Literature DB >> 23705683

How kinetics within the unfolded state affects protein folding: an analysis based on markov state models and an ultra-long MD trajectory.

Nan-jie Deng1, Wei Dai, Ronald M Levy.   

Abstract

Understanding how kinetics in the unfolded state affects protein folding is a fundamentally important yet less well-understood issue. Here we employ three different models to analyze the unfolded landscape and folding kinetics of the miniprotein Trp-cage. The first is a 208 μs explicit solvent molecular dynamics (MD) simulation from D. E. Shaw Research containing tens of folding events. The second is a Markov state model (MSM-MD) constructed from the same ultralong MD simulation; MSM-MD can be used to generate thousands of folding events. The third is a Markov state model built from temperature replica exchange MD simulations in implicit solvent (MSM-REMD). All the models exhibit multiple folding pathways, and there is a good correspondence between the folding pathways from direct MD and those computed from the MSMs. The unfolded populations interconvert rapidly between extended and collapsed conformations on time scales ≤40 ns, compared with the folding time of ∼5 μs. The folding rates are independent of where the folding is initiated from within the unfolded ensemble. About 90% of the unfolded states are sampled within the first 40 μs of the ultralong MD trajectory, which on average explores ∼27% of the unfolded state ensemble between consecutive folding events. We clustered the folding pathways according to structural similarity into "tubes", and kinetically partitioned the unfolded state into populations that fold along different tubes. From our analysis of the simulations and a simple kinetic model, we find that, when the mixing within the unfolded state is comparable to or faster than folding, the folding waiting times for all the folding tubes are similar and the folding kinetics is essentially single exponential despite the presence of heterogeneous folding paths with nonuniform barriers. When the mixing is much slower than folding, different unfolded populations fold independently, leading to nonexponential kinetics. A kinetic partition of the Trp-cage unfolded state is constructed which reveals that different unfolded populations have almost the same probability to fold along any of the multiple folding paths. We are investigating whether the results for the kinetics in the unfolded state of the 20-residue Trp-cage is representative of larger single domain proteins.

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Year:  2013        PMID: 23705683      PMCID: PMC3808496          DOI: 10.1021/jp401962k

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  57 in total

1.  Entropic barriers, transition states, funnels, and exponential protein folding kinetics: a simple model.

Authors:  D J Bicout; A Szabo
Journal:  Protein Sci       Date:  2000-03       Impact factor: 6.725

2.  Trp-cage: folding free energy landscape in explicit water.

Authors:  Ruhong Zhou
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-27       Impact factor: 11.205

3.  Escaping free-energy minima.

Authors:  Alessandro Laio; Michele Parrinello
Journal:  Proc Natl Acad Sci U S A       Date:  2002-09-23       Impact factor: 11.205

4.  Computing time scales from reaction coordinates by milestoning.

Authors:  Anton K Faradjian; Ron Elber
Journal:  J Chem Phys       Date:  2004-06-15       Impact factor: 3.488

Review 5.  Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet.

Authors:  Eugene Shakhnovich
Journal:  Chem Rev       Date:  2006-05       Impact factor: 60.622

6.  Rate constant and reaction coordinate of Trp-cage folding in explicit water.

Authors:  Jarek Juraszek; Peter G Bolhuis
Journal:  Biophys J       Date:  2008-08-01       Impact factor: 4.033

7.  Computing the stability diagram of the Trp-cage miniprotein.

Authors:  Dietmar Paschek; Sascha Hempel; Angel E García
Journal:  Proc Natl Acad Sci U S A       Date:  2008-11-12       Impact factor: 11.205

Review 8.  The protein folding problem.

Authors:  Ken A Dill; S Banu Ozkan; M Scott Shell; Thomas R Weikl
Journal:  Annu Rev Biophys       Date:  2008       Impact factor: 12.981

Review 9.  Everything you wanted to know about Markov State Models but were afraid to ask.

Authors:  Vijay S Pande; Kyle Beauchamp; Gregory R Bowman
Journal:  Methods       Date:  2010-06-04       Impact factor: 3.608

Review 10.  The folding of single domain proteins--have we reached a consensus?

Authors:  Tobin R Sosnick; Doug Barrick
Journal:  Curr Opin Struct Biol       Date:  2010-12-06       Impact factor: 6.809

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  17 in total

1.  A hydrodynamic view of the first-passage folding of Trp-cage miniprotein.

Authors:  Vladimir A Andryushchenko; Sergei F Chekmarev
Journal:  Eur Biophys J       Date:  2015-11-12       Impact factor: 1.733

2.  First Passage Times, Lifetimes, and Relaxation Times of Unfolded Proteins.

Authors:  Wei Dai; Anirvan M Sengupta; Ronald M Levy
Journal:  Phys Rev Lett       Date:  2015-07-21       Impact factor: 9.161

3.  How long does it take to equilibrate the unfolded state of a protein?

Authors:  Ronald M Levy; Wei Dai; Nan-Jie Deng; Dmitrii E Makarov
Journal:  Protein Sci       Date:  2013-09-17       Impact factor: 6.725

4.  Extracting intrinsic dynamic parameters of biomolecular folding from single-molecule force spectroscopy experiments.

Authors:  Gi-Moon Nam; Dmitrii E Makarov
Journal:  Protein Sci       Date:  2015-07-14       Impact factor: 6.725

Review 5.  Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics.

Authors:  Tatiana Maximova; Ryan Moffatt; Buyong Ma; Ruth Nussinov; Amarda Shehu
Journal:  PLoS Comput Biol       Date:  2016-04-28       Impact factor: 4.475

6.  Computing conformational free energy differences in explicit solvent: An efficient thermodynamic cycle using an auxiliary potential and a free energy functional constructed from the end points.

Authors:  Robert C Harris; Nanjie Deng; Ronald M Levy; Ryosuke Ishizuka; Nobuyuki Matubayasi
Journal:  J Comput Chem       Date:  2016-12-23       Impact factor: 3.376

7.  Temperature evolution of Trp-cage folding pathways: An analysis by dividing the probability flux field into stream tubes.

Authors:  Vladimir A Andryushchenko; Sergei F Chekmarev
Journal:  J Biol Phys       Date:  2017-10-05       Impact factor: 1.365

8.  Connecting free energy surfaces in implicit and explicit solvent: an efficient method to compute conformational and solvation free energies.

Authors:  Nanjie Deng; Bin W Zhang; Ronald M Levy
Journal:  J Chem Theory Comput       Date:  2015-06-09       Impact factor: 6.006

Review 9.  Markov state models of biomolecular conformational dynamics.

Authors:  John D Chodera; Frank Noé
Journal:  Curr Opin Struct Biol       Date:  2014-05-16       Impact factor: 6.809

10.  Accelerated molecular dynamics simulations of protein folding.

Authors:  Yinglong Miao; Ferran Feixas; Changsun Eun; J Andrew McCammon
Journal:  J Comput Chem       Date:  2015-06-12       Impact factor: 3.376

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