Literature DB >> 18178645

Mutations affecting the oligomerization interface of G-protein-coupled receptors revealed by a novel de novo protein design framework.

Martin S Taylor1, Ho K Fung, Rohit Rajgaria, Marta Filizola, Harel Weinstein, Christodoulos A Floudas.   

Abstract

Specific functional and pharmacological properties have recently been ascribed to G-protein-coupled receptor (GPCR) dimers/oligomers. Because the association of two identical or two distinct GPCR monomers seems to be required to elicit receptor function, it is necessary to understand the exact nature of this interaction. We present here a novel method for de novo protein design and its application to the prediction of mutations that can stabilize or destabilize a GPCR dimer while maintaining the monomer's native fold. To test the efficacy of this new method, the dimer of the single-spanned transmembrane domain of glycophorin A was used as a model system. Experimental data from mutagenesis of the helix-helix interface are compared with computational predictions at that interface, and the model's results are found to be consistent with the experimental findings. A flexible template was developed for the rhodopsin homodimer at atomic resolution and used to predict sets of three and five mutations. The results are found to be consistent across eight case studies, with favored mutations at each position. Mutation sets predicted to be the most disruptive at the dimerization interface are found to be less specific to the flexible template than sets predicted to be less disruptive.

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Year:  2008        PMID: 18178645      PMCID: PMC2267121          DOI: 10.1529/biophysj.107.117622

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  50 in total

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Authors:  C Loose; J L Klepeis; C A Floudas
Journal:  Proteins       Date:  2004-02-01

Review 2.  Roles of G-protein-coupled receptor dimerization.

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Journal:  EMBO Rep       Date:  2004-01       Impact factor: 8.807

Review 3.  Dimerization of G-protein-coupled receptors: roles in signal transduction.

Authors:  Mei Bai
Journal:  Cell Signal       Date:  2004-02       Impact factor: 4.315

Review 4.  De novo proteins from designed combinatorial libraries.

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Journal:  Protein Sci       Date:  2004-07       Impact factor: 6.725

5.  A concept for G protein activation by G protein-coupled receptor dimers: the transducin/rhodopsin interface.

Authors:  Slawomir Filipek; Krystiana A Krzysko; Dimitrios Fotiadis; Yan Liang; David A Saperstein; Andreas Engel; Krzysztof Palczewski
Journal:  Photochem Photobiol Sci       Date:  2004-02-27       Impact factor: 3.982

6.  Sequence context modulates the stability of a GxxxG-mediated transmembrane helix-helix dimer.

Authors:  Abigail K Doura; Felix J Kobus; Leonid Dubrovsky; Ellen Hibbard; Karen G Fleming
Journal:  J Mol Biol       Date:  2004-08-20       Impact factor: 5.469

Review 7.  Exploring folding free energy landscapes using computational protein design.

Authors:  Brian Kuhlman; David Baker
Journal:  Curr Opin Struct Biol       Date:  2004-02       Impact factor: 6.809

8.  A knowledge-based scale for the analysis and prediction of buried and exposed faces of transmembrane domain proteins.

Authors:  Thijs Beuming; Harel Weinstein
Journal:  Bioinformatics       Date:  2004-02-26       Impact factor: 6.937

9.  The affinity of GXXXG motifs in transmembrane helix-helix interactions is modulated by long-range communication.

Authors:  Roman A Melnyk; Sanguk Kim; A Rachael Curran; Donald M Engelman; James U Bowie; Charles M Deber
Journal:  J Biol Chem       Date:  2004-02-05       Impact factor: 5.157

10.  Improvement of the anti-C3 activity of compstatin using rational and combinatorial approaches.

Authors:  D Morikis; A M Soulika; B Mallik; J L Klepeis; C A Floudas; J D Lambris
Journal:  Biochem Soc Trans       Date:  2004-02       Impact factor: 5.407

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  10 in total

1.  New compstatin variants through two de novo protein design frameworks.

Authors:  M L Bellows; H K Fung; M S Taylor; C A Floudas; A López de Victoria; D Morikis
Journal:  Biophys J       Date:  2010-05-19       Impact factor: 4.033

Review 2.  Computational protein design: engineering molecular diversity, nonnatural enzymes, nonbiological cofactor complexes, and membrane proteins.

Authors:  Jeffery G Saven
Journal:  Curr Opin Chem Biol       Date:  2011-04-12       Impact factor: 8.822

3.  Energy design for protein-protein interactions.

Authors:  D V S Ravikant; Ron Elber
Journal:  J Chem Phys       Date:  2011-08-14       Impact factor: 3.488

Review 4.  Structure-function of the G protein-coupled receptor superfamily.

Authors:  Vsevolod Katritch; Vadim Cherezov; Raymond C Stevens
Journal:  Annu Rev Pharmacol Toxicol       Date:  2012-11-08       Impact factor: 13.820

Review 5.  Computational design of membrane proteins.

Authors:  Jose Manuel Perez-Aguilar; Jeffery G Saven
Journal:  Structure       Date:  2012-01-11       Impact factor: 5.006

Review 6.  Computational studies of membrane proteins: models and predictions for biological understanding.

Authors:  Jie Liang; Hammad Naveed; David Jimenez-Morales; Larisa Adamian; Meishan Lin
Journal:  Biochim Biophys Acta       Date:  2011-10-12

Review 7.  Computational methods for de novo protein design and its applications to the human immunodeficiency virus 1, purine nucleoside phosphorylase, ubiquitin specific protease 7, and histone demethylases.

Authors:  M L Bellows; C A Floudas
Journal:  Curr Drug Targets       Date:  2010-03       Impact factor: 3.465

8.  Computational protein design: Advances in the design and redesign of biomolecular nanostructures.

Authors:  Jeffery G Saven
Journal:  Curr Opin Colloid Interface Sci       Date:  2010-04-01       Impact factor: 6.448

Review 9.  Increasingly accurate dynamic molecular models of G-protein coupled receptor oligomers: Panacea or Pandora's box for novel drug discovery?

Authors:  Marta Filizola
Journal:  Life Sci       Date:  2009-05-22       Impact factor: 5.037

Review 10.  Structural Perspective on Revealing and Altering Molecular Functions of Genetic Variants Linked with Diseases.

Authors:  Yunhui Peng; Emil Alexov; Sankar Basu
Journal:  Int J Mol Sci       Date:  2019-01-28       Impact factor: 5.923

  10 in total

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