Predicted structures of agonist and antagonist bound complexes of adenosine A_3 receptor
Abstract
We used the GEnSeMBLE Monte Carlo method to predict ensemble of the 20 best packings (helix rotations and tilts) based on the neutral total energy (E) from a vast number (10 trillion) of potential packings for each of the four subtypes of the adenosine G protein-coupled receptors (GPCRs), which are involved in many cytoprotective functions. We then used the DarwinDock Monte Carlo methods to predict the binding pose for the human A_3 adenosine receptor (hAA_3R) for subtype selective agonists and antagonists. We found that all four A_3 agonists stabilize the 15th lowest conformation of apo-hAA_3R while also binding strongly to the 1st and 3rd. In contrast the four A_3 antagonists stabilize the 2nd or 3rd lowest conformation. These results show that different ligands can stabilize different GPCR conformations, which will likely affect function, complicating the design of functionally unique ligands. Interestingly all agonists lead to a trans χ1 angle for W6.48 that experiments on other GPCRs associate with G-protein activation while all 20 apo-AA_3R conformations have a W6.48 gauche+ χ1 angle associated experimentally with inactive GPCRs for other systems. Thus docking calculations have identified critical ligand-GPCR structures involved with activation. We found that the predicted binding site for selective agonist Cl-IB-MECA to the predicted structure of hAA_3R shows favorable interactions to three subtype variable residues, I253^(6.58), V169^(EL2), and Q167^(EL2), while the predicted structure for hAA_(2A)R shows weakened to the corresponding amino acids: T256^(6.58), E169^(EL2), and L167^(EL2), explaining the observed subtype selectivity.
Additional Information
© 2011 Wiley-Liss, Inc. Received 5 October 2010; Revised 20 January 2011; Accepted 1 February 2011. Published online 15 February 2011. Grant sponsor: Gifts to the Materials and Process Simulation Center (MSC) (California Institute of Technology). Lindsay Riley participated in 2009 program of Southern California Bioinformatics Summer Institute (SoCalBSI). The authors thank Dr. Jenelle Bray and Dr. Ravi Abrol for sharing their SuperBiHelix and BiHelix protocols before publication.Attached Files
Accepted Version - nihms270736.pdf
Supplemental Material - PROT_23012_sm_suppinformation.pdf
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Additional details
- PMCID
- PMC3092833
- Eprint ID
- 23855
- DOI
- 10.1002/prot.23012
- Resolver ID
- CaltechAUTHORS:20110601-091219051
- Caltech Materials and Process Simulation Center (MSC)
- Created
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2011-06-17Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field