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Quantitative Structure-Activity Relationships for Anticancer Activity of 2- Phenylindoles Using Mathematical Molecular Descriptors

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Calculated atom pairs (APs) and a set of 369 topological indices (TIs) calculated by POLLY, Triplet, and Molconn-Z software were used to develop QSARs for anticancer activity of a group of 2-phenyl indoles. The TIs included both topostructural (TS) and topochemical (TC) indices. Results show that ridge regression using TS indices, TC indices, and atom pairs produced high-quality models for the prediction of anticancer activity of a set of 89 phenylindole derivatives. Quality of QSARs derived in this paper is comparable or superior to both CoMFA and other statistical models reported for 2-phynylindoles in the earlier published literature. Easily calculated molecular descriptors like TIs and APs used in this paper may find application in the QSAR and in silico prediction of bioactivity of new phenylindole derivatives.

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Keywords: Breast cancer; CoMFA; QSAR; anticancer activity; mathematical molecular descriptors; phenylindole; ridge regression; topochemical indices triglycerides; topological indices; topostructural indices; tubulin

Document Type: Research Article

Publication date: June 1, 2011

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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