Computational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptors

PLoS Comput Biol. 2014 Apr 17;10(4):e1003585. doi: 10.1371/journal.pcbi.1003585. eCollection 2014 Apr.

Abstract

Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking. Here, we report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 receptor and series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alanine / metabolism*
  • Computational Biology*
  • Ligands
  • Models, Molecular
  • Protein Binding
  • Receptors, G-Protein-Coupled / chemistry
  • Receptors, G-Protein-Coupled / metabolism*

Substances

  • Ligands
  • Receptors, G-Protein-Coupled
  • Alanine

Grants and funding

Support from the Swedish Research Council (VR), the eSSENCE e-science initiative and the Swedish National Infrastructure for Computing (SNIC) is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.