Title :
Prediction of Protein-Protein Interactions from Secondary Structures in Binding Motifs Using the Statistic Method
Author :
Yu, Jian-Tao ; Guo, Mao-zu
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin
Abstract :
Protein-protein interactions and their full network are crucial to understand biological function and disease occurrence. In respect of involvement of binding motifs and specific secondary structures in protein-protein interactions, we applied a statistical method to explore the frequency with which helices, sheets and disordered secondary structures appeared on protein-protein binding motif regions and tried to predict protein-protein interactions taking this frequency as a threshold. The results have shown that i ) on the average, helices and disordered structures constitute most of the binding regions (about 92%). ii ) for individual binding motif, the ratio may not be as significant as that in general cases. However, it is still greatly higher than that in random condition. This conclusion will be beneficial to protein-protein interaction prediction from a new orientation, secondary structures, instead of traditional ways of amino acid sequences and three-dimensional protein structures.
Keywords :
biology computing; learning (artificial intelligence); macromolecules; molecular configurations; proteins; statistical analysis; amino acid sequences; binding motifs; disease occurrence; protein-protein interactions prediction; secondary structures; statistic method; three-dimensional protein structures; Amino acids; Biology computing; Computer networks; Computer science; Diseases; Frequency; Nuclear magnetic resonance; Proteins; Statistical analysis; Statistics; binding motif; protein-protein interaction; secondary structure prediction; statistic method;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.451