QSAR study on the antimalarial activity of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors

Abstract

Plasmodium falciparum, the most fatal parasite that causes malaria, is responsible for over one million deaths per year. P. falciparum dihydroorotate dehydrogenase (PfDHODH) has been validated as a promising drug development target for antimalarial therapy since it catalyzes the rate-limiting step for DNA and RNA biosynthesis. In this study, we investigated the quantitative structure–activity relationships (QSAR) of the antimalarial activity of PfDHODH inhibitors by generating four computational models using a multilinear regression (MLR) and a support vector machine (SVM) based on a dataset of 255 PfDHODH inhibitors. All the models display good prediction quality with a leave-one-out q² >0.66, a correlation coefficient (r) >0.85 on both training sets and test sets, and a mean square error (MSE) <0.32 on training sets and <0.37 on test sets, respectively. The study indicated that the hydrogen bonding ability, atom polarizabilities and ring complexity are predominant factors for inhibitors’ antimalarial activity. The models are capable of predicting inhibitors’ antimalarial activity and the molecular descriptors for building the models could be helpful in the development of new antimalarial drugs.

Keywords:

• Quantitative structure–activity relationships (QSAR)
• Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH)
• Kohonen’s self-organizing map
• multilinear regression
• support vector machine

Acknowledgments

The authors thank Molecular Networks GmbH, Erlangen, Germany for providing the programs ADRIANA.Code, Corina and SONNIA for our scientific work.