Determining the minimum number of protein-protein interactions required to support known protein complexes

Natsu Nakajima; Morihiro Hayashida; Jesper Jansson; Osamu Maruyama; Tatsuya Akutsu

doi:10.1371/journal.pone.0195545

Determining the minimum number of protein-protein interactions required to support known protein complexes

PLoS One. 2018 Apr 26;13(4):e0195545. doi: 10.1371/journal.pone.0195545. eCollection 2018.

Authors

Natsu Nakajima¹, Morihiro Hayashida², Jesper Jansson³, Osamu Maruyama⁴, Tatsuya Akutsu⁵

Affiliations

¹ Institute of Molecular and Cellular Biosciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan.
² Department of Electrical Engineering and Computer Science, National Institute of Technology, Matsue College, 14-4, Nishiikumacho, Matsue, Shimane 690-8518, Japan.
³ Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
⁴ Institute of Mathematics for Industry, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan.
⁵ Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.

Abstract

The prediction of protein complexes from protein-protein interactions (PPIs) is a well-studied problem in bioinformatics. However, the currently available PPI data is not enough to describe all known protein complexes. In this paper, we express the problem of determining the minimum number of (additional) required protein-protein interactions as a graph theoretic problem under the constraint that each complex constitutes a connected component in a PPI network. For this problem, we develop two computational methods: one is based on integer linear programming (ILPMinPPI) and the other one is based on an existing greedy-type approximation algorithm (GreedyMinPPI) originally developed in the context of communication and social networks. Since the former method is only applicable to datasets of small size, we apply the latter method to a combination of the CYC2008 protein complex dataset and each of eight PPI datasets (STRING, MINT, BioGRID, IntAct, DIP, BIND, WI-PHI, iRefIndex). The results show that the minimum number of additional required PPIs ranges from 51 (STRING) to 964 (BIND), and that even the four best PPI databases, STRING (51), BioGRID (67), WI-PHI (93) and iRefIndex (85), do not include enough PPIs to form all CYC2008 protein complexes. We also demonstrate that the proposed problem framework and our solutions can enhance the prediction accuracy of existing PPI prediction methods. ILPMinPPI can be freely downloaded from http://sunflower.kuicr.kyoto-u.ac.jp/~nakajima/.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Computational Biology
Computer Simulation
Protein Interaction Mapping / methods*
Proteins / chemistry*
Proteins / metabolism*

Substances

Proteins

Associated data

Dryad/10.5061/dryad.8s3682g

Grants and funding

T. Akutsu was partially supported by JSPS, Japan, (Grants-in-Aid 26240034). M. Hayashida was partially supported by JSPS, Japan (Grants-in-Aid 16K00392). J. Jansson was partially supported by the Hakubi Project at Kyoto University, Japan. O. Maruyama was partially supported by JSPS KAKENHI Grant Number 26330330.