An integrated machine learning system to computationally screen protein databases for protein binding peptide ligands.
A fairly large set of protein interactions is mediated by families of peptide binding domains, such as Src homology 2 (SH2), SH3, PDZ, major histocompatibility complex, etc. To identify their ligands by experimental screening is not only labor-intensive but almost futile in screening low abundance species due to the suppression by high abundance species. An ideal way of studying protein-protein interactions is to use high throughput computational approaches to screen protein sequence databases to direct the validating experiments toward the most promising peptides. Predictors with only good cross-validation were not good enough to screen protein databases. In the current study we built integrated machine learning systems using three novel coding methods and screened the Swiss-Prot and GenBank protein databases for potential ligands of 10 SH3 and three PDZ domains. A large fraction of predictions has already been experimentally confirmed by other independent research groups, indicating a satisfying generalization capability for future applications in identifying protein interactions.
Zhang
Ling
L
Proteomics Research Center, National Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences/Peking Union Medical College, 5 Dong Dan San Tiao, 100005 Beijing, China.
Shao
Chen
C
Zheng
Dexian
D
Gao
Youhe
Y
D020816:Amino Acid Motifs; D001185:Artificial Intelligence; D030562:Databases, Protein; D001330:Electronic Data Processing / Q000379:methods*; D005544:Forecasting; D006801:Humans; D008024:Ligands; D008962:Models, Theoretical; D010446:Peptide Fragments / Q000032:analysis* / Q000378:metabolism; D011237:Predictive Value of Tests; D040081:Protein Array Analysis / Q000706:statistics & numerical data; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D017434:Protein Structure, Tertiary; D015003:Yeasts
D008024:Ligands; D010446:Peptide Fragments