Signaling across biological membranes is critical to living cells and involves membrane- embedded receptors, which transduce extracellular stimuli into cytoplasmic responses through long-range allosteric communication. G protein-coupled receptors (GPCRs) constitute the largest family among these receptors. They are encoded by more than eight hundred genes in humans and are involved in a large diversity of critical functions but also diseases, making GPCRs the target of close to 30 % of current marketed drugs. Although a wealth of genomic and functional data is available on these receptors, the lack of high-resolution structural and mechanistic information hinders the development of specific therapies to modulate their function. The goal of this proposal is to uncover the sequence, structure and energetic relationships governing GPCR signaling properties. We will address this problem using structure modeling, computational protein design, statistical analysis and experimental approaches. An immediate challenge will be to uncover the structure space sampled by representative members of naturally evolved GPCRs. [This will be achieved by modeling the conformations of inactive and active states of the receptor and identifying the networks of physical interactions mediating the allosteric transitions using structural sampling techniques that will be developed within the program RosettaMembrane.] An orthogonal question is which amino-acid sequence space encodes the folding and structural plasticity in GPCRs. It will be answered by statistical comparison between natural sequences and sequences evolved in silico under multiple physical constraints using the design mode of RosettaMembrane. As stringent tests of the accuracy of the structural, energetic and mechanistic predictions, GPCR variants with modified signaling properties will be designed and experimentally tested. The high-resolution information gained from these studies will set the stage for the rational design of GPCR variants with reprogrammed signaling properties for future structural and functional studies at the system level.

Public Health Relevance

G protein-coupled receptors are critically involved in many diseases but the lack of high-resolution structures of these receptors hinders the design of specific therapeutics. The proposed research aims at accurately modeling their structures in diverse functional states and at designing receptor variants with reprogrammed signaling properties to better understand their function.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Biochemistry and Biophysics of Membranes Study Section (BBM)
Program Officer
Dunsmore, Sarah
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Baylor College of Medicine
Schools of Medicine
United States
Zip Code
Feng, Xiang; Barth, Patrick (2016) A topological and conformational stability alphabet for multipass membrane proteins. Nat Chem Biol 12:167-73
Barth, Patrick; Senes, Alessandro (2016) Toward high-resolution computational design of the structure and function of helical membrane proteins. Nat Struct Mol Biol 23:475-80
Arber, Caroline; Feng, Xiang; Abhyankar, Harshal et al. (2015) Survivin-specific T cell receptor targets tumor but not T cells. J Clin Invest 125:157-68
Wang, Y; Barth, P (2015) Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy. Nat Commun 6:7196
Kufareva, Irina; Katritch, Vsevolod; Participants of GPCR Dock 2013 et al. (2014) Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges. Structure 22:1120-39
Chen, Kuang-Yui M; Sun, Jiaming; Salvo, Jason S et al. (2014) High-resolution modeling of transmembrane helical protein structures from distant homologues. PLoS Comput Biol 10:e1003636