Literature DB >> 26579922

Conformational Entropies and Order Parameters: Convergence, Reproducibility, and Transferability.

Samuel Genheden1, Mikael Akke2, Ulf Ryde1.   

Abstract

Conformational entropy provides major contributions to protein folding and functions, such as ligand binding, making it a potentially important driver of biologically relevant processes. NMR spectroscopy is a unique technique to estimate conformational entropy changes at atomic resolution, an approach that can be favorably augmented by comparisons with results from molecular dynamics (MD) simulations, for example, by generating an order-parameter-to-entropy dictionary. Here, we address critical issues pertaining to such an approach, including reproducibility, convergence, and transferability by analyzing long (380 ns -1 ms) MD trajectories obtained for five different proteins. We observe that order parameters and conformational entropies calculated over 10-100 ns windows are typically well converged among individual MD trajectories and reproducible between pairs of independent trajectories, when calculated on a per-residue level. However, significant discrepancies sometimes arise for the total conformational entropy evaluated as the sum of the residue-specific entropies, especially in cases that involve rare transitions to alternative conformational states. Furthermore, we find that the order-parameter-to-entropy dictionary depends strongly on the protein and the sampling frequency, but much less so on the molecular dynamics force field. Thus, the transferability of the dictionary is poor between proteins but relatively good between different states (e.g., different ligand-bound complexes) of the same protein, provided that a protein-specific dictionary has been derived.

Year:  2014        PMID: 26579922     DOI: 10.1021/ct400747s

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  10 in total

1.  Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations.

Authors:  Michael C Baxa; Esmael J Haddadian; John M Jumper; Karl F Freed; Tobin R Sosnick
Journal:  Proc Natl Acad Sci U S A       Date:  2014-10-13       Impact factor: 11.205

2.  Self-Consistent Framework Connecting Experimental Proxies of Protein