Abstract
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.
Keywords: Breast cancer, anticancer activity, phenylindole, tubulin, mathematical molecular descriptors, ridge regression, topological indices, topostructural indices, topochemical indices triglycerides, QSAR, CoMFA
Current Computer-Aided Drug Design
Title: Quantitative Structure-Activity Relationships for Anticancer Activity of 2- Phenylindoles Using Mathematical Molecular Descriptors
Volume: 7 Issue: 2
Author(s): Subhash C. Basak, Qianhong Zhu and Denise Mills
Affiliation:
Keywords: Breast cancer, anticancer activity, phenylindole, tubulin, mathematical molecular descriptors, ridge regression, topological indices, topostructural indices, topochemical indices triglycerides, QSAR, CoMFA
Abstract: 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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Cite this article as:
C. Basak Subhash, Zhu Qianhong and Mills Denise, Quantitative Structure-Activity Relationships for Anticancer Activity of 2- Phenylindoles Using Mathematical Molecular Descriptors, Current Computer-Aided Drug Design 2011; 7 (2) . https://dx.doi.org/10.2174/157340911795677648
DOI https://dx.doi.org/10.2174/157340911795677648 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
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