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Ashok Sharma

Researcher at Central Institute of Medicinal and Aromatic Plants

Publications -  73
Citations -  1183

Ashok Sharma is an academic researcher from Central Institute of Medicinal and Aromatic Plants. The author has contributed to research in topics: Docking (molecular) & Virtual screening. The author has an hindex of 18, co-authored 73 publications receiving 872 citations. Previous affiliations of Ashok Sharma include Council of Scientific and Industrial Research & Academy of Scientific and Innovative Research.

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Purification, characterization, and in vitro activity of 2,4-Di-tert-butylphenol from Pseudomonas monteilii PsF84: conformational and molecular docking studies.

TL;DR: To the authors' knowledge, this is the first report of antifungal VOC (2,4-di-tert-butylphenol) produced by P. monteilii that can be a potent inhibitor of β-tubulin of F. oxysporum.
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An insight into medicinal chemistry of anticancer quinoxalines

TL;DR: A wide variety of bioactive quinoxalines has been realised as antitumour, antifungal, anti-inflammatory, antimicrobial, and antiviral agents.
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Molecular docking studies to map the binding site of squalene synthase inhibitors on dehydrosqualene synthase of Staphylococcus aureus.

TL;DR: This study attempts to focus on squalene synthase inhibitors, lapaquistat acetate and squalestatins reported as cholesterol lowering agents in vitro and in vivo but not studied in context to dehydrosqualenes synthase of S. aureus to develop new drugs to target the virulence factor.
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Identification and analysis of miRNAs and their targets in ginger using bioinformatics approach

TL;DR: Thirteen miRNA families were found to regulate 300 target transcripts and play an important role in cell signaling, reproduction, metabolic process and stress, to understand the miRNA mediated gene regulatory control and to validate miRNA target predictions.
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Molecular docking based virtual screening of natural compounds as potential BACE1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis.

TL;DR: Screening the natural database InterBioScreen, followed by three-dimensional (3D) QSAR pharmacophore modeling, mapping, in silico ADME/T predictions to find the potential BACE1 inhibitors and molecular dynamics of selected inhibitors were performed to observe the dynamic structure of protein after ligand binding.