3D-Segmentierungstechniken und vektorwertige Bewertungsfunktionen für symbolisches Protein-Protein-Docking

Abstract

The growing number of known 3D protein structures asks for computing systems predicting whether and where two molecules interact with each other. This requires search for possible docking sites of proteins. Based on results of preprocessing techniques like computation of molecular surfaces and segmentation, a knowledge based control algorithm implemented with the semantic network ERNEST searches for geometrical and chemical complementarity on molecular surfaces, computes coarse docking positions considering steric clash and simple geometric judgement functions. Additionally, ERNEST guides a more detailed analysis of finer calcultations including correlation of geometry and hydrophobicity. The proposed hierarchical system allows to predict completely automatically and in reasonable short computing times possible docking sites for two given proteins. A set of 18 representative examples is discussed.