Molecular Characterization and Identification of Potential Inhibitors for 'E' Protein of Dengue Virus.

Dengue is an arthropod-borne acute febrile illness caused by Dengue Virus (DENV), a member of Flaviviridae. Severity of the infection ranges from mild self-limiting illness to severe life-threatening hemorrhagic fever (DHF) and dengue shock syndrome (DSS). To date, there is no specific antiviral therapy established to treat the infection. The current study reports the epidemiology of DENV infections and potential inhibitors of DENV 'E' protein. Among the various serotypes, DENV-2 serotype was observed more frequently, followed by DENV-4, DENV-1, and DENV-3. New variants of existing genotypes were observed in DENV-1, 2, and 4 serotypes. Predominantly, the severe form of dengue was attributable to DENV-2 infections, and the incidence was more common in males and pediatric populations. Both the incidence and the disease severity were more common among the residents of non-urban environments. Due to the predominantly self-limiting nature of primary dengue infection and folk medicine practices of non-urban populations, we observed a greater number of secondary dengue cases than primary dengue cases. Hemorrhagic manifestations were more in secondary dengue in particularly in the pediatric group. Through different computational methods, ligands RGBLD1, RGBLD2, RGBLD3, and RGBLD4 are proposed as potential inhibitors in silico against DENV-1, -2, -3, and -4 serotypes.

Novel and potent inhibitors for dihydropteroate synthase of Helicobacter pylori.

An endless drug-resistant strains of Helicobacter pylori and multitudinous drug reactions are obstacles in the treatment of H. pylori infections, thereby ambitious novel proof-of-concept for inhibitor design was practiced in advancement of medication. Dihydropteroate synthase (DHPS) is an alluring target that plays a great role in folate synthesis pathway essential for amino acids biosynthesis was selected for designing novel drugs to prevent infections caused by pathogenic H. pylori. In the present study, a reliable tertiary structure of DHPS in complex with inhibitor 6MB was constructed by Modeler 9v19. DrugBank compounds of DHPS, published inhibitors, and co-crystal ligand (6MB) were docked against DHPS. The best docked compounds were screened against 28.5 million compounds resulted 1186 structural analogs. Virtual screening workflow and quantum polarized ligand dockings of these compounds against DHPS resulted three leads that showed better XP Gscores, ADME properties, and binding-free energies compared to 6MB, DrugBank compounds, and published inhibitors. The proposed leads were also validated by receiver operative characteristic (ROC) curve metrics in the presence of thousand decoys and the best docked existing compounds against DHPS. Long-range molecular dynamics (MD) simulations for 100 ns were executed after post-docking evaluations. Trajectory analysis showed the lead-DHPS docking complex's inter-molecular interactions were stable throughout the entire runtime of MD simulations than 6MB-DHPS complex and Eliglustat-DHPS complex. The study outcomes showed good competitive binding propensity and active-tunneling of leads over the existing inhibitors, thereby these leads could be ideal inhibitors against DHPS to target H. pylori.

Hierarchical-Clustering, Scaffold-Mining Exercises and Dynamics Simulations for Effectual Inhibitors Against Lipid-A Biosynthesis of Helicobacter pylori.

INTRODUCTION: Treatment failures of standard regimens and new strains egression are due to the augmented drug resistance conundrum. These confounding factors now became the drug designers spotlight to implement therapeutics against Helicobacter pylori strains and to safeguard infected victims with devoid of adverse drug reactions. Thereby, to navigate the chemical space for medicine, paramount vital drug target opting considerations should be imperative. The study is therefore aimed to develop potent therapeutic variants against an insightful extrapolative, common target LpxC as a follow-up to previous studies. METHODS: We explored the relationships between existing inhibitors and novel leads at the scaffold level in an appropriate conformational plasticity for lead-optimization campaign. Hierarchical-clustering and shape-based screening against an in-house library of > 21 million compounds resulted in panel of 11,000 compounds. Rigid-receptor docking through virtual screening cascade, quantum-polarized-ligand, induced-fit dockings, post-docking processes and system stability assessments were performed. RESULTS: After docking experiments, an enrichment performance unveiled seven ranked actives better binding efficiencies with Zinc-binding potency than substrate and in-actives (decoy-set) with ROC (1.0) and area under accumulation curve (0.90) metrics. Physics-based membrane permeability accompanied ADME/T predictions and long-range dynamic simulations of 250 ns chemical time have depicted good passive diffusion with no toxicity of leads and sustained consistency of lead1-LpxC in the physiological milieu respectively. CONCLUSIONS: In the study, as these static outcomes obtained from this approach competed with the substrate and existing ligands in binding affinity estimations as well as positively correlated from different aspects of predictions, which could facilitate promiscuous new chemical entities against H. pylori.

