A　major　challenge　in　the　field　of　protein-protein　docking　is　to　discriminate　between　the　many　wrong　and　few　near-native　conformations,　i.e.　scoring.　Here,　we　introduce　combinatorial　complex-type-dependent　scoring　functions　for　different　types　of　protein-protein　complexes,　protease/　inhibitor,　antibody/antigen,　enzyme/inhibitor　and　others.　The　scoring　functions　incorporate　both　physical　and　knowledge-based　potentials,　i.e.　atomic　contact　energy　(ACE),　the　residue　pair　potential　(RP),　electrostatic　and　van　der　Waals＇　interactions.　For　different　type　complexes,　the　weights　of　the　scoring　functions　were　optimized　by　the　multiple　linear　regression　method,　in　which　only　top　300　structures　with　ligand　root　mean　square　deviation　(L_RMSD)　less　than　20　angstrom　from　the　bound　(co-crystallized)　docking　of　57　complexes　were　used　to　construct　a　training　set.　We　employed　the　bound　docking　studies　to　examine　the　quality　of　the　scoring　function,　and　also　extend　to　the　unbound　(separately　crystallized)　docking　studies　and　extra　8　protein-protein　complexes.　In　bound　docking　of　the　57　cases,　the　first　hits　of　protease/inhibitor　cases　are　all　ranked　in　the　top　5.　For　the　cases　of　antibody/antigen,　enzyme/inhibitor　and　others,　there　are　17/19,　5/6　and　13/15　cases　with　the　first　hits　ranked　in　the　top　10,　respectively.　In　unbound　docking　studies,　the　first　hits　of　9/17　protease/inhibitor,　6/19　antibody/antigen,　1/6　enzyme/inhibitor　and　6/15　others＇　complexes　are　ranked　in　the　top　10.　Additionally,　for　the　extra　8　cases,　the　first　hits　of　the　two　protease/inhibitor　cases　are　ranked　in　the　top　for　the　bound　and　unbound　test.　For　the　two　enzyme/inhibitor　cases,　the　first　hits　are　ranked　1st　for　bound　test,　and　the　119th　and　17th　for　the　unbound　test.　For　the　others,　the　ranks　of　the　first　hits　are　the　1st　for　the　bound　test　and　the　12th　for　the　1WQ1　unbound　test.　To　some　extent,　the　results　validated　our　divide-and-conquer　strategy　in　the　docking　study,　which　might　hopefully　shed　light　on　the　prediction　of　protein-protein　interactions.　(c)　2007　Elsevier　B.　V.　All　rights　reserved.