期刊
JOURNAL OF MOLECULAR STRUCTURE
卷 1258, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.molstruc.2022.132689
关键词
Molecular descriptors; Molecular docking; Molecular dynamics; Poly [ADP-Ribose] polymerase 1; Aziridine derivatives; Anti-cancer
资金
- R&D wing of Integral University, Lucknow and Babasaheb Bhimrao Ambedkar University, Lucknow
This study reveals that compound 3a is a potential anticancer candidate targeting PARP1. Through computation and simulation, the stable binding of compound 3a to PARP1 and its good binding free energy were determined.
The Poly [ADP-Ribose] polymerase 1 (PARP1) has recently been thought to be one of the potentially successful targets against cancer, specifically for ovarian and BRCA mutated breast cancers. Here, unprotected (N -H/N-Me) aziridine derivatives were recognized as potential anti-cancer compounds targeting the apoptotic pathway using a combined molecular descriptors (MDs) computation, prediction of activity spectra for substances (PASS), adsorption, distribution, metabolism, excretion and toxicity (ADMET) evaluation, Brain Or IntestinaL EstimateD (BOILED-Egg), Bioactivity score (BAS), docking-based virtual screening (DBVS), integral docking and molecular dynamics (MD) simulation. Twenty one N -H/N-Me aziridine derivatives were screened to identify molecules binding to the PARP1 followed by docking and MD simulation. Compound 3a shows a good binding profile, with the PARP1 as observed by the molecular docking evaluations. The docking complexes of the lead compound 3a with the target PARP1 were found stable during molecular dynamics simulations as represented by the obtained parameters including radius of gyration (Rg) and root mean square deviation (RMSD). The compound 3a yielded good binding free energy using the analysis of molecular mechanics generalized born surface area (MM-GBSA) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA). Therefore, the findings of this study unravels that the compounds 3a is a lead anticancer candidate against selected target PARP1.(c) 2022 Elsevier B.V. All rights reserved.
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