Borja Pitarch1, Juan A G Ranea2,3,4, Florencio Pazos1. 1. Computational Systems Biology Group, Systems Biology Department, National Centre for Biotechnology (CNB-CSIC), 28049 Madrid, Spain. 2. Department of Molecular Biology and Biochemistry, University of Malaga, Malaga 29071, Spain. 3. CIBER de Enfermedades Raras, Instituto de Salud Carlos III, Madrid, Spain. 4. Institute of Biomedical Research in Malaga (IBIMA), Malaga, Spain.
Abstract
MOTIVATION: Predicting the residues controlling a protein's interaction specificity is important not only to better understand its interactions but also to design mutations aimed at fine-tuning or swapping them as well. RESULTS: In this work, we present a methodology that combines sequence information (in the form of multiple sequence alignments) with interactome information to detect that kind of residues in paralogous families of proteins. The interactome is used to define pairwise similarities of interaction contexts for the proteins in the alignment. The method looks for alignment positions with patterns of amino-acid changes reflecting the similarities/differences in the interaction neighborhoods of the corresponding proteins. We tested this new methodology in a large set of human paralogous families with structurally characterized interactions, and discuss in detail the results for the RasH family. We show that this approach is a better predictor of interfacial residues than both, sequence conservation and an equivalent 'unsupervised' method that does not use interactome information. AVAILABILITY AND IMPLEMENTATION: http://csbg.cnb.csic.es/pazos/Xdet/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Predicting the residues controlling a protein's interaction specificity is important not only to better understand its interactions but also to design mutations aimed at fine-tuning or swapping them as well. RESULTS: In this work, we present a methodology that combines sequence information (in the form of multiple sequence alignments) with interactome information to detect that kind of residues in paralogous families of proteins. The interactome is used to define pairwise similarities of interaction contexts for the proteins in the alignment. The method looks for alignment positions with patterns of amino-acid changes reflecting the similarities/differences in the interaction neighborhoods of the corresponding proteins. We tested this new methodology in a large set of human paralogous families with structurally characterized interactions, and discuss in detail the results for the RasH family. We show that this approach is a better predictor of interfacial residues than both, sequence conservation and an equivalent 'unsupervised' method that does not use interactome information. AVAILABILITY AND IMPLEMENTATION: http://csbg.cnb.csic.es/pazos/Xdet/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Braelyn M Page; Tyler A Martin; Collette L Wright; Lauren A Fenton; Maite T Villar; Qingling Tang; Antonio Artigues; Audrey Lamb; Aron W Fenton; Liskin Swint-Kruse Journal: Protein Sci Date: 2022-07 Impact factor: 6.993