Computational methods in drug discovery

Pharmacol Rev. 2013 Dec 31;66(1):334-95. doi: 10.1124/pr.112.007336. Print 2014.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Animals
  • Computer-Aided Design
  • Drug Discovery*
  • Drug-Related Side Effects and Adverse Reactions
  • Humans
  • Ligands
  • Molecular Structure
  • Pharmaceutical Preparations / metabolism
  • Pharmacokinetics


  • Ligands
  • Pharmaceutical Preparations