Discriminative random field approach to prediction of protein residue contacts

Mayumi Kamada, Morihiro Hayashida, Jiangning Song, Tatsuya Akutsu

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3 Citations (Scopus)


Understanding of interactions of proteins is important to reveal networks and functions of molecules. Many investigations have been conducted to analyze interactions and contacts between residues. It is supported that residues at interacting sites have co-evolved with those at the corresponding residues in the partner protein to keep the interactions between the proteins. Therefore, mutual information (MI) between residues calculated from multiple sequence alignments of homologous proteins is considered to be useful for identifying contact residues in interacting proteins. In our previous work, we proposed a prediction method for protein-protein interactions using mutual information and conditional random fields (CRFs), and confirmed its usefulness. The discriminative random field (DRF) is a special type of CRFs, and can recognize some specific characteristic regions in an image. Since the matrix consisted of mutual information between residues in two interacting proteins can be regarded as an image, we propose a prediction method for protein residue contacts using DRF models with mutual information. To validate our method, we perform computational experiments for several interactions between Pfam domains. The results suggest that the proposed DRF-based method with MI is useful for predicting protein residue contacts compared with that using the corresponding Markov random field (MRF) model.
Original languageEnglish
Title of host publication2011 IEEE Conference on Systems Biology (ISB)
EditorsL Chen, X S Zhang, Y Wang
Place of PublicationChina
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages285 - 291
Number of pages7
ISBN (Print)9781457716669
Publication statusPublished - 2011
EventInternational Conference on Computational Systems Biology (ISB) 2011 - Zhuhai, China
Duration: 2 Sept 20114 Sept 2011
Conference number: 5th


ConferenceInternational Conference on Computational Systems Biology (ISB) 2011
Abbreviated titleISB 2011

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