A method for localizing ligand binding pockets in protein structures.
The accurate identification of ligand binding sites in protein structures can be valuable in determining protein function. Once the binding site is known, it becomes easier to perform in silico and experimental procedures that may allow the ligand type and the protein function to be determined. For example, binding pocket shape analysis relies heavily on the correct localization of the ligand binding site. We have developed SURFNET-ConSurf, a modular, two-stage method for identifying the location and shape of potential ligand binding pockets in protein structures. In the first stage, the SURFNET program identifies clefts in the protein surface that are potential binding sites. In the second stage, these clefts are trimmed in size by cutting away regions distant from highly conserved residues, as defined by the ConSurf-HSSP database. The largest clefts that remain tend to be those where ligands bind. To test the approach, we analyzed a nonredundant set of 244 protein structures from the PDB and found that SURFNET-ConSurf identifies a ligand binding pocket in 75% of them. The trimming procedure reduces the original cleft volumes by 30% on average, while still encompassing an average 87% of the ligand volume. From the analysis of the results we conclude that for those cases in which the ligands are found in large, highly conserved clefts, the combined SURFNET-ConSurf method gives pockets that are a better match to the ligand shape and location. We also show that this approach works better for enzymes than for nonenzyme proteins.
Glaser
Fabian
F
European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom. fabian@ebi.ac.uk
Morris
Richard J
RJ
Najmanovich
Rafael J
RJ
Laskowski
Roman A
RA
Thornton
Janet M
JM
D000465:Algorithms; D000595:Amino Acid Sequence; D001665:Binding Sites; D030562:Databases, Protein; D008024:Ligands; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software
D008024:Ligands; D011506:Proteins