Two Challenging Difficulties of Protein Complex Prediction
- 312 Downloads
A protein complex is a group of proteins which carries out particular functions in the cell. The component proteins of a protein complex are connected via weak physical contacts, called protein–protein interactions (PPIs). Proteome-wide PPIs are determined by high-throughput assays. Thus, it is interesting to computationally predict protein complexes from such PPIs. In this paper, we describe two challenging difficulties of the problem. The first difficulty is that the smallest protein complexes are of size two. It is quite difficult to predict them due to their simple inherent structure. The second difficulty is that some known complexes are overlapped with each other, because it is not trivial how to model such overlaps mathematically. For these issues, we have proposed our own approaches. In both methods, we design a scoring function and algorithms based on Markov chain Monte Carlo to optimize the scoring function. In this article, we briefly show our key regularization terms included in the whole scoring function.
KeywordsProtein complex Protein–protein interaction Markov chain Monte Carlo
This work was partially supported by JSPS KAKENHI Grant Number 26330330.
- 1.C.K. Widita, O. Maruyama, PPSampler2: predicting protein complexes more accurately and efficiently by sampling. BMC Syst. Biol. 7(Suppl 6), S14 (2013)Google Scholar
- 2.O. Maruyama, Y. Kuwahara, Rocsampler: regularizing overlapping protein complexes in protein-protein interaction networks, in Proceeding of 2016 IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS) (IEEE, 2016). (The full version of this work is sumitted to a journal)Google Scholar