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.

Highlights

  • G-protein coupled receptors (GPCRs) are an important group of membrane proteins that mediate physiological signals from the outside to the inside of cells

  • We present here a new free energy perturbation (FEP) scheme for accurate calculation of the energetics of alanine scanning, which is applied to characterize the binding of antagonists to the human neuropeptide Y (NPY) receptor type 1 GPCR

  • Both automated docking with Glide [22] and mutagenesis-guided docking of BIBP3226 into the hY1 model were carried out, and the resulting complexes were subject to a final round of molecular dynamics (MD) equilibration using a spherical simulation system using the program Q [23], which allows for very efficient FEP calculations [6]

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Summary

Introduction

G-protein coupled receptors (GPCRs) are an important group of membrane proteins that mediate physiological signals from the outside to the inside of cells They are targets for approximately 30% of all prescribed drugs and of major interest to the pharmaceutical industry [1]. The field has benefitted enormously from breakthroughs in membrane protein crystallography, with a steadily increasing number of GPCR crystal structures determined since 2007 [3]. These structures enable structure-based drug design for crystallized targets and make modelling of homologous GPCRs for the same purpose feasible [4]. Computational modelling is of optimal use in combination with site-directed mutagenesis data and structureactivity relationships for series of ligands [5], but requires careful validation

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