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

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.

恶性疟原虫(Plasmodium falciparum)是引发疟疾的致死性最强的寄生虫，每年造成超百万例死亡。恶性疟原虫二氢乳清酸脱氢酶(PfDHODH)已被验证为抗疟疾治疗极具潜力的药物开发靶点，因其催化DNA与RNA生物合成的限速步骤。本研究基于包含255个PfDHODH抑制剂的数据集，采用多元线性回归(MLR)与支持向量机(SVM)构建了四种计算模型，以此探究PfDHODH抑制剂抗疟疾活性的定量构效关系(QSAR)。所有模型均展现出优异的预测性能：训练集与测试集的留一法q²值均大于0.66，相关系数(r)均大于0.85；训练集的均方误差(MSE)小于0.32，测试集的MSE则小于0.37。本研究表明，氢键结合能力、原子极化率与环复杂度是影响抑制剂抗疟疾活性的主要因素。所构建的模型可有效预测抑制剂的抗疟疾活性，且用于建模的分子描述符可为新型抗疟疾药物的开发提供助力。