Exploring allosteric hits of the NS2B-NS3 protease of DENV2 by structure-guided screening.

Despite the rising number of cases and increasing global disease burden, there is no definitive therapy against dengue to date, which necessitates the urgent discovery of inhibitors against the virus. The NS2B-NS3 serine protease of the dengue virus (DENV) catalyses polyprotein cleavage and is a potential target for drug discovery. The protease possesses a potentially druggable allosteric site, and the binding of inhibitors to this site locks the protease in an inactive conformation. The allosteric site is a potential druggable target for drug discovery against flaviviruses. This study aimed to identify serotype-specific hits against the allosteric site in the NS2B-NS3 protease of DENV serotype 2 (DENV2) from the Enamine, Selleck, and ChemDiv antiviral libraries. The prepared libraries were screened using a redocking and rescoring-based strategy with Glide SP and Glide XP, and the hitlist was initially screened by comparing their docking scores with that of reported allosteric inhibitors, myricetin and curcumin. The hitlist was subsequently screened by comparing the molecular mechanics with generalised Born and surface area solvation (MM-GBSA) energy with that of the standards. Ten hits were finally selected by virtual screening, and the stability of the hit-receptor complexes was determined with 100 ns molecular dynamics (MD) simulations in an explicit solvent. Trajectory visualisation and analyses of the RMSD and RMSF values revealed that three hits, including two catechins, remained stably bound to the allosteric binding site throughout the production run. Hit-receptor interaction analyses revealed that the hits formed highly stable interactions with Glu 88, Trp 89, Leu 149, Ile 165, and Asn 167, and MM-GBSA energy analysis revealed that the three hits had high binding affinity to the allosteric site. The findings obtained herein can aid in identifying novel serotype-specific inhibitors of DENV protease in future.

Search for potentially biased epidermal growth factor receptor (EGFR) inhibitors through pharmacophore modelling, molecular docking, and molecular dynamics (MD) simulation approaches.

Epidermal growth factor receptor (EGFR), being one of the most crucial receptor in cancer therapy, has been selected as a potential target for the present study. Ligand-based pharmacophore model (n = 30, R2=0.93 with root mean square deviation = 1.14, ΔCost = 144.27 and configuration cost = 21) was developed and validated with Fischer's randomisation (at 95% confidence), test set (n = 225, R2 pred = 0.81), external data set (n = 13, R2 pred = 0.95) and decoy set (n = 70), further the model has been used to search for novel EGFR inhibitors. The validated model was used for virtual screening of zinc database. A pool of 115,948 candidate molecules was screened through the model. Subsequently, molecules having predicted IC50<0.2 µM were selected for screening through drug-like properties filter. Based on pharmacokinetic profile (ADMET study), Lipinski's rule of five and Veber's rule, 62 molecules were shortlisted for molecular docking. Using consensus docking, five hit molecules were selected, which were further considered for molecular dynamics simulation. Additionally MM-GBSA analysis was carried which showed that affinity of hits towards the receptor of three compound mainly ZINC305, ZINC131796 and ZINC131785 were similar to the standard vanedtinib. The simulation, performed for 100 ns, revealed that two hit molecules, namely ZINC305 and ZINC131785, showing potential interactions at the ligand-binding domain of EGFR protein with good ligand-protein stability. Communicated by Ramaswamy H. Sarma.

Drug repurposing against the RNA-dependent RNA polymerase domain of dengue serotype 3 by virtual screening and molecular dynamics simulations.

Dengue is an arboviral disease caused by the dengue flavivirus. The NS5 protein of flaviviruses is a potential therapeutic target, and comprises an RNA-dependent RNA polymerase (RDRP) domain that catalyses viral replication. The aim of this study was to repurpose FDA-approved drugs against the RDRP domain of dengue virus serotype 3 (DENV3) using structure-based virtual screening and molecular dynamics (MD) simulations. The FDA-approved drugs were screened against the RDRP domain of DENV3 using a two-step docking-based screening approach with Glide SP and Glide XP. For comparison, four reported DENV3 RDRP inhibitors were docked as standards. The hitlist was screened based on the docking score of the inhibitor with the lowest docking score (PubChem ID: 118797902; reported IC50 value: 0.34 µM). Five hits with docking scores and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) energy lower than those of 118797902 were selected. The stability of the hit-receptor complexes was investigated using 100 ns MD simulations in an explicit solvent. The results of MD simulations demonstrated that polydatin and betiatide remained stably bound to the receptor, and formed stable interactions with the RDRP domain of DENV3. The hit-receptor interactions were comparable to those of 118797902. The average Prime MM-GBSA energy of polydatin and betiatide was lower than that of 118797902 during simulation, indicating that their binding affinity to DENV3 RDRP was higher than that of the standard. The results of this study may aid in the development of serotype-selective drugs against dengue in the future.Communicated by Ramaswamy H. Sarma.

