title: Sequence specificity between interacting and non-interacting homologs identifies interface residues--a homodimer and monomer use case.
abstract: BACKGROUND
  Protein families participating in protein-protein interactions may contain sub-families that have different binding characteristics, ranging from right binding to showing no interaction at all. Composition differences at the sequence level in these sub-families are often decisive to their differential functional interaction. Methods to predict interface sites from protein sequences typically exploit conservation as a signal. Here, instead, we provide proof of concept that the sequence specificity between interacting versus non-interacting groups can be exploited to recognise interaction sites.
  
  
  RESULTS
  We collected homodimeric and monomeric proteins and formed homologous groups, each having an interacting (homodimer) subgroup and a non-interacting (monomer) subgroup. We then compiled multiple sequence alignments of the proteins in the homologous groups and identified compositional differences between the homodimeric and monomeric subgroups for each of the alignment positions. Our results show that this specificity signal distinguishes interface and other surface residues with 40.9% recall and up to 25.1% precision.
  
  
  CONCLUSIONS
  To our best knowledge, this is the first large scale study that exploits sequence specificity between interacting and non-interacting homologs to predict interaction sites from sequence information only. The performance obtained indicates that this signal contains valuable information to identify protein-protein interaction sites.
authors.affiliation: Center for Integrative Bioinformatics VU (IBIVU), Vrije University Amsterdam, De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands. q.hou@vu.nl.
authors.forename: Qingzhen
authors.initials: Q
authors.lastname: Hou
authors.affiliation: Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands. bedutilh@gmail.com.|Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 28, 6525 GA, Nijmegen, The Netherlands. bedutilh@gmail.com.|Department of Marine Biology, Institute of Biology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. bedutilh@gmail.com.
authors.forename: Bas E
authors.initials: BE
authors.lastname: Dutilh
authors.affiliation: Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 28, 6525 GA, Nijmegen, The Netherlands. m.huynen@cmbi.ru.nl.
authors.forename: Martijn A
authors.initials: MA
authors.lastname: Huynen
authors.affiliation: Center for Integrative Bioinformatics VU (IBIVU), Vrije University Amsterdam, De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands. j.heringa@vu.nl.
authors.forename: Jaap
authors.initials: J
authors.lastname: Heringa
authors.affiliation: Center for Integrative Bioinformatics VU (IBIVU), Vrije University Amsterdam, De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands. k.a.feenstra@vu.nl.
authors.forename: K Anton
authors.initials: KA
authors.lastname: Feenstra
mesh_terms: D019540:Area Under Curve; D019281:Dimerization; D054730:Protein Interaction Domains and Motifs; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D012372:ROC Curve
chemical_list: D011506:Proteins