  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 hits and their multi-fitting, low-affinity drug candidates but also on
more efficient in vivo testing.
