Why so few drug targets: A mathematical explanation?

Kyaw Tun, Marta Menghini, Lina D'Andrea, Pawan Dhar, Hiroshi Tanaka, Alessandro Giuliani

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

The apparently paradoxical lack of correlation between the huge increase in the discovery of new potential drug targets made possible by the post-genomic sciences and new drugs development has stimulated many different interpretations. Here we illustrate the general principle of redundancy of biological pathways on hand of simplified mathematical approaches applied to different models of biological regulation. The simulation was based on the analysis of the 'degree of autonomy' of network architectures in which the possibility for an external stimulus (e.g. a drug) impinging into a specific node to be sensed by the entire network, and eventually amplified up to a macroscopic consequence, was demonstrated to be limited to strictly linear pathways. The implications of such a result for poly pharmacology and computational approaches to drug development are described as well.

Original languageEnglish
Pages (from-to)206-213
Number of pages8
JournalCurrent Computer-Aided Drug Design
Volume7
Issue number3
DOIs
Publication statusPublished - 2011 Sep

Keywords

  • Drug development
  • Multiple targets
  • Networks
  • Pharmacology
  • Systems biology

ASJC Scopus subject areas

  • Molecular Medicine
  • Drug Discovery

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