Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis

By Thomas Gueudré, Carlo Baldassi, M. Zamparo, Martin Weigt, Andrea Pagnani. 2016

117 citations recorded by the source corpus.

Significance Most biological processes rely on specific interactions between proteins, but the experimental characterization of protein−protein interactions is a labor-intensive task of frequently uncertain outcome. Computational methods based on exponentially growing genomic databases are urgently needed. It has recently been shown that coevolutionary methods are able to detect correlated mutations between residues in different proteins, which are in contact across the interaction interface, thus enabling the structure prediction of protein complexes. Here we show that the applicability of coevolutionary methods is much broader, connecting multiple scales relevant in protein−protein interaction: the residue scale of interprotein contacts, the protein scale of specific interactions between paralogous proteins, and the evolutionary scale of conserved interactions between homologous protein families. Understanding protein−protein interactions is central to our understanding of almost all complex biological processes. Computational tools exploiting rapidly growing genomic databases to characterize protein−protein interactions are urgently needed. Such methods should connect multiple scales from evolutionary conserved interactions between families of homologous proteins, over the identification of specifically interacting proteins in the case of multiple paralogs inside a species, down to the prediction of residues being in physical contact across interaction interfaces. Statistical inference methods detecting residue−residue coevolution have recently triggered considerable progress in using sequence data for quaternary protein structure prediction; they require, however, large joint alignments of homologous protein pairs known to interact. The generation of such alignments is a complex computational task on its own; application of coevolutionary modeling has, in turn, been restricted to proteins without paralogs, or to bacterial systems with the corresponding coding genes being colocalized in operons. Here we show that the direct coupling analysis of residue coevolution can be extended to connect the different scales, and simultaneously to match interacting paralogs, to identify interprotein residue−residue contacts and to discriminate interacting from noninteracting families in a multiprotein system. Our results extend the potential applications of coevolutionary analysis far beyond cases treatable so far.

Subfields: Molecular Biology

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In Molecular Biology

1. Sheng Wang
2. Jinbo Xu
3. Anne-Florence Bitbol
4. Tian-Ming Zhou
5. Qing Wu
6. Feifeng Zhao
7. Xiufeng Li
8. Hong Zeng

Citations in the corpus

• Revealing evolutionary constraints on proteins through sequence analysis (2018, methodology): “More generally, such one- and two-body descriptions have been very successfully employed via Direct Coupling Analysis (DCA) to identify strongly coupled residues that are in contact within a folded protein [36–38], to investigate folding [39], and to predict fitness [33, 40–45] and conformational ch”
• ComplexContact: a web server for inter-protein contact prediction using deep learning (2018, background): “In most eukaryotes, it is challenging to concatenate two individual MSAs since an individual MSA may contain abundant paralogs and two genes may interact even if they are not close by genomic distance (13).”
• Inferring interaction partners from protein sequences using mutual information (2018, methodology): “In contrast to the previ- 30 ous pairwise maximum entropy-based approaches [16, 17], the present method is based on an 31 approximate maximization of mutual information between the sequences from the two protein 32 families.”