Structural requirements of N-aryl-oxazolidinone-5-carboxamide derivatives for anti-HIV protease activity using molecular modelling techniques

Abstract

Two- and three-dimensional quantitative structure–activity relation (QSAR) models were generated for a series of N-aryl-oxazolidinone-5-carboxamide derivatives to identify potent anti-HIV-1 integrase ligands. The studies were performed by the partial least squares method coupled with various feature selection methods, such as genetic algorithm (GA) and stepwise methods, to derive QSAR models, which were further validated for statistical significance and predictive ability by internal and external validation. The best two-dimensional QSAR model was selected, which had a correlation coefficient, r2, of 0.9246, a cross-validated squared correlation coefficient, q2, of 0.7726 and an external predictive ability, pred_r2, of 0.8331. This model was developed by GA partial least squares with descriptors such as SsNH2 count, SssOE index, T_N_F_4, SsOH count and T_O_O_2. Three-dimensional QSAR studies gave reasonably good predictive models with a high cross-validated q2 value of 0.6953 and pred_r2 of 0.7499 in the GA k nearest neighbour molecular field analysis method. For a series of N-aryl-oxazolidinone-5-carboxamide derivatives, chemical feature-based pharmacophore models with the lowest root mean square deviation value (0.00765nm) showed one aromatic feature, two hydrogen bond acceptors, one hydrogen bond donor and one aliphatic feature. The information provided by two- and three-dimensional QSAR models may lead to better understanding of the structural requirements of oxazolidinone-5-carboxamides and help in designing novel, potent anti-HIV-1 integrase molecules.