PresCont: predicting protein-protein interfaces utilizing four residue properties.
An important task of computational biology is to identify those parts of a polypeptide chain, which are involved in interactions with other proteins. For this purpose, we have developed the program PresCont, which predicts in a robust manner amino acids that constitute protein-protein interfaces (PPIs). PresCont reaches state-of-the-art classification quality on the basis of only four residue properties that can be readily deduced from the 3D structure of an individual protein and a multiple sequence alignment (MSA) composed of homologs. The core of PresCont is a support vector machine, which assesses solvent-accessible surface area, hydrophobicity, conservation, and the local environment of each amino acid on the protein surface. For training and performance testing, we compiled three nonoverlapping datasets consisting of permanently formed or transient complexes, respectively. A comparison with SPPIDER, ProMate, and meta-PPISP showed that PresCont compares favorably with these highly sophisticated programs, and that its prediction quality is less dependent on the type of protein complex being considered. This balance is due to a mutual compensation of classification weaknesses observed for individual properties: For PPIs of permanent complexes, solvent-accessible surface and hydrophobicity contribute most to classification quality, for PPIs of transient complexes, the assessment of the local environment is most significant. Moreover, we show that for permanent complexes a segmentation of PPIs into core and rim residues has only a moderate influence on prediction quality. PresCont is available as a web service at http://www-bioinf.uni-regensburg.de/.
Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany.
Hermann
H
Zellner
Martin
M
Staudigel
Thomas
T
Trenner
Meik
M
Bittkowski
Vincent
V
Wolowski
Christian
C
Icking
Rainer
R
Merkl
D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D017124:Conserved Sequence; D005656:Fungal Proteins / Q000737:chemistry; D057927:Hydrophobic and Hydrophilic Interactions; D008958:Models, Molecular; D046912:Multiprotein Complexes / Q000737:chemistry; D054730:Protein Interaction Domains and Motifs; D012372:ROC Curve; D016415:Sequence Alignment; D012984:Software; D060388:Support Vector Machine; D013499:Surface Properties; D015003:Yeasts; D012359:tRNA Methyltransferases / Q000737:chemistry
D005656:Fungal Proteins; D046912:Multiprotein Complexes; D012359:tRNA Methyltransferases; C036814:tRNA (guanine-N7-)-methyltransferase