CONSTRUCTION AND RETROSPECTIVE VALIDATION OF STRUCTURE-BASED VIRTUAL SCREENING PROTOCOLS TO IDENTIFY POTENT LIGANDS FOR HUMAN ADRENERGIC BETA-2 RECEPTOR

Abstract

Adrenergic Beta-2 Receptor (ADRB2) is a member of G-protein coupled receptors family, which has served as targets for more than 30% of top-selling drugs in the market. Recently, an enhanced dataset of ligands and decoys for ADRB2 has publicly available. However, the original retrospective structure-based virtual screening campaign accompanying the dataset showed relatively poor quality with enrichment factor of true positives at 1% false positives (EF 1% )value of 3.9. In this article, the construction and retrospective validation of a structure-based virtual screening protocol by employing PLANTS1.2 as the molecular docking software and PyPLIF as an alternative post docking scoring functions are presented. The results show that the developed protocols have better quality compared the original structure-based virtual screening with EF 1% values of 24.24 and 8.22 by using ChemPLP from PLANTS1.2 and by using Tc-PLIF from PyPLIF, respectively. Further investigation by performing systematic filtering resulted in the identification of D113, S203, and N293 as molecular determinants in ADRB2-ligand binding. Key words : Structure-based virtual screening, molecular docking, adrenergic beta-2 receptor, protein-ligand interaction fingerprinting, molecular determinants