Effective labeling of molecular surface points for cavity detection and location of putative binding sites.
We present a method for detecting and comparing cavities on protein surfaces that is useful for protein binding site recognition. The method is based on a representation of the protein structures by a collection of spin-images and their associated spin-image profiles. Results of the cavity detection procedure are presented for a large set of non-redundant proteins and compared with SURFNET-ConSurf. Our comparison method is used to find a surface region in one cavity of a protein that is geometrically similar to a surface region in the cavity of another protein. Such a finding would be an indication that the two regions likely bind to the same ligand. Our overall approach for cavity detection and comparison is benchmarked on several pairs of known complexes, obtaining a good coverage of the atoms of the binding sites.
Bock
Mary Ellen
ME
Department of Statistics, Purdue University 150 N. University Street, West Lafayette, IN 47907-2067, USA. mbock@purdue.edu
Garutti
Claudio
C
Guerra
Conettina
C
D001665:Binding Sites; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013499:Surface Properties
D011506:Proteins