Ab initio modelling of an essential mammalian protein: Transcription Termination Factor 1 (TTF1).

Transcription Termination Factor 1 (TTF1) is an essential mammalian protein that regulates transcription, replication fork arrest, DNA damage repair, chromatin remodelling etc. TTF1 interacts with numerous cellular proteins to regulate various cellular phenomena which play a crucial role in maintaining normal cellular physiology, and dysregulation of this protein has been reported to induce oncogenic transformation of the cells. However, despite its key role in many cellular processes, the complete structure of human TTF1 has not been elucidated to date, neither experimentally nor computationally. Therefore, understanding the structure of human TTF1 is crucial for studying its functions and interactions with other cellular factors. The aim of this study was to construct the complete structure of human TTF1 protein, using molecular modelling approaches. Owing to the lack of suitable homologues in the Protein Data Bank (PDB), the complete structure of human TTF1 was constructed by ab initio modelling. The structural stability was determined with molecular dynamics (MD) simulations in explicit solvent, and trajectory analyses. The frequently occurring conformation of human TTF1 was selected by trajectory clustering, and the central residues of this conformation were determined by centrality analyses of the Residue Interaction Network (RIN) of TTF1. Two residue clusters, one in the oligomerization domain and other in the C-terminal domain, were found to be central to the structural stability of human TTF1. To the best of our knowledge, this study is the first to report the complete structure of this essential mammalian protein, and the results obtained herein will provide structural insights for future research including that in cancer biology and related studies.Communicated by Ramaswamy H. Sarma.

Metagenomic study focusing on antibiotic resistance genes from the sediments of River Yamuna.

Antibiotic resistance is one of the major health concerns of the present century. The direct discharge of urban sewage, hospital effluents, and pharmaceutical wastes increases the concentration of antibiotics in riverine ecosystems. This provides selection pressure for the development of novel antibiotic-resistant strains. In this study, metagenomics approach was employed a for constructing a comprehensive profile of the Antibiotic Resistance Genes (ARGs) identified in the sediments of the Yamuna River. A total of 139 ARGs were identified from 39 microbial species. Abundance analysis revealed that, aminoglycoside, beta-lactam, macrolide, and tetracycline resistance genes were highly abundant in the sediment samples obtained from the Yamuna River. The evolutionary relationships among the ARGs were studied by phylogenetic analyses, which revealed that, the identified resistome comprised eight clusters. Network analysis was performed for investigating the broad-spectrum profiles of the ARGs and their enrichment in different biological functions and pathways. Protein-protein interaction (PPI) analyses revealed that, 76, 36, 18, and 5 Gene Ontology (GO)-terms were significantly enriched in Biological process, Molecular Function, Cellular Component, and KEGG Pathways analysis, respectively. The present study elucidates the ecology of microbial antibiotic resistance in the riverine ecosystem of the Yamuna River and provides novel insights into the environmental hotspots that are amenable to the emergence of ARGs in the contaminated riverine hydrosphere.

Employing virtual screening and molecular dynamics simulations for identifying hits against the active cholera toxin.

Cholera is a major global threat, affecting millions each year. The ADP ribosyltransferase activity of the active cholera toxin catalyses the massive loss of water and electrolytes during cholera infections. The active toxin heterodimer comprises the A1 subunit from Vibrio cholerae and ARF (ADP Ribosylation Factor) from the human host. Although the active toxin is a potential target for drug discovery against cholera, it has been scarcely targeted to date. The A1-ARF interface contains a potential druggable site for small molecule inhibitors. By combining a sequential docking and scoring strategy with molecular dynamics (MD) simulations, this study identified hits against the protein-protein interface (PPI) of the active cholera toxin from an in-house library of 9,175 ADMET-screened alkaloids. The docking algorithms and scoring functions of Glide SP, Glide XP, and AutoDock were employed for initial library screening. Three alkaloids were initially selected by docking-based virtual screening. The stability of the hit-toxin complexes was validated by MD simulations. Two of the three hits, namely, A6225 (7-formyldehydrothalicsimidine) and A16503 (1,2,7,8-tetrahydroxy dibenz[cd,f]indol-4(5H)-one), formed stable complexes with the toxin. Analyses of the hydrogen bond occupancies revealed that the hits formed stable hydrogen bonds with the toxin PPI. The hits identified herein can serve as reference compounds for drug discovery against cholera in the future.

