The efficiency of multi-target drugs: the network approach might help drug design

Trends Pharmacol Sci. 2005 Apr;26(4):178-82. doi: 10.1016/


Despite considerable progress in genome- and proteome-based high-throughput screening methods and rational drug design, the number of successful single-target drugs did not increase appreciably during the past decade. Network models suggest that partial inhibition of a surprisingly small number of targets can be more efficient than the complete inhibition of a single target. This and the success stories of multi-target drugs and combinatorial therapies led us to suggest that systematic drug-design strategies should be directed against multiple targets. We propose that the final effect of partial, but multiple, drug actions might often surpass that of complete drug action at a single target. The future success of this novel drug-design paradigm will depend not only on a new generation of computer models to identify the correct multiple targets and their multi-fitting, low-affinity drug candidates but also on more-efficient in vivo testing.

Publication types

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

MeSH terms

  • Computational Biology
  • Drug Design*
  • Models, Biological
  • Neural Networks, Computer*