Using collections of structural models to predict changes of binding affinity caused by mutations in protein–protein interactions

Alberto Meseguer, Lluis Dominguez, Patricia M. Bota, Joaquim Aguirre-Plans, Jaume Bonet, Narcis Fernandez-Fuentes, Baldo Oliva*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (SciVal)

Abstract

Protein–protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state-of-the-art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state-of-art methods.

Original languageEnglish
Pages (from-to)2112-2130
Number of pages19
JournalProtein Science
Volume29
Issue number10
Early online date05 Sept 2020
DOIs
Publication statusPublished - 01 Oct 2020

Keywords

  • prediction of binding affinity
  • protein interaction comparative modeling
  • protein–protein binding affinity
  • protein–protein interactions
  • Models, Structural
  • Models, Chemical
  • Computational Biology
  • Protein Interaction Mapping
  • Proteins
  • Databases, Protein
  • Protein Binding
  • Software
  • Mutation

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