Literature DB >> 25725756

Systematic characterization of protein folding pathways using diffusion maps: application to Trp-cage miniprotein.

Sang Beom Kim1, Carmeline J Dsilva1, Ioannis G Kevrekidis1, Pablo G Debenedetti1.   

Abstract

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories in a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.

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Year:  2015        PMID: 25725756     DOI: 10.1063/1.4913322

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  8 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.  Galerkin approximation of dynamical quantities using trajectory data.

Authors:  Erik H Thiede; Dimitrios Giannakis; Aaron R Dinner; Jonathan Weare
Journal:  J Chem Phys       Date:  2019-06-28       Impact factor: 3.488

3.  Preferential binding effects on protein structure and dynamics revealed by coarse-grained Monte Carlo simulation.

Authors:  R B Pandey; D J Jacobs; B L Farmer
Journal:  J Chem Phys       Date:  2017-05-21       Impact factor: 3.488

4.  Identification of simple reaction coordinates from complex dynamics.

Authors:  Robert T McGibbon; Brooke E Husic; Vijay S Pande
Journal:  J Chem Phys       Date:  2017-01-28       Impact factor: 3.488

5.  Computational investigation of cold denaturation in the Trp-cage miniprotein.

Authors:  Sang Beom Kim; Jeremy C Palmer; Pablo G Debenedetti
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-25       Impact factor: 11.205

6.  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

7.  Long-Time-Scale Predictions from Short-Trajectory Data: A Benchmark Analysis of the Trp-Cage Miniprotein.

Authors:  John Strahan; Adam Antoszewski; Chatipat Lorpaiboon; Bodhi P Vani; Jonathan Weare; Aaron R Dinner
Journal:  J Chem Theory Comput       Date:  2021-04-28       Impact factor: 6.006

8.  Analyzing Grid-Based Direct Quantum Molecular Dynamics Using Non-Linear Dimensionality Reduction.

Authors:  Gareth W Richings; Scott Habershon
Journal:  Molecules       Date:  2021-12-07       Impact factor: 4.411

  8 in total

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