Identification of potential human COX-2 inhibitors using computational modeling and molecular dynamics simulations

Abstract

To explore the structure-property relationship in a set of molecules against Cyclooxygenase-2 (COX-2), pharmacophore modeling, molecular docking and 3D-QSAR studies were performed. A set of 66 reported molecules with different scaffolds having pIC50 values ranging from 8.886 to 4.342 were considered to create a model that can efficiently explain the essential features required for the inhibition of COX-2 and to generate a model that alleviates in distinguishing molecules that have good efficiency. Computational modeling and molecular dynamics simulation approaches are used to identify a new potential COX2 inhibitor. The Molecular screening was performed by using different sequential methods right from Pharmacophore based virtual screening, molecular docking, and molecular dynamics simulations using Maestro11.9 software. Based on the best pharmacophore model (AHRRR_7), the resultant set of 56,480 molecules were screened from the set of 12,16,239 molecules (from ZINC15 database). The preliminarily screened molecules were subjected to molecular docking (PDB_ID: 5F1A) for the further screening through HTVS (High Throughput Virtual Screening), SP (Standard Precision) and XP (Extra Precision) methods. A set of 20 molecules was selected from the resultant molecular docking outcomes (360 molecules) based on the best docking score. Lipinski’s rule of five validates the pharmaceutical bioactivity of all 20 molecules. Out of 20 molecules, 4 were selected as the best molecules based on their docking score and ligand-receptor interaction diagram and further subjected to molecular dynamics (MD) simulation study. Outcomes of the present study conclude with a new molecule (SB2) which shows the best interactions for the inhibition of human COX-2 enzyme in comparison to the reported molecules.