Protein docking combining symbolic descriptions of molecular surfaces and grid-based scoring functions.

With the growing number of known 3D protein structures, computing systems, that can predict where two protein molecules interact with each other is becoming of increasing interest. A system is presented, integrating preprocessing like the computation of molecular surfaces, segmentation, and searching for complementarity in the general framework of a pattern analyzing semantic network (ERNEST). The score of coarse symbolic computations is used by the problem independent control strategy of ERNEST to guide a more detailed analysis considering steric clash and judgements based on grid-based surface representations. Successful examples of the docking system are discussed that compare well with other approaches.