the data demonstrated that the compounds shortlisted in this study might be subjected to experimental evaluation to uncover their real blockade capacity of SARS-CoV-2 host ACE2 receptor.

SARS-CoV-2: An Update on Genomics, Risk Assessment, Potential Therapeutics and Vaccine Development.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a great threat to public health, being a causative pathogen of a deadly coronavirus disease (COVID-19). It has spread to more than 200 countries and infected millions of individuals globally. Although SARS-CoV-2 has structural/genomic similarities with the previously reported SARS-CoV and MERS-CoV, the specific mutations in its genome make it a novel virus. Available therapeutic strategies failed to control this virus. Despite strict standard operating procedures (SOPs), SARS-CoV-2 has spread globally and it is mutating gradually as well. Diligent efforts, special care, and awareness are needed to reduce transmission among susceptible masses particularly elder people, children, and health care workers. In this review, we highlighted the basic genome organization and structure of SARS-CoV-2. Its transmission dynamics, symptoms, and associated risk factors are discussed. This review also presents the latest mutations identified in its genome, the potential therapeutic options being used, and a brief explanation of vaccine development efforts against COVID-19. The effort will not only help readers to understand the deadly SARS-CoV-2 virus but also provide updated information to researchers for their research work.

Toward novel inhibitors against KdsB: a highly specific and selective broad-spectrum bacterial enzyme.

KdsB (3-deoxy-manno-octulosonate cytidylyltransferase) is a highly specific and selective bacterial enzyme that catalyzes KDO (3-Deoxy-D-mano-oct-2-ulosonic acid) activation in KDO biosynthesis pathway. Failure in KDO biosynthesis causes accumulation of lipid A in the bacterial outer membrane that leads to cell growth arrest. This study reports a combinatorial approach comprising virtual screening of natural drugs library, molecular docking, computational pharmacokinetics, molecular dynamics simulation, and binding free energy calculations for the identification of potent lead compounds against the said enzyme. Virtual screening demonstrated 1460 druglike compounds in a total of 4800, while molecular docking illustrated Ser13, Arg14, and Asp236 as the anchor amino acids for recognizing and binding the inhibitors. Functional details of the enzyme in complex with the best characterized compound-226 were explored through two hundred nanoseconds of MD simulation. The ligand after initial adjustments jumps into the active cavity, followed by the deep cavity, and ultimately backward rotating movement toward the initial docked site of the pocket. During the entire simulation period, Asp236 remained in contact with the ligand and can be considered as a major catalytic residue of the enzyme. Radial distribution function confirmed that toward the end of the simulation, strengthening of ligand-receptor occurred with ligand and enzyme active residues in close proximity. Binding free energy calculations via MM(PB/GB)SA and Waterswap reaction coordinates, demonstrated the high affinity of the compound for enzyme active site residues. These findings can provide new avenues for designing potent compounds against notorious bacterial pathogens.

Role of Zinc and Magnesium Ions in the Modulation of Phosphoryl Transfer in Protein Tyrosine Phosphatase 1B.

While the majority of phosphatases are metalloenzymes, the prevailing model for the reactions catalyzed by protein tyrosine phosphatases does not involve any metal ion, yet both metal cations and oxoanions affect their enzymatic activity. Mg2+ and Zn2+ activate and inhibit, respectively, protein tyrosine phosphatase 1B (PTP1B). Molecular dynamics simulations, metadynamics, and quantum chemical calculations in combination with experimental investigations demonstrate that Mg2+ and Zn2+ compete for the same binding site in the active site only in the closed conformation of the enzyme in its phosphorylated state. The two cations have different effects on the arrangements and activities of water molecules that are necessary for the hydrolysis of the phosphocysteine intermediate in the second catalytic step of the reaction. Remarkable differences between the established structural enzymology of PTP1B investigated ex vivo and the function of PTP1B in vivo become evident. Different reaction pathways are viable when the presence of metal ions and their cellular concentrations are considered. The findings suggest that the substrate delivers the inhibitory Zn2+ ion to the active site. The inhibition and activation can be ascribed to the different coordination chemistries of Zn2+ and Mg2+ ions and the orientation of the metal-coordinated water molecules. Metallochemistry adds an additional dimension to the regulation of PTP1B and presumably other members of this enzyme family.

Molecular dynamics simulation studies of novel ß-lactamase inhibitor.

