Loop prediction for a GPCR homology model: algorithms and results.

Area of Science:

• Structural Biology
• Computational Chemistry
• Pharmacology

Background:

• G-protein-coupled receptors (GPCRs) are crucial membrane proteins involved in numerous cellular signaling pathways.
• Accurate prediction of GPCR loop structures, particularly extracellular loops, is essential for understanding ligand binding and drug design.
• Previous methods struggled with accurate loop structure prediction in complex, perturbed environments.

Purpose of the Study:

• To present a novel physics-based computational method for predicting the structure of intracellular and extracellular loops in four different GPCRs.
• To validate the method's accuracy by comparing predictions with known structures and assessing its performance in homology modeling.

Main Methods:

• Utilized the protein local optimization program (PLOP) to generate thousands of loop structure candidates by sampling amino acid rotamer states.
• Employed a physics-based, all-atom energy function (OPLS force field with implicit solvent and corrections) for discriminating candidate loops.
• Incorporated explicit membrane molecules for relevant simulations and introduced a new sampling algorithm to improve exploration of conformational space, especially for long loops.

Main Results:

• Successfully predicted loop structures for bovine rhodopsin, turkey β1-adrenergic receptor, human β2-adrenergic receptor, and human A2a adenosine receptor.
• Captured the architecture of both short loops and the critical, long second extracellular loop, which is vital for ligand interactions.
• Demonstrated the first successful example of RMSD-validated, physics-based loop prediction within a GPCR homology model (β2Ar using β1Ar template).

Conclusions:

• The developed physics-based approach enables accurate prediction of GPCR loop structures, even in perturbed environments.
• This method holds significant potential for advancing GPCR research, drug discovery, and the development of novel therapeutics targeting these important receptors.