Global vision of druggability issues: applications and perspectives

Drug Discov Today. 2017 Feb;22(2):404-415. doi: 10.1016/j.drudis.2016.11.021. Epub 2016 Dec 6.


During the preliminary stage of a drug discovery project, the lack of druggability information and poor target selection are the main causes of frequent failures. Elaborating on accurate computational druggability prediction methods is a requirement for prioritizing target selection, designing new drugs and avoiding side effects. In this review, we describe a survey of recently reported druggability prediction methods mainly based on networks, statistical pocket druggability predictions and virtual screening. An application for a frequent mutation of p53 tumor suppressor is presented, illustrating the complementarity of druggability prediction approaches, the remaining challenges and potential new drug development perspectives.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites
  • DNA / metabolism
  • Drug Discovery*
  • Humans
  • Models, Theoretical*
  • Tumor Suppressor Protein p53 / genetics
  • Tumor Suppressor Protein p53 / metabolism


  • Tumor Suppressor Protein p53
  • DNA