Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology.

Journal: The protein journal
Published Date:

Abstract

Protein-protein interactions (PPIs) involve the physical or functional contact between two or more proteins. Generally, proteins that can interact with each other always have special relationships. Some previous studies have reported that gene ontology (GO) terms are related to the determination of PPIs, suggesting the special patterns on the GO terms of proteins in PPIs. In this study, we explored the special GO term patterns on human PPIs, trying to uncover the underlying functional mechanism of PPIs. The experimental validated human PPIs were retrieved from STRING database, which were termed as positive samples. Additionally, we randomly paired proteins occurring in positive samples, yielding lots of negative samples. A simple calculation was conducted to count the number of positive samples for each GO term pair, where proteins in samples were annotated by GO terms in the pair individually. The similar number for negative samples was also counted and further adjusted due to the great gap between the numbers of positive and negative samples. The difference of the above two numbers and the relative ratio compared with the number on positive samples were calculated. This ratio provided a precise evaluation of the occurrence of GO term pairs for positive samples and negative samples, indicating the latent GO term patterns for PPIs. Our analysis unveiled several nuclear biological processes, including gene transcription, cell proliferation, and nutrient metabolism, as key biological functions. Interactions between major proliferative or metabolic GO terms consistently correspond with significantly reported PPIs in recent literature.

Authors

  • Yu-Hang Zhang
    Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • FeiMing Huang
    School of Life Sciences, Shanghai University, Shanghai 200444, China.
  • JiaBo Li
    School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, People's Republic of China.
  • WenFeng Shen
    School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, People's Republic of China.
  • Lei Chen
    Department of Chemistry, Stony Brook University Stony Brook NY USA.
  • KaiYan Feng
    Department of Computer Science, Guangdong AIB Polytechnic, Guangzhou, 510507, P. R. China.
  • Tao Huang
    The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Yu-Dong Cai
    College of Life Science, Shanghai University, Shanghai, People's Republic of China.