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Published February 2012 | Accepted Version + Supplemental Material
Journal Article Open

BiHelix: Towards de novo structure prediction of an ensemble of G-protein coupled receptor conformations

Abstract

G-Protein Coupled Receptors (GPCRs) play a critical role in cellular signal transduction pathways and are prominent therapeutic targets. Recently there has been major progress in obtaining experimental structures for a few GPCRs. Each GPCR, however, exhibits multiple conformations that play a role in their function and we have been developing methods aimed at predicting structures for all these conformations. Analysis of available structures shows that these conformations differ in relative helix tilts and rotations. The essential issue is, determining how to orient each of the seven helices about its axis since this determines how it interacts with the other six helices. Considering all possible helix rotations to ensure that no important packings are overlooked, and using rotation angle increments of 30° about the helical axis would still lead to 12^7 or 35 million possible conformations each with optimal residue positions. We show in this paper how to accomplish this. The fundamental idea is to optimize the interactions between each pair of contacting helices while ignoring the other 5 and then to estimate the energies of all 35 million combinations using these pair-wise interactions. This BiHelix approach dramatically reduces the effort to examine the complete set of conformations and correctly identifies the crystal packing for the experimental structures plus other near-native packings we believe may play an important role in activation. This approach also enables a detailed structural analysis of functionally distinct conformations using helix-helix interaction energy landscapes and should be useful for other helical transmembrane proteins as well.

Additional Information

© 2011 Wiley Periodicals, Inc. Received 1 March 2011; Revised 10 September 2011; Accepted 27 September 2011. Published online 12 October 2011. The authors would like to acknowledge fruitful discussions with Soo-Kyung Kim, Bartosz Trzaskowski, and Adam Griffith. Bartosz also assisted with some of the analysis of the CombiHelix output. Funding: NIH Grant Number: R01NS071112, R21MH073910, and California Institute of Technology.

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Accepted Version - nihms-330919.pdf

Supplemental Material - PROT_23216_sm_suppinfo.pdf

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