Issue 43, 2021

Ligand-based pharmacophore modeling and molecular dynamic simulation approaches to identify putative MMP-9 inhibitors

Abstract

MMP-9 is a calcium-dependent zinc endopeptidase that plays a crucial role in various diseases and is a ubiquitous target for many classes of drugs. The availability of MMP-9 crystal structure in combination with aryl sulfonamide anthranilate hydroxamate inhibitor facilitates to accentuate the computer-aided screening of MMP-9 inhibitors with the presumed binding mode. In the current study, ligand-based pharmacophore modeling and 3D-QSAR analysis were performed using 67 reported MMP-9 inhibitors possessing pIC50 in the range of 5.221 to 9.000. The established five-point hypothesis model DDHRR_1 was statistically validated using various parameters R2 (0.9076), Q2 (0.8170), and F value (83.5) at a partial least square of four. Hypothesis validation and enrichment analysis were performed for the generated hypothesis. Further, Y-scrambling and Xternal validation using mean-absolute error-based criteria were performed to evaluate the reliability of the model. Docking in the XP mode and binding free energy was calculated for 67 selected ligands to explore the key binding interactions and binding affinity against the MMP-9 enzyme. Additionally, high-throughput virtual screening was carried out for 2.3 million chemical molecules to explore the potential virtual hits, and their predicted activity was calculated. Thus, the results obtained aid in developing novel MMP-9 inhibitors with significant activity and binding affinity.

Graphical abstract: Ligand-based pharmacophore modeling and molecular dynamic simulation approaches to identify putative MMP-9 inhibitors

Supplementary files

Article information

Article type
Paper
Submitted
18 5 2021
Accepted
17 7 2021
First published
06 8 2021
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2021,11, 26820-26831

Ligand-based pharmacophore modeling and molecular dynamic simulation approaches to identify putative MMP-9 inhibitors

B. K. R. Sanapalli, V. Yele, S. Jupudi and V. V. S. R. Karri, RSC Adv., 2021, 11, 26820 DOI: 10.1039/D1RA03891E

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