Structural analysis and molecular dynamics simulation studies of HIV-1 antisense protein predict its potential role in HIV replication and pathogenesis.

The functional significance of the HIV-1 Antisense Protein (ASP) has been a paradox since its discovery. The expression of this protein in HIV-1-infected cells and its involvement in autophagy, transcriptional regulation, and viral latency have sporadically been reported in various studies. Yet, the definite role of this protein in HIV-1 infection remains unclear. Deciphering the 3D structure of HIV-1 ASP would throw light on its potential role in HIV lifecycle and host-virus interaction. Hence, using extensive molecular modeling and dynamics simulation for 200 ns, we predicted the plausible 3D-structures of ASP from two reference strains of HIV-1 namely, Indie-C1 (subtype-C) and NL4-3 (subtype-B) so as to derive its functional implication through structural domain analysis. In spite of sequence and structural differences in subtype B and C ASP, both structures appear to share common domains like the Von Willebrand Factor Domain-A (VWFA), Integrin subunit alpha-X (ITGSX), and ETV6-Transcriptional repressor, thereby reiterating the potential role of HIV-1 ASP in transcriptional repression and autophagy, as reported in earlier studies. Gromos-based cluster analysis of the centroid structures also reassured the accuracy of the prediction. This is the first study to elucidate a highly plausible structure for HIV-1 ASP which could serve as a feeder for further experimental validation studies.

Structure-based design of small molecule and peptide inhibitors for selective targeting of ROCK1: an integrative computational approach.

Rho-associated, coiled-coil-containing protein kinase (ROCK1) regulates cell contraction, morphology, and motility by phosphorylating its downstream targets. ROCK1 is a proven target for many pathological conditions like cancer, atherosclerosis, glaucoma, neuro-degeneration, etc. Though many kinase inhibitors are available, there is a dearth of studies on repurposing approved drugs and novel peptide inhibitors that could potentially target ROCK1. Hence, in this study, an extensive integration of open-source pipelines was employed to probe the potential inhibitors (ligand/peptide) for targeting ROCK1. To start with, a systematic enrichment analysis was performed to delineate the most optimal ROCK1 crystal structure that can be harnessed for drug design. A comparative analysis of conformational flexibility between monomeric and dimeric forms was also performed to prioritize the optimal assembly for structural studies. Subsequently, Virtual screening of FDA-approved drugs in Drugbank was performed using POAP pipeline. Further, the top hits were probed for binding affinity, crucial interaction fingerprints, and complex stability during MD simulation. In parallel, a combinatorial tetrapeptide library was also virtually screened against ROCK1 using the PepVis pipeline. Following which, all these shortlisted inhibitors (compounds/peptides) were subjected to Kinomerun analysis to infer other potential kinase targets. Finally, Polydatin and conivaptan were prioritized as the most potential repurposable inhibitors, and WWWF, WWVW as potential inhibitory peptides for targeting ROCK1. The prioritized inhibitors are highly promising for use in therapeutics, as these are resultants of the multilevel stringent filtration process. The computational strategies implemented in this study could potentially serve as a scaffold towards selective inhibitor design for other kinases.Communicated by Ramaswamy H. Sarma.

Elucidating the Therapeutic Potential of Cell-Penetrating Peptides in Human Tenon Fibroblast Cells.

Cell-penetrating peptides (CPPs) have been widely used as vehicles for delivering therapeutic molecules to the site of action. Apart from their delivering potential, the biological effects of CPPs have not been explored in detail. JTS-1 is a CPP that has been reported to have gene delivery functions, although its biological role is yet to be determined. Hence, in this study, we revealed the biological mechanism such as its uptake mechanism and immunogenic potential and function using primary human tenon fibroblast (TF) cells collected from patients undergoing glaucoma trabeculectomy surgery. Our results showed that the JTS-1 peptide has an α-helical structure and is nontoxic up to 1 µM concentration. It was found to be colocalized with early endosome (Rab5), recycling endosome (Rab7), and Rab11 and interacted with major histocompatibility complex (MHC) class I and II. The peptide also affected actin polymerization, which is regulated by cofilin phosphorylation and ROCK1 localization. It also inhibited TF cell proliferation. Therefore, the JTS-1 peptide could be used as a possible therapeutic agent for modifying the fibrosis process, where TF proliferation is a key cause of surgery failure.

KinomeRun: An interactive utility for kinome target screening and interaction fingerprint analysis towards holistic visualization on kinome tree.

