| Literature DB >> 15134505 |
Aihua Xie1, Chenzhong Liao, Zhibin Li, Zhiqiang Ning, Weiming Hu, Xianping Lu, Leming Shi, Jiaju Zhou.
Abstract
Histone deacetylases (HDACs) play a critical role in gene transcription and have become a novel target for the discovery of drugs against cancer and other diseases. During the past several years there have been extensive efforts in the identification and optimization of histone deacetylase inhibitors (HDACIs) as novel anticancer drugs. Here we report a comprehensive quantitative structure-activity relationship (QSAR) study of HDACIs in the hope of identifying the structural determinants for anticancer activity. We have identified, collected, and verified the structural and biological activity data for 124 compounds from various literature sources and performed an extensive QSAR study on this comprehensive data set by using various QSAR and classification methods. A highly predictive QSAR model with R(2) of 0.76 and leave-one-out cross-validated R(2) of 0.73 was obtained. The overall rate of cross-validated correct prediction of the classification model is around 92%. The QSAR and classification models provided direct guidance to our internal programs of identifying and optimizing HDAC inhibitors. Limitations of the models were also discussed.Entities:
Mesh:
Substances:
Year: 2004 PMID: 15134505 DOI: 10.2174/1568011043352948
Source DB: PubMed Journal: Curr Med Chem Anticancer Agents ISSN: 1568-0118