Identification of a 2-aminothiazole framework using classical QSAR model targeting chloroquine-sensitive Plasmodium falciparum

Abstract

Chloroquine-sensitive Plasmodium falciparum is the most deadly form of human malaria. It is associated with a number of mutations in P. falciparum. Chloroquine-resistant transporter is a protein that serves as a transporter in the parasite's digesting vacuole membrane. In order to combat chloroquine-sensitive P. falciparum strains (NF54), this study employs QSAR modelling to examine possible structural alterations of 2-amino-thiazole derivatives. The traditional QSAR model was built using the PaDEL descriptor via QSARINS software. The model was found to have an internal cross-validation value of Q2loo = 0.7890 and an external validation parameter of RMSE ext = 0.6938. The predicted pIC50 values from the QSAR techniques for the case study chemicals were compared and found to be well fitted to the model and well predicted for the external set of compounds. The outcome demonstrates the value of using the suggested method in the creation of new medication candidates could fill the critical gap in scientific knowledge and open up novel possibilities for pharmaceutical development.