Loop prediction for a GPCR homology model: Algorithms and results
- 29 September 2012
- journal article
- research article
- Published by Wiley in Proteins: Structure, Function, and Bioinformatics
- Vol. 81 (2), 214-228
- https://doi.org/10.1002/prot.24178
Abstract
We present loop structure prediction results of the intracellular and extracellular loops of four G-protein-coupled receptors (GPCRs): bovine rhodopsin (bRh), the turkey β1-adrenergic (β1Ar), the human β2-adrenergic (β2Ar) and the human A2a adenosine receptor (A2Ar) in perturbed environments. We used the protein local optimization program, which builds thousands of loop candidates by sampling rotamer states of the loops' constituent amino acids. The candidate loops are discriminated between with our physics-based, all-atom energy function, which is based on the OPLS force field with implicit solvent and several correction terms. For relevant cases, explicit membrane molecules are included to simulate the effect of the membrane on loop structure. We also discuss a new sampling algorithm that divides phase space into different regions, allowing more thorough sampling of long loops that greatly improves results. In the first half of the paper, loop prediction is done with the GPCRs' transmembrane domains fixed in their crystallographic positions, while the loops are built one-by-one. Side chains near the loops are also in non-native conformations. The second half describes a full homology model of β2Ar using β1Ar as a template. No information about the crystal structure of β2Ar was used to build this homology model. We are able to capture the architecture of short loops and the very long second extracellular loop, which is key for ligand binding. We believe this the first successful example of an RMSD validated, physics-based loop prediction in the context of a GPCR homology model.Keywords
Funding Information
- National Science Foundation Graduate Research Fellowship (DGE-07-07425)
This publication has 38 references indexed in Scilit:
- Update 1 of: Computational Modeling Approaches to Structure–Function Analysis of G Protein-Coupled ReceptorsChemical Reviews, 2011
- G protein-coupled receptors: novel targets for drug discovery in cancerNature Reviews Drug Discovery, 2010
- Homology Modeling of GPCRsMethods in molecular biology (Clifton, N.J.), 2009
- Computational modeling of protein mutant stability: analysis and optimization of statistical potentials and structural features reveal insights into prediction model developmentBMC Structural Biology, 2007
- CUPSAT: prediction of protein stability upon point mutationsNucleic Acids Research, 2006
- Computational methods in drug design: Modeling G protein-coupled receptor monomers, dimers, and oligomersThe AAPS Journal, 2006
- Molecular mechanisms of ligand binding, signaling, and regulation within the superfamily of G-protein-coupled receptors: molecular modeling and mutagenesis approaches to receptor structure and functionPharmacology & Therapeutics, 2004
- A hierarchical approach to all‐atom protein loop predictionProteins, 2004
- Computer Modeling of Protein Folding: Conformational and Energetic Analysis of Reduced and Detailed Protein ModelsJournal of Molecular Biology, 1995
- Database of homology‐derived protein structures and the structural meaning of sequence alignmentProteins, 1991