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Abstract
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.