Kinases are key targets for many of the pathological conditions. Inverse screening of ligands serves as an essential mode to identify potential kinase targets in modern drug discovery research. Hence, we intend to develop KinomeRun, a robust pipeline for inverse screening and kinome tree visualization through the seamless integration of kinome structures, docking and kinome-drug interaction fingerprint analysis. In this pipeline, the hurdle of residue numbering in kinome is also resolved by creating a common index file with the conserved kinase pocket residues for comparative interaction analysis. KinomeRun can be used to screen the ligands of interest docked against multiple kinase structures in parallel around the kinase binding site and also to filter out the targets with unique interaction patterns. This automation is essential for prioritization of kinase targets that show specificity for a given drug and will also serve as a crucial tool kit for holistic approaches in kinase drug discovery. KinomeRun is developed using python and bash programming language and is distributed freely under the GNU GPL licence-3.0 and can be downloaded at https://github.com/inpacdb/KinomeRun. The tutorial videos for installation, target screening and customized filtration are available at https://www.youtube.com/playlist?list=PLuIaEFtMVgQ7v__WigQH9ilGVxrfI1LKs and also be downloaded for offline viewing from the github link.

PepVis: An integrated peptide virtual screening pipeline for ensemble and flexible docking protocols.

Peptide therapeutics is proven to be highly potential in the treatment of various diseases due to its specificity, biological safety, and cost-effectiveness. Many of the FDA-approved peptides are currently available for therapeutic applications. In the current postgenomic era, high-throughput computational screening of drugs and peptides are highly exploited in peptide therapeutics for cost-effective and robustness. However, there is a paucity of efficient pipelines that automate virtual screening process of peptides through integration of open-source tools that are optimal to perform ensemble and flexible docking protocols. Hence, in this study, we developed a GUI-based pipeline named PepVis for automated script generation for large-scale peptide modeling and virtual screening. PepVis integrates Modpep and Gromacs for peptide structure modeling and optimization; AutoDock Vina, ZDOCK, and AutoDock CrankPep for virtual screening of peptides; ZRANK2 for rescoring of protein-peptide complexes, and FlexPepDock for flexible refinement of protein-peptide complexes. Benchmarking of ensemble docking through PepVis infers that ModPep + Vina to outperform ModPep + ZDock in terms of detecting near-natives from LEADS-PEP dataset. PepVis is built modular to incorporate many other docking algorithms in the future. This pipeline is distributed freely under the GNU GPL license and can be downloaded at https://github.com/inpacdb/PepVis.

PocketPipe: A computational pipeline for integratedPocketome prediction and comparison.

Functional characterisation of proteins often depends on specific interactions with other molecules. In the drug discovery scenario, the ability of a protein to bind with drug-like molecule with a high affinity is referred as druggability. Deciphering such druggable binding pockets on proteins plays an important role in structure-based drug designing studies. Moreover, availability of plethora of structural data poses a need automated pipelines which can efficiently integrate robust algorithms towards large-scale pocket identification and comparison. These pipelines have direct applicability on off-target analysis, drug repurposing and structural prioritization of drug targets in pathogenic microbes. However, currently there is a paucity of such efficient pipelines. Hence, by this study a highly optimized shell script based pipeline (PocketPipe) has been developed with seamless integration of robust algorithms namely, P2Rank (predicts binding sites based on machine learning) and PocketMatch-v2.1 (compares binding pockets by residue-based method), for pocketome generation and comparison, respectively. The process of input workflow and various steps carried out by PocketPipe and the output results are well documented in the operating manual. On execution, the pipeline features seamless operability, high scalability, dynamic file handling and results parsing. PocketPipe is distributed freely under GNU GPL license and can be downloaded at https://github.com/inpacdb/PocketPipe.

Analysis of candidate genes ZEB1 and LOXHD1 in late-onset Fuchs' endothelial corneal dystrophy in an Indian cohort.

BACKGROUND: Fuchs' endothelial corneal dystrophy (FECD) is a complex degenerative disease of the corneal endothelium with genetic predisposition. Pathogenic rare variants have been identified in SLC4A11, LOXHD1, ZEB1, and AGBL1. Association of single nucleotide polymorphisms (SNPs) and CTG trinucleotide repeat expansions in the intron of TCF4 gene to FECD has been studied across multiple ethnicities. Recently, genome-wide association studies have also identified KANK4, LAMC1, and ATP1B1 as novel loci for FECD. Here, we report the contribution of ZEB1 and LOXHD1 genes in our sporadic late-onset FECD cohort. MATERIALS AND METHODS: In the experimental study, coding regions of ZEB1 and LOXHD1 were screened by Sanger DNA sequencing in 52 late-onset and 5 early-onset FECD cases of Indian origin, recruited at a tertiary eye care center. Further, bioinformatics analysis was done. RESULTS: One reported missense mutation, c.2522A>C; p.(Q841P), and one variant of uncertain significance (VUS), c.619A>G; p.(S207G), were identified in the ZEB1 gene. One VUS, c.6413G>Ap.(R2138Q), was observed in LOXHD1. A 3D structural bioinformatic analysis of the missense variant in LOXHD1 predicted the variant to affect the structure-function relationship of the protein. DISCUSSION: While mutations in ZEB1 contributed to 2% of the late-onset FECD cases, the exact role of the two VUS identified in ZEB1 and LOXHD1 in FECD pathogenesis needs to be studied.