Elastic network model of learned maintained contacts to predict protein motion

PLoS One. 2017 Aug 30;12(8):e0183889. doi: 10.1371/journal.pone.0183889. eCollection 2017.

Abstract

We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology remains unchanged throughout the motion and are thus most appropriate to simulate highly collective function-related movements. lmcENM uses machine learning to differentiate breaking from maintained contacts. We show that lmcENM accurately captures functional transitions unexplained by the classical ENM and three reference ENM variants, while preserving the simplicity of classical ENM. We demonstrate the effectiveness of our approach on a large set of proteins covering different motion types. Our results suggest that accurately predicting a "deformation-invariant" contact topology offers a promising route to increase the general applicability of ENMs. We also find that to correctly predict this contact topology a combination of several features seems to be relevant which may vary slightly depending on the protein. Additionally, we present case studies of two biologically interesting systems, Ferric Citrate membrane transporter FecA and Arachidonate 15-Lipoxygenase.

MeSH terms

  • Animals
  • Arachidonate 15-Lipoxygenase / chemistry
  • Elasticity
  • Humans
  • Machine Learning*
  • Models, Molecular
  • Motion*
  • Protein Conformation
  • Proteins / chemistry*

Substances

  • Proteins
  • Arachidonate 15-Lipoxygenase

Grants and funding

This work was supported by the Alexander von Humboldt Foundation through an Alexander von Humboldt professorship awarded to Prof. Oliver Brock, http://www.humboldt-foundation.de/web/start.html (funded by the German Federal Ministry of Education and Research). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.