Sunil Kumar Tripathi
Alagappa University
19 Papers
59 Citations
Sunil Kumar Tripathi is an academic researcher from Alagappa University. The author has contributed to research in topics: Docking (molecular) & Biology. The author has an hindex of 10, co-authored 17 publications. Previous affiliations of Sunil Kumar Tripathi include Madurai Kamaraj University.
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Papers
Extra precision docking, free energy calculation and molecular dynamics simulation studies of CDK2 inhibitors.
TL;DR: It is suggested that the phenylacetyl type of substituents and cyclohexyl moiety make the favorable interactions with a number of residues in the active site, and show better inhibitory activity to improve the pharmacokinetic profile of compounds against CDK2.
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•Journal Article
Tool development for Prediction of pIC50 values from the IC50 values - A pIC50 value calculator
TL;DR: The tool for the prediction of pIC50 values from the IC50 in nanomolar and micromolar using the JavaScript programming language, which is available at the Sanjeevslab webpage: http://www.110mb.com/index.php?p=1_7_Tools.
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Identification of potential HIV-1 integrase strand transfer inhibitors: in silico virtual screening and QM/MM docking studies.
TL;DR: The pharmacophore hypothesis AADHR was used as a 3D query in a sequential virtual screening study to filter small molecule databases Maybridge, ChemBridge and Asinex and found three compounds that form stable interactions with key residues.
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Shape and pharmacophore-based virtual screening to identify potential cytochrome P450 sterol 14α-demethylase inhibitors.
Karnati Konda Reddy,Sanjeev Kumar Singh,Sunil Kumar Tripathi,Chandrabose Selvaraj,Venkatesan Suryanarayanan +4 more
TL;DR: A virtual screening protocol using both phase shape and pharmacophore model against Asinex, ChemBridge and Maybridge databases identified potential CYP51 inhibitors, which could also be employed to design ligands with enhanced inhibitory potencies and to predict the potencies of analogs to guide synthesis/or prepare synthetic antifungal analogs against CYP 51.
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Molecular docking, QPLD, and ADME prediction studies on HIV-1 integrase leads
TL;DR: These compounds could be employed to design ligands with enhanced inhibitory potencies and to predict the potencies of analogs to guide synthesis/or prepare synthetic analogs for second generation drug development against HIV-1 IN.
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