PoPS: a computational tool for modeling and predicting protease specificity.
Proteases play a fundamental role in the control of intra- and extra-cellular processes by binding and cleaving specific amino acid sequences. Identifying these targets is extremely challenging. Current computational attempts to predict cleavage sites are limited, representing these amino acid sequences as patterns or frequency matrices. Here we present PoPS, a publicly accessible bioinformatics tool (http://pops.csse.monash.edu.au/) that provides a novel method for building computational models of protease specificity, which while still being based on these amino acid sequences, can be built from any experimental data or expert knowledge available to the user. PoPS specificity models can be used to predict and rank likely cleavages within a single substrate, and within entire proteomes. Other factors, such as the secondary or tertiary structure of the substrate, can be used to screen unlikely sites. Furthermore, the tool also provides facilities to infer, compare and test models, and to store them in a publicly accessible database.
Boyd
Sarah E
SE
School of Computer Science & Software Engineering and The Victorian Bioinformatics, Consortium, Monash University, Melbourne, Victoria 3800, Australia. sarah.boyd@infotech.monash.edu.au
Pike
Robert N
RN
Rudy
George B
GB
Whisstock
James C
JC
Garcia de la Banda
Maria
M
D000465:Algorithms; D001185:Artificial Intelligence; D001665:Binding Sites; D003198:Computer Simulation; D004789:Enzyme Activation; D008956:Models, Chemical; D008958:Models, Molecular; D010447:Peptide Hydrolases / Q000032:analysis / Q000737:chemistry* / Q000145:classification; D011485:Protein Binding; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D013329:Structure-Activity Relationship; D013379:Substrate Specificity
D010447:Peptide Hydrolases