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.
Ackermann
F
F
Bielefeld University, Germany.
Herrmann
G
G
Kummert
F
F
Posch
S
S
Sagerer
G
G
Schomburg
D
D
D001665:Binding Sites; D018360:Crystallography, X-Ray; D016208:Databases, Factual; D010363:Pattern Recognition, Automated; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D012984:Software; D013499:Surface Properties; D014359:Trypsin Inhibitor, Kazal Pancreatic / Q000737:chemistry
D011506:Proteins; D014359:Trypsin Inhibitor, Kazal Pancreatic