Integration of core hopping, quantum-mechanics, molecular mechanics coupled binding-energy estimations and dynamic simulations for fragment-based novel therapeutic scaffolds against Helicobacter pylori strains.

The cascade of complications by Helicobacter pylori including extra-gastric and peptic ulcers to gastric cancer imposes a salient cause of cancer death globally. Adverse drug reactions and burgeoned genetically diverse resistant strains create a big barrier in the treatment, thereby demanding novel proof-of-concept ligands and breakthrough medicines. Hence, as a follow-up of the previous proteomics study against 53 H. pylori strains, KdsB was identified as a vital conserved-target enzyme. Herein, the rational therapeutic-design strategies exploiting for such a hidden cryptic inhibitor were utilized in lead-optimization campaigns through shape screening, the powerful scaffold-hopping, rigid-receptor, quantum-polarized ligand and induced-fit docking techniques coupled with estimating molecular-mechanics energies (ΔGbind) through generalized-Born and surface-area-continuum solvation. Variable-dielectric-Surface-Generalized Born, a novel energy model and physics-based corrections for bond-interactions and ADME/Tox predictions led to yield improved eight therapeutic chemical entities with positive synthesizability scores (0-1). Long-range molecular dynamics (300 ns) simulations revealed stability of leads. Significant computational findings with better competitive binding-strengths than experimental ligands could pave the best choice for selecting better leads as it warrants and filter false-positives based on the consensus of scaffolds interactions and suggesting that designed novel class of KdsB-antagonist molecules may dysfunction the target and stimulate new insights for developing effectual medical interventions.

In silico probing exercises, bioactive-conformational and dynamic simulations strategies for designing and promoting selective therapeutics against Helicobacter pylori strains.

A myriad of drug-resistant strains of Helicobacter pylori and adverse drug-reactions create a big-barrier in the treatment, thereby demanding novel proof-of-concept inhibitors and breakthrough medicines. Hence, an affinity-centric protocol was devised to implement scaffold-design for 3-dehydroquinate dehydratase-II (AroQ) as a follow-up of our study against beaucoup strains. Herein, the study focuses on preferred the attractive-target methodically due to its salient features include conserving, essential and specific for H. pylori, not present in humans and gut-flora. Structural refinement, energy minimization and optimization of the developed best-model were employed with confirming active site residues around substrate. Published AroQ-inhibitors and substrate were utilized to probe an in-house library of molecules. The prepared dataset was allowed to lead-optimization campaign includes rigid-receptor docking through high-throughput virtual, standard-precision, extra-precision screening filters, quantum-polarized-ligand (quantum mechanical and molecular mechanical (QM/MM)) and induced-fit docking experiments. Convergence threshold (0.05) and Truncated Newton Conjugate Gradient (TNCG) were set in ConfGen's algorithm to produce high-quality bioactive conformations by thoroughly narrowing the conformational space accessible to the leads. ADME/Tox predictions and long-range molecular dynamics simulations were executed after post-docking evaluations. The approach provided seven ranked compounds with better scoring functions, bioactive-conformers and pharmacokinetics profiles than published ligands and substrate. Simulations revealed more consistency of lead1-AroQ complex throughout chemical time than controls in the formulated physiological milieu. The study outcomes showing the good competitive binding propensity for active-tunnel over the substrate and previous ligands, thereby these leads could be ideal for proposing as selective cutting-edge inhibitors to target AroQ specific for H. pylori strains.

Epitope-driven common subunit vaccine design against H. pylori strains.

The developing potent vaccine is a pre-emptive strategy to tackle drug abuses and maladies of multidrug-resistant Helicobacter pylori strains. Ongoing vaccine studies are being conducted, however, development is in its infancy as ineffective vaccine targets might be. So, the linear perspective may indicate the need for potent subunit vaccine variants. Here, surface-exposed membrane proteins out of 826 common proteins of 53 H. pylori strains were chosen for analysis, as a follow-up to previous studies; these proteins are responsible for antigenicity to elicit the immune response. Antigenic determinant regions on prognostic targets were evaluated in the successive peptide screening using experimental T-cell epitope positive control and optimized with eminent immunoinformatics algorithms. In the milieu of docking, an ensemble of 2200 multiple conformers of complexes of modeled peptide and human leukocyte antigen- antigenD Related Beta-chain (HLA-DRB) was generated. Prioritized physics-based Molecular Mechanics-Generalized Born Surface Area approach coupled with bond length monitoring paved the improvement of prediction accuracy with binding potency estimations. ΔGbind free energy, interaction patterns, enrichment factor contributions and root-mean-square deviation predictions evidenced the existence of better binding affinities of four novel peptides hits with predominant allotype HLA-DR alleles than co-crystal controls. Moreover, conformational plasticity and stability assessments of the better ranked complex epitope-2 (86-FRRNPNINV-94) - HLA-DRB5*0101 formulated in dynamic simulations of 10,416 trajectories depicted stable interaction profile that correlated with docking endpoints. Thus, the proposed novel vaccine cocktails of the study would be ideal candidates and provide new insights for T-cell driven subunit vaccine design against H. pylori strains Communicated by Ramaswamy H. Sarma.

