Literature DB >> 24297889

Coevolutionary signals across protein lineages help capture multiple protein conformations.

Faruck Morcos1, Biman Jana, Terence Hwa, José N Onuchic.   

Abstract

A long-standing problem in molecular biology is the determination of a complete functional conformational landscape of proteins. This includes not only proteins' native structures, but also all their respective functional states, including functionally important intermediates. Here, we reveal a signature of functionally important states in several protein families, using direct coupling analysis, which detects residue pair coevolution of protein sequence composition. This signature is exploited in a protein structure-based model to uncover conformational diversity, including hidden functional configurations. We uncovered, with high resolution (mean ~1.9 Å rmsd for nonapo structures), different functional structural states for medium to large proteins (200-450 aa) belonging to several distinct families. The combination of direct coupling analysis and the structure-based model also predicts several intermediates or hidden states that are of functional importance. This enhanced sampling is broadly applicable and has direct implications in protein structure determination and the design of ligands or drugs to trap intermediate states.

Keywords:  conformational plasticity; covariation; molecular dynamics; statistical inference

Mesh:

Substances:

Year:  2013        PMID: 24297889      PMCID: PMC3870752          DOI: 10.1073/pnas.1315625110

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  38 in total

1.  Direct-coupling analysis of residue coevolution captures native contacts across many protein families.

Authors:  Faruck Morcos; Andrea Pagnani; Bryan Lunt; Arianna Bertolino; Debora S Marks; Chris Sander; Riccardo Zecchina; José N Onuchic; Terence Hwa; Martin Weigt
Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-21       Impact factor: 11.205

2.  Computational modeling of phosphotransfer complexes in two-component signaling.

Authors:  Alexander Schug; Martin Weigt; James A Hoch; Jose N Onuchic; Terence Hwa; Hendrik Szurmant
Journal:  Methods Enzymol       Date:  2010-03-01       Impact factor: 1.600

3.  Protein structure prediction: do hydrogen bonding and water-mediated interactions suffice?

Authors:  Vanessa Oklejas; Chenghang Zong; Garegin A Papoian; Peter G Wolynes
Journal:  Methods       Date:  2010-05-26       Impact factor: 3.608

4.  The Pfam protein families database.

Authors:  Robert D Finn; Jaina Mistry; John Tate; Penny Coggill; Andreas Heger; Joanne E Pollington; O Luke Gavin; Prasad Gunasekaran; Goran Ceric; Kristoffer Forslund; Liisa Holm; Erik L L Sonnhammer; Sean R Eddy; Alex Bateman
Journal:  Nucleic Acids Res       Date:  2009-11-17       Impact factor: 16.971

5.  SMOG@ctbp: simplified deployment of structure-based models in GROMACS.

Authors:  Jeffrey K Noel; Paul C Whitford; Karissa Y Sanbonmatsu; José N Onuchic
Journal:  Nucleic Acids Res       Date:  2010-06-04       Impact factor: 16.971

6.  Protein sectors: evolutionary units of three-dimensional structure.

Authors:  Najeeb Halabi; Olivier Rivoire; Stanislas Leibler; Rama Ranganathan
Journal:  Cell       Date:  2009-08-21       Impact factor: 41.582

7.  Accessing a hidden conformation of the maltose binding protein using accelerated molecular dynamics.

Authors:  Denis Bucher; Barry J Grant; Phineus R Markwick; J Andrew McCammon
Journal:  PLoS Comput Biol       Date:  2011-04-21       Impact factor: 4.475

8.  Induced fit or conformational selection? The role of the semi-closed state in the maltose binding protein.

Authors:  Denis Bucher; Barry J Grant; J Andrew McCammon
Journal:  Biochemistry       Date:  2011-11-10       Impact factor: 3.162

9.  Protein 3D structure computed from evolutionary sequence variation.

Authors:  Debora S Marks; Lucy J Colwell; Robert Sheridan; Thomas A Hopf; Andrea Pagnani; Riccardo Zecchina; Chris Sander
Journal:  PLoS One       Date:  2011-12-07       Impact factor: 3.240

10.  Reorganizing the protein space at the Universal Protein Resource (UniProt).

Authors: 
Journal:  Nucleic Acids Res       Date:  2011-11-18       Impact factor: 16.971

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  69 in total

1.  From residue coevolution to protein conformational ensembles and functional dynamics.

Authors:  Ludovico Sutto; Simone Marsili; Alfonso Valencia; Francesco Luigi Gervasio
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-20       Impact factor: 11.205

2.  Constructing sequence-dependent protein models using coevolutionary information.

Authors:  Ryan R Cheng; Mohit Raghunathan; Jeffrey K Noel; José N Onuchic
Journal:  Protein Sci       Date:  2015-08-10       Impact factor: 6.725

Review 3.  Epistasis in protein evolution.

Authors:  Tyler N Starr; Joseph W Thornton
Journal:  Protein Sci       Date:  2016-02-28       Impact factor: 6.725

4.  Interaction specificity of clustered protocadherins inferred from sequence covariation and structural analysis.

Authors:  John M Nicoludis; Anna G Green; Sanket Walujkar; Elizabeth J May; Marcos Sotomayor; Debora S Marks; Rachelle Gaudet
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-20       Impact factor: 11.205

5.  Influence of multiple-sequence-alignment depth on Potts statistical models of protein covariation.

Authors:  Allan Haldane; Ronald M Levy
Journal:  Phys Rev E       Date:  2019-03       Impact factor: 2.529

6.  Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

Authors:  Fang Bai; Faruck Morcos; Ryan R Cheng; Hualiang Jiang; José N Onuchic
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-29       Impact factor: 11.205

7.  Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis.

Authors:  Guido Uguzzoni; Shalini John Lovis; Francesco Oteri; Alexander Schug; Hendrik Szurmant; Martin Weigt
Journal:  Proc Natl Acad Sci U S A       Date:  2017-03-13       Impact factor: 11.205

8.  Deciphering the structure of the condensin protein complex.

Authors:  Dana Krepel; Ryan R Cheng; Michele Di Pierro; José N Onuchic
Journal:  Proc Natl Acad Sci U S A       Date:  2018-11-01       Impact factor: 11.205

9.  Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy.

Authors:  Y Wang; P Barth
Journal:  Nat Commun       Date:  2015-05-21       Impact factor: 14.919

10.  Structured States of Disordered Proteins from Genomic Sequences.

Authors:  Agnes Toth-Petroczy; Perry Palmedo; John Ingraham; Thomas A Hopf; Bonnie Berger; Chris Sander; Debora S Marks
Journal:  Cell       Date:  2016-09-22       Impact factor: 41.582

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