Knowledge of protein targets of drugs is necessary in solving various problems in drug discovery process. A computer aided drug design to new drug development is striking alternative to the traditional paradigm of drug discovery through screening. The elements of this approach are reviewed, with emphasis on the use of homology-built model structures. QSAR is among the most comprehensively used in-silico method for analogue-based drug design. The use of various descriptor classes like, quantum chemical, conceptual density functional theory (DFT) molecular mechanics and docking-based descriptors in prediction of anti-cancer activity are well known. The QSAR has broadly been applied for the activity prediction of various series of biological and chemical compounds together with anticancer drugs. This article consists of review of QSAR studies which have been carried out with some newer anticancer agents which are potent and highly selective.
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