In silico-based identification of new anti-PfDHFR drug candidates via 1,3,5-triazine derivatives

Abstract

Quantitative structure-activity relationship study was used to investigate the relationship between anti-PfDHFR activity and structure of twenty-eight 1,3,5-triazine derivatives. We performed benchmark studies on the molecular geometry, electron properties of 1,3,5-triazine using semi-empirical(PM3), density functional theory and post Hartree-Fock methods. Followed by a QSAR study using multiple linear regression (MLR) and artificial neural networks (ANN). The QSAR models developed allow identify/describe the relationship between the biological activity of the molecules and their molecular descriptors (topological, physicochemical, electronic...). A further external set of compounds was used for validation where a high correlation between experimental and predicted anti-PfDHFR activity values is noticed. This QSAR study provides useful information for developing novel PfDHFR inhibitors. The set’s ADME properties and drug similarities, as well as newly produced compounds and reference ligand, were investigated. These findings would be extremely useful in guiding optimization for the development of new anti-PfDHFR drug candidates.