New Delhi Metallo-ß-Lactamase-1 (NDM-1) has drawn great attention due to its diverse antibiotic resistant activity. It can hydrolyze almost all clinically available ß-lactam antibiotics. To inhibit the activity of NDM-1 a new strategy is proposed using computational methods. Molecular dynamics (MD) simulations are used to analyze the molecular interactions between selected inhibitor candidates and NDM-1 structure. The enzyme-ligand complex is subject to binding free energy calculations using MM(PB/GB)SA methods. The role of each residue of the active site contributing in ligand binding affinity is explored using energy decomposition analysis. Furthermore, a hydrogen bonding network between ligand and enzyme active site is observed and key residues are identified ensuring that the ligand stays inside the active site and maintains its movement towards the active site pocket. A production run of 150ns is carried out and results are analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) to explain the stability of enzyme ligand complex. Important active site residue e.g. PHE70, VAL73, TRP93, HIS122, GLN123, ASP124, HIS189, LYS216, CYS208, LYS211, ALA215, HIS250, and SER251 were observed to be involved in ligand attachemet inside the active site pocket, hence depicting its inhibitor potential. Hydrogen bonds involved in structural stability are analyzed through radial distribution function (RDF) and contribution of important residues involved in ligand movement is explained using a novel analytical tool, axial frequency distribution (AFD) to observe the role of important hydrogen bonding partners between ligand atoms and active site residues.

Binding pattern analysis and structural insight into the inhibition mechanism of Sterol 24-C methyltransferase by docking and molecular dynamics approach.

Sterol 24-C methyltransferase (SMT) plays a major role during the production of steroids, especially in the biosynthesis of ergosterol, which is the major membrane sterol in leishmania parasite, and the etiological basis of leishmaniasis. Mechanism-based inactivators bind irreversibly to SMT and interfere with its activity to provide leads for the design of antileishmanial inhibitors. In this study, computational methods are used for studying enzyme-inhibitor interactions. fifty-seven mechanism-based inactivators are docked using 3 docking/scoring approaches (FRED, GoldScore, and ChemScore). A consensus is generated from the results of different scoring functions which are also validated with already reported experimental values. The most active compound thus obtained is subjected to molecular dynamics simulation of length 20 ns. Stability of simulation is analyzed through root-mean-square deviation, beta factor (B-factor), and radius of gyration (Rg). Hydrogen bonds and their involvement in the structural stability of the enzyme are evaluated through radial distribution function. Newly developed application of axial frequency distribution that determines three-particle correlation on frequency distributions before and after simulation has provided a clear evidence for the movement of the inhibitor into active pocket of the enzyme. Results yielded strong interaction between enzyme and the inhibitor throughout the simulation. Binding of the inhibitor with enzyme has stabilized the enzyme structure; thus, the inhibitor has the potential to become a lead compound.

Comparative modeling and virtual screening for the identification of novel inhibitors for myo-inositol-1-phosphate synthase.

Myo-inositol-1-phosphate (MIP) synthase is a key enzyme in the myo-inositol biosynthesis pathway. Disruption of the inositol signaling pathway is associated with bipolar disorders. Previous work suggested that MIP synthase could be an attractive target for the development of anti-bipolar drugs. Inhibition of this enzyme could possibly help in reducing the risk of a disease in patients. With this objective, three dimensional structure of the protein was modeled followed by the active site prediction. For the first time, computational studies were carried out to obtain structural insights into the interactive behavior of this enzyme with ligands. Virtual screening was carried out using FILTER, ROCS and EON modules of the OpenEye scientific software. Natural products from the ZINC database were used for the screening process. Resulting compounds were docked into active site of the target protein using FRED (Fast Rigid Exhaustive Docking) and GOLD (Genetic Optimization for Ligand Docking) docking programs. The analysis indicated extensive hydrogen bonding network and hydrophobic interactions which play a significant role in ligand binding. Four compounds are shortlisted and their binding assay analysis is underway.

Structure and dynamics studies of sterol 24-C-methyltransferase with mechanism based inactivators for the disruption of ergosterol biosynthesis.

The enzyme sterol 24-C-methyltransferase (SMT) belongs to the family of transferases, specifically to the one-carbon transferring methyltransferases. SMT has been found playing a major role during the production of steroids, especially for the biosynthesis of ergosterol, which is the major membrane sterol in leishmania parasites, causing leishmaniasis. However, SMT and ergosterol are not found in mammals, so, an extensive study has been carried out over the susceptible SMT protein, which is found to be highly conserved among all the Leishmania species and holds a significant anti-leishmanial drug target. To date, there is no computational data available for SMT, due to its highly unexplored profile. In this work, a complete set of structural attributes have been examined through the available computational procedures, along with an attempt to characterize the most capable modeling server available. The exploration ranges from physicochemical characterization, pairwise alignment, secondary structure prediction, to active site detection. With this information, a docking study was carried out to find the compound that best binds into the active site. Moreover, molecular dynamics simulation was conducted to examine the stability of the homology modeled protein and the ligand-enzyme complex. The results indicate that the ligand-enzyme complex is more stable.