QSAR modeling, docking and ADMET studies for exploration of potential anti-malarial compounds against Plasmodium falciparum

Abstract

Abstract Development of resistance in the Plasmodium falciparum to Artemisinin, the most effective anti-malarial compound, threatens malaria elimination tactics. To gain more efficacious Artemisinin derivatives, QSAR modeling and docking was performed. In the present study, 2D-QSAR model and molecular docking were used to evaluate the Artemisinin compounds and to reveal their binding modes and structural basis of inhibitory activity. Moreover, ADMET-related descriptors have been calculated to predict the pharmacokinetic properties of the effective compounds. The correlation expressed as coefficient of determination (r2) and prediction accuracy expressed in the form of cross-validated r2 (q2) of QSAR model are found 0.9687 and 0.9586, respectively. Total 239 descriptors have been included in the study as independent variables. The four chemical descriptors, namely radius of gyration, mominertia Z, SssNH count and SK Average have been found to be well correlated with anti-malarial activities. The model was statistically robust and has good predictive power which could be employed for virtual screening of proposed anti-malarial compounds. QSAR and docking results revealed that studied compounds exhibit good anti-malarial activities and binding affinities. The outcomes could be useful for the design and development of the potent inhibitors which after optimization can be potential therapeutics for malaria.