The Study Of Protein-Protein Interactions And The Prediction Methods Of Their Interacting Sites

The success of Human Genome Project resulted in a lot of genes found and located, and brought the study of biology from "genomics" era into "post- genomics" era. At the same time, the result also transferred the life sciences' study to the whole investigation of biological functions. Proteomics developed by centering on the study of protein-protein interaction is a challenging field which focuses on investigating the protein compositions and theirs activity rules in whole cell level. Usually, the functions of proteins behave themselves as the interactions with other proteins and biomacromolecules. The studies of protein-protein interactions will facilitate the analysis of protein functions, the understanding of life activities and pharmaceutical design. Nevertheless, the investigation of protein-protein interactions has been developed very slowly. Only over the past few years, however, do a vast amount of protein data and the associated data, which are benefited from rapid development of high-throughput biotechnology, make it possible to investigate the interactions between proteins in a systemic level. But, such techniques are tedious, time-consuming and labor-intensive, and suffer from high rates of both false positive and false negative predictions. Therefore, this study seeks some computational approaches to predict protein-protein interactions, and focuses on the prediction of protein interactions and interacting sites. The main works in this thesis can be introduced as follows:1) A novel method of predicting protein-protein interaction sites was proposed in this thesis based on amino acid evolutionary conservation. Under the works of natural selection, amino acid residues that are involved in the function of a given protein family are more conservative. The interaction between proteins and environments depends on these important residues. Based on multiple sequence alignment, we use three features, i.e., protein residue spatial sequence profile, sequence information entropy and evolution rate, to describe the evolutionary conservation. We...