Computational Approach to Drug Design for Oxazolidinones as Antibacterial Agents

Abstract

A three dimensional Quantitative Structure Activity Relationship (3D-QSAR) model for a series of (S)-3-Aryl-5-substituted oxazolidinones was developed to gain insights into the design for potential new antibacterial agents. It was found that the Comparative Molecular Field Analysis (CoMFA) method yielded good results while the Comparative Molecular Similarity Indices Analysis (CoMSIA) was less satisfactory. The CoMFA method yielded a cross-validated correlation coefficient q(2) = 0.681, non-cross-validated R(2) = 0.991, SE (Standard Error ) = 0.054, and the value of statistical significance measure F = 266.98. The relative steric and electrostatic contributions are 0.542 and 0.458, respectively. These results indicate that the model possesses a high predictivity. Guided by this model, three new compounds were synthesized. All these compounds exhibit inhibitory activity; two of them were shown having high activity (MIC = 1.0 microg/ml). The activity observed by experiments was in good agreement with the theoretical one. It is anticipated that the present model would be of value in facilitating design of new potent antibacterial agents.