Use of 3D QSAR Methodology for Data Mining the National Cancer Institute Repository of Small Molecules: Application to HIV-1 Reverse Transcriptase Inhibition

Abstract

A three-dimensional (3D) stereoelectronic pharmacophore developed from a 3D quantitative structure–activity relationship (QSAR) investigation formed the basis of the development of a two-phase data-mining methodology to uncover novel leads to inhibit human immunodeficiency virus type 1 (HIV-1) reverse transcriptase at the nonnucleoside binding site. The database searching phase employed a field search for ligand requirements (such as logP, molecular volume) that were accessible from the database keys. Next, a 3D database search was performed that used an automated fitting procedure and the calculation of several binding parameters. These binding parameters were used to test the hits by a discriminant function that was previously trained to recognize active from inactive analogs. During the structural evaluation phase of the methodology, conformational properties and complementary receptor features of the hits were examined by 2D and 3D evaluations, which were followed by molecular modeling investigations. When this method was applied to a test database, an improvement from 6.4% to 100% active analogs was achieved.