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

• Published in: Trends in pharmacological sciences (Regular ed.) Vol. 26; no. 4; pp. 178 - 182
• Main Authors: Csermely, Péter, Ágoston, Vilmos, Pongor, Sándor
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.04.2005
• Subjects: Computational Biology; Drug Design; Models, Biological; Neural Networks (Computer)
• ISSN: 0165-6147; 1873-3735
• DOI: 10.1016/j.tips.2005.02.007

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.