Prediction and characterisation of lantibiotic structures with molecular modelling and molecular dynamics simulations.

Lantibiotics are lanthionine-containing bactericidal peptides produced by gram-positive bacteria as a defence mechanism against other bacterial species. Lantipeptides disrupt the integrity of target cells by forming pores in their cell membranes, or by preventing cell wall biosynthesis, which subsequently results in cell death. Lantibiotics are of immense importance to the food preservation and pharmaceutical industries. The rise in multidrug resistance demands the discovery of novel antimicrobials, and several authors advocate that lantibiotics hold the future of antimicrobial drug discovery. Owing to their amenability to structural modifications, novel lantibiotics with higher efficacy and antimicrobial activity can be constructed by bioengineering and nanoengineering strategies, and is opined to have immense therapeutic success in combating the rise in multidrug resistance. Understanding the structure and dynamics of lantibiotics is therefore crucial for the development of novel lantipeptides, and this study aimed to study the structural properties and dynamics of 37 lantibiotics using computational strategies. The structures of these 37 lantibiotics were constructed from homology, and their structural stability and compactness were analysed by molecular dynamics simulations. The phylogenetic relationships, physicochemical properties, disordered regions, pockets, intramolecular bonds and interactions, and structural diversity of the 37 lantipeptides were studied. The structures of the 37 lantipeptides constructed herein remained stable throughout simulation. The study revealed that the structural diversity of lantibiotics is not significantly correlated to sequence diversity, and this property could be exploited for designing novel lantipeptides with higher efficacy.

Targeting the dengue ß-OG with serotype-specific alkaloid virtual leads.

The dengue envelope ß-OG pocket is a crucial hinge for mediating virus-host fusion via conformational changes in the envelope to the fusion-competent form. The ß-OG pocket is a small molecule target site for inhibition of virus-host fusion. As of date, the only structure of the ß-OG pocket known is of serotype 2. Studies of ß-OG inhibition by small molecules primarily target viral serotype 2. Envelope and ß-OG sequence alignments, reveal dissimilarities across serotypes. In light of protein sequence-structure-function correlation, sequence variations suggest serotypic variations in ß-OG druggability. This, together with the fact that dengue viral proteins do have serotype-specific variations of structure and function, lead to the study of the serotype-specificity of the dengue ß-OG ligand binding behaviour. ß-OG druggability was compared using comparative models of envelope proteins containing the ß-OG pocket in four serotypes of the dengue virus. ß-OG ligand binding was found to vary with respect to hydrophobicity, hydrophilicity, hydrogen bonding, van der Waals interactions with ligands and tightness of the binding site. The study also reports serotype-specific virtual leads identified from a library of 9175 alkaloids, using a consensus docking and scoring approach. The docking algorithms of Glide SP and XP, together with the Lamarckian genetic algorithm were employed for consensus docking. For consensus scoring, the Glide empirical score was employed along with the scoring function of AutoDock. A multi-dimensional lead optimisation approach was performed for optimising affinity, ligand efficiency, lipophilic ligand efficiency, ADMET and molecular torsional strains. The study proposes the serotype-specific inhibition of the ß-OG for an effective inhibition of virus-host fusion, in contrast to a pan inhibitor.

Identification of inhibitors against the potential ligandable sites in the active cholera toxin.

The active cholera toxin responsible for the massive loss of water and ions in cholera patients via its ADP ribosylation activity is a heterodimer of the A1 subunit of the bacterial holotoxin and the human cytosolic ARF6 (ADP Ribosylation Factor 6). The active toxin is a potential target for the design of inhibitors against cholera. In this study we identified the potential ligandable sites of the active cholera toxin which can serve as binding sites for drug-like molecules. By employing an energy-based approach to identify ligand binding sites, and comparison with the results of computational solvent mapping, we identified two potential ligandable sites in the active toxin which can be targeted during structure-based drug design against cholera. Based on the probe affinities of the identified ligandable regions, docking-based virtual screening was employed to identify probable inhibitors against these sites. Several indole-based alkaloids and phosphates showed strong interactions to the important residues of the ligandable region at the A1 active site. On the other hand, 26 top scoring hits were identified against the ligandable region at the A1 ARF6 interface which showed strong hydrogen bonding interactions, including guanidines, phosphates, Leucopterin and Aristolochic acid VIa. This study has important implications in the application of hybrid structure-based and ligand-based methods against the identified ligandable sites using the identified inhibitors as reference ligands, for drug design against the active cholera toxin.