The efficiency of multi-target drugs: the network approach might help drug design.
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.
Csermely
Péter
P
Department of Medical Chemistry, Semmelweis University, PO Box 260, H-1444 Budapest 8, Hungary. csermely@puskin.sote.hu
Agoston
Vilmos
V
Pongor
Sándor
S
D019295:Computational Biology; D015195:Drug Design; D008954:Models, Biological; D016571:Neural Networks, Computer