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Chemometric modelling of antimalarial activity of aryltriazolylhydroxamates
Authors:Probir Kumar Ojha
Institution:Division of Medicinal and Pharmaceutical Chemistry, Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology , Jadavpur University , Kolkata, 700 032, India
Abstract:We have performed quantitative structure–activity relationship (QSAR) and quantitative activity–activity relationship (QAAR) studies for aryltriazolylhydroxamates having antimalarial activity data against both chloroquine-sensitive (D6 clone) and chloroquine-resistant (W2 clone) strains of Plasmodium falciparum to understand the relationships between the biological activity and molecular properties for the design of new compounds. The QSAR studies were performed using 35 compounds among which 26 molecules were taken using k-means clustering technique in the training set for the derivation of the QSAR models and nine molecules were kept as the test-set compounds to evaluate the predictive ability of the derived models. The chemometric tool used for the analysis was the genetic function approximation. The developed models were analysed in terms of their predictive ability, and comparable results were obtained for cross-validated predictive variance (Q 2) and externally predicted variance (R 2 pred) values (0.761 and 0.829, respectively, for the D6 model, 0.708 and 0.748, respectively, for the W2 model and 0.984 and 0.982, respectively for the QAAR model). The QSAR models suggest that the number of methylene groups (between the triazolyl and hydroxamate moieties) and partially negatively charged surface areas of the molecules are important parameters for the antimalarial activity.
Keywords:genetic function approximation  k-means cluster  quantitative structure–activity relationship  quantitative activity–activity relationship  aryltriazolylhydroxamate
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