E-pharmacophore-based virtual screening to identify GSK-3ß inhibitors.

Glycogen synthase kinase-3ß (GSK-3ß) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3ß increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer's disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3ß to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3ß. The 50 ns MD simulations run confirmed the stable nature of GSK-3ß-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3ß.

In Silico Approach to Support that p-Nitrophenol Monooxygenase from Arthrobacter sp. Strain JS443 Catalyzes the Initial Two Sequential Monooxygenations.

p-Nitrophenol (PNP), used primarily for manufacturing pesticides and dyes, has been recognized as a priority environmental pollutant. It is therefore important to reduce the input of this toxicant into the environment and to establish approaches for its removal from the contaminated sites. PNP monooxygenase, a novel enzyme from Gram-positive bacteria like Arthrobacter sp. and Bacillus sp., that comprises two components, a flavoprotein reductase and an oxygenase, catalyzes the initial two sequential monooxygenations to convert PNP to trihydroxybenzene. Accurate and reliable prediction of this enzyme-substrate interactions and binding affinity are of vital importance in understanding these catalytic mechanisms of the two sequential reactions. As crystal structure of the enzyme has not yet been published, we built a homology model for PNP monooxygenase using crystallized chlorophenol 4-monooxygenase from Burkholderia cepacia AC1100 (3HWC) as the template. The model was assessed for its reliability using PROCHECK, ERRAT and ProSA. Molecular docking of the physiological substrates, PNP and 4-nitrocatechol (4-NC), was carried out using Glide v5.7 implemented in Maestro v9.2, and the binding energies were calculated to substantiate the prediction. Docking complexes formed by molecular level interactions of PNP monooxygenase-PNP/4-NC without or with the cofactors, FAD and NADH, showed good correlation with the established experimental evidence that the two-component PNP monooxygenase catalyzes both the hydroxylation of PNP and the oxidative release of nitrite from 4-NC in B. sphaericus JS905. Furthermore, molecular dynamics simulations performed for docking complexes using Desmond v3.0 showed stable nature of the interactions as well.

In silico approach to support that p-nitrophenol monooxygenase from Arthrobacter sp. strain JS443 catalyzes the initial two sequential monooxygenations.

p-Nitrophenol (PNP), used primarily for manufacturing pesticides and dyes, has been recognized as a priority environmental pollutant. It is therefore important to reduce the input of this toxicant into the environment and to establish approaches for its removal from the contaminated sites. PNP monooxygenase, a novel enzyme from Gram-positive bacteria like Arthrobacter sp. and Bacillus sp., that comprises two components, a flavoprotein reductase and an oxygenase, catalyzes the initial two sequential monooxygenations to convert PNP to trihydroxybenzene. Accurate and reliable prediction of this enzyme-substrate interactions and binding affinity are of vital importance in understanding these catalytic mechanisms of the two sequential reactions. As crystal structure of the enzyme has not yet been published, we built a homology model for PNP monooxygenase using crystallized chlorophenol 4-monooxygenase from Burkholderia cepacia AC1100 (3HWC) as the template. The model was assessed for its reliability using PROCHECK, ERRAT, WHATCHECK and ProSA. Molecular docking of the physiological substrates, PNP and 4-nitrocatechol (4-NC), was carried out using Glide v5.7 implemented in Maestro v9.2, and the binding energies were calculated to substantiate the prediction. Docking complexes formed by molecular level interactions of PNP monooxygenase-PNP/4-NC without or with the cofactors, FAD and NADH, showed good correlation with the established experimental evidence that the two-component PNP monooxygenase catalyzes both the hydroxylation of PNP and the oxidative release of nitrite from 4-NC in B. sphaericus JS905. Furthermore, molecular dynamics simulations performed for docking complexes using Desmond v3.0 showed stable nature of the interactions as well.