Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

ABSTRACT:

Background

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect.

Results

We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting P

SUBMITTER: Jelinek J 

PROVIDER: S-EPMC5731498 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature