Quantitative Structure Activity Relationship Study of Naphthoquinone Analogs as Possible DNA Topoisomerase Inhibitors | Abstract

Der Pharma Chemica
Journal for Medicinal Chemistry, Pharmaceutical Chemistry, Pharmaceutical Sciences and Computational Chemistry

ISSN: 0975-413X


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Quantitative Structure Activity Relationship Study of Naphthoquinone Analogs as Possible DNA Topoisomerase Inhibitors

Author(s): Prabha T, Kaviarasan L, Sivakumar T

Quantitative Structure Activity Relationship (QSAR) is among the most widely used computational technology for analogue-based drug design. A molecular modeling approach of Naphthoquinone (NQ) analogue as anticancer activity from recently reported literature were taken and was QSAR model was generated by using MOE 2009.10. DNA topoisomerases are enzymes that alter DNA topology by causing and resealing DNA strand breaks. The quinone nuclei, which can inhibit the activity of topoisomerase. In order to develop a new pharmacophoric model for this inhibition, a QSAR approach of reported NQ derivatives against cancer cell has been studied. Multiple linear regression analysis was performed to derive the quantitative structure activity relationship models which were further evaluated internally as well as externally for the prediction of activity. Accurate IC50 values (μM) were collected for 26 analogs, and other descriptor parameters, such as log p (o/w), MR, DM, EELE, LUMO, HOMO, and TPSA were compared with these compounds. A training set of 26 analogs, all having a common NQ moiety, provided a cross-validated correlation coefficient (r2) value of 0.10835 and root mean square error value of 0.3951. The resulting QSAR pharmacophore model generated from the present study should be useful in the design a similar group of more potent substituted compounds of NQ targets as anticancer agents. Moreover, based on this QSAR study we have developed the 20 newly designed NQ derivatives and estimated their predicted IC50 values theoretically by using file which is generated by QSAR study of the training set compounds.

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