Protein kinases are attractive targets for therapeutic interventions in many diseases. Due to their importance
in drug discovery, a kinase family-specific potential of mean force (PMF) scoring function, kinase-PMF,
was developed to assess the binding of ATP-competitive kinase inhibitors. It is hypothesized that targetspecific
PMF scoring functions may achieve increased performance in scoring along with the growth of the
PDB database. The kinase-PMF inherits the functions and atom types in PMF04 and uses a kinase data set
of 872 complexes to derive the potentials. The performance of kinase-PMF was evaluated with an external
test set containing 128 kinase crystal structures. We compared it with eight scoring functions commonly
used in computer-aided drug design, either in terms of the retrieval rate of retrieving “right” conformations
or a virtual screening study. The evaluation results clearly demonstrate that a target-specific scoring function
is a promising way to improve prediction power in structure-based drug design compared with other general
scoring functions.