Literature DB >> 25530262

Evolution, energy landscapes and the paradoxes of protein folding.

Peter G Wolynes1.   

Abstract

Protein folding has been viewed as a difficult problem of molecular self-organization. The search problem involved in folding however has been simplified through the evolution of folding energy landscapes that are funneled. The funnel hypothesis can be quantified using energy landscape theory based on the minimal frustration principle. Strong quantitative predictions that follow from energy landscape theory have been widely confirmed both through laboratory folding experiments and from detailed simulations. Energy landscape ideas also have allowed successful protein structure prediction algorithms to be developed. The selection constraint of having funneled folding landscapes has left its imprint on the sequences of existing protein structural families. Quantitative analysis of co-evolution patterns allows us to infer the statistical characteristics of the folding landscape. These turn out to be consistent with what has been obtained from laboratory physicochemical folding experiments signaling a beautiful confluence of genomics and chemical physics.
Copyright © 2014 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Entities:  

Keywords:  Folding landscape; Natural selection; Structure prediction

Mesh:

Year:  2014        PMID: 25530262      PMCID: PMC4472606          DOI: 10.1016/j.biochi.2014.12.007

Source DB:  PubMed          Journal:  Biochimie        ISSN: 0300-9084            Impact factor:   4.079


  99 in total

1.  Modeling evolutionary landscapes: mutational stability, topology, and superfunnels in sequence space.

Authors:  E Bornberg-Bauer; H S Chan
Journal:  Proc Natl Acad Sci U S A       Date:  1999-09-14       Impact factor: 11.205

2.  Understanding hierarchical protein evolution from first principles.

Authors:  N V Dokholyan; E I Shakhnovich
Journal:  J Mol Biol       Date:  2001-09-07       Impact factor: 5.469

3.  Establishing the entatic state in folding metallated Pseudomonas aeruginosa azurin.

Authors:  Chenghang Zong; Corey J Wilson; Tongye Shen; Pernilla Wittung-Stafshede; Steven L Mayo; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2007-02-14       Impact factor: 11.205

4.  Heterogeneity even at the speed limit of folding: large-scale molecular dynamics study of a fast-folding variant of the villin headpiece.

Authors:  Daniel L Ensign; Peter M Kasson; Vijay S Pande
Journal:  J Mol Biol       Date:  2007-09-29       Impact factor: 5.469

5.  Redesigning the hydrophobic core of a four-helix-bundle protein.

Authors:  M Munson; R O'Brien; J M Sturtevant; L Regan
Journal:  Protein Sci       Date:  1994-11       Impact factor: 6.725

6.  Protein folding mechanisms and the multidimensional folding funnel.

Authors:  N D Socci; J N Onuchic; P G Wolynes
Journal:  Proteins       Date:  1998-08-01

7.  Coevolutionary information, protein folding landscapes, and the thermodynamics of natural selection.

Authors:  Faruck Morcos; Nicholas P Schafer; Ryan R Cheng; José N Onuchic; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2014-08-11       Impact factor: 11.205

8.  Experimental evidence for a frustrated energy landscape in a three-helix-bundle protein family.

Authors:  Beth G Wensley; Sarah Batey; Fleur A C Bone; Zheng Ming Chan; Nuala R Tumelty; Annette Steward; Lee Gyan Kwa; Alessandro Borgia; Jane Clarke
Journal:  Nature       Date:  2010-02-04       Impact factor: 49.962

9.  Learning To Fold Proteins Using Energy Landscape Theory.

Authors:  N P Schafer; B L Kim; W Zheng; P G Wolynes
Journal:  Isr J Chem       Date:  2014-08       Impact factor: 3.333

10.  Protein frustratometer: a tool to localize energetic frustration in protein molecules.

Authors:  Michael Jenik; R Gonzalo Parra; Leandro G Radusky; Adrian Turjanski; Peter G Wolynes; Diego U Ferreiro
Journal:  Nucleic Acids Res       Date:  2012-05-29       Impact factor: 16.971

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  45 in total

1.  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

2.  Surveying the Energy Landscapes of Aβ Fibril Polymorphism.

Authors:  Mingchen Chen; Nicholas P Schafer; Peter G Wolynes
Journal:  J Phys Chem B       Date:  2018-10-01       Impact factor: 2.991

3.  Topology, structures, and energy landscapes of human chromosomes.

Authors:  Bin Zhang; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2015-04-27       Impact factor: 11.205

4.  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

5.  Protein tolerance to random circular permutation correlates with thermostability and local energetics of residue-residue contacts.

Authors:  Joshua T Atkinson; Alicia M Jones; Vikas Nanda; Jonathan J Silberg
Journal:  Protein Eng Des Sel       Date:  2019-12-31       Impact factor: 1.650

6.  Evidence for the principle of minimal frustration in the evolution of protein folding landscapes.

Authors:  Franco O Tzul; Daniel Vasilchuk; George I Makhatadze
Journal:  Proc Natl Acad Sci U S A       Date:  2017-02-14       Impact factor: 11.205

7.  Exploring the aggregation free energy landscape of the amyloid-β protein (1-40).

Authors:  Weihua Zheng; Min-Yeh Tsai; Mingchen Chen; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2016-10-03       Impact factor: 11.205

Review 8.  Genomic Energy Landscapes.

Authors:  Bin Zhang; Peter G Wolynes
Journal:  Biophys J       Date:  2016-09-30       Impact factor: 4.033

9.  Funneled angle landscapes for helical proteins.

Authors:  John J Kozak; Harry B Gray; Roberto A Garza-López
Journal:  J Inorg Biochem       Date:  2020-05-11       Impact factor: 4.155

10.  Magnesium controls aptamer-expression platform switching in the SAM-I riboswitch.

Authors:  Susmita Roy; Scott P Hennelly; Heiko Lammert; José N Onuchic; Karissa Y Sanbonmatsu
Journal:  Nucleic Acids Res       Date:  2019-04-08       Impact factor: 16.971

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