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Computational Modeling of Artemisinins with Antileishmanial Activity

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Thirty-two artemisinins (artemisinin and analogues) with antileishmanial activity against Leishmania donovani are studied. Molecular Electrostatic Potential (MEP) maps are used in an attempt to identify key structural features of the artemisinins that are necessary for their activities and to investigate the interaction with the molecular receptor (heme). The Chemometric Methods: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Stepwise Discriminant Analysis (SDA), K-Nearest Neighbor (KNN) and Soft Independent Modeling of Class Analogy (SIMCA) are employed to reduce dimensionality and to investigate which subset of variables is responsible for the classification between more and less antileishmanial active artemisinins. The PCA, HCA, SDA, KNN and SIMCA studies showed that the variables HOMO (highest occupied molecular orbital) energy, QO1 (charge on O1 atom), QC3 (charge on C3 atom) and POL (molecular polarizability) are responsible to separate the artemisinins according to their degree of antileishmanial activity. The prediction study was done with a set of thirteen artemisinins. Seven artemisininis with biological activity reported in literature, according to our classification: less active, and six artemisinins whose biological tests were not performed yet. All the compounds from literature were confirmed as less active, while one of the artemisinins biologically not tested was predicted as more active against L. donovani. In order to verify if the structural features that are necessary for their antileishmanial activity were maintained, and to investigate the interaction with molecular receptor (heme), we also performed calculation of the MEP. MEP maps were analyzed for the most active compounds of the prediction set.
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Document Type: Research Article

Publication date: November 1, 2011

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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