Pattern recognition strategies for molecular surfaces: III. Binding site prediction with a neural network.
An algorithm for the identification of possible binding sites of biomolecules, which are represented as regions of the molecular surface, is introduced. The algorithm is based on the segmentation of the molecular surface into overlapping patches as described in the first article of this series.1 The properties of these patches (calculated on the basis of physical and chemical properties) are used for the analysis of the molecular surfaces of 7821 proteins and protein complexes. Special attention is drawn to known protein binding sites. A binding site identification algorithm is realized on the basis of the calculated data using a neural network strategy. The neural network is able to classify surface patches as protein-protein, protein-DNA, protein-ligand, or nonbinding sites. To show the capability of the algorithm, results of the surface analysis and the predictions are presented and discussed with representative examples.
Keil
Matthias
M
Department of Physical Chemistry, Darmstadt University of Technology, 64287 Darmstadt, Germany.
Exner
Thomas E
TE
Brickmann
Jürgen
J
D000465:Algorithms; D004247:DNA / Q000737:chemistry*; D008958:Models, Molecular; D016571:Neural Networks, Computer; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
D011506:Proteins; D004247:DNA