Abstract
Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.
Footnotes
This work was supported by the National Science Foundation through the Office for Cyber Infrastructure Transformative Computational Sciences Fellowship [OCI-1122919] (E.W.L.); the National Institutes of Health National Institute of Mental Health [Grant R01 MH090192] (to the Meiler laboratory); the National Institutes of Health National Institute of General Medical Sciences [Grant R01 GM099842]; and the National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases [Grant R01 DK097376].
- Copyright © 2013 by The American Society for Pharmacology and Experimental Therapeutics
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