Development of an affinity evaluation and prediction system by using the shape complementarity characteristic between proteins.
A system was developed to evaluate and predict the interaction between protein pairs by using the widely used shape complementarity search method as the algorithm for docking simulations between the proteins. This system, which we call the affinity evaluation and prediction (AEP) system, was used to evaluate the interaction between 20 protein pairs. The system first executes a "round robin" shape complementarity search of the target protein group, and evaluates the interaction of the complex structures obtained by shape complementarity search. These complex structures are selected by using a statistical procedure that we developed called "grouping". At a low prevalence of 5.0%, our AEP system predicted protein-protein interaction with 65.0% recall, 15.1% precision, 80.0% accuracy, and had an area under the curve (AUC) of 0.74. By optimizing the grouping process, our AEP system successfully predicted 13 protein pairs (among 20 pairs) that were biologically significant combinations. Our ultimate goal is to construct an affinity database that will provide crucial information obtained using our AEP system to cell biologists and drug designers.
Tsukamoto
Koki
K
Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan. k-tsukamoto@aist.go.jp
Yoshikawa
Tatsuya
T
Hourai
Yuichiro
Y
Fukui
Kazuhiko
K
Akiyama
Yutaka
Y
D000465:Algorithms; D019295:Computational Biology; D008958:Models, Molecular; D015394:Molecular Structure; D011487:Protein Conformation; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping / Q000706:statistics & numerical data; D011506:Proteins / Q000737:chemistry*
D011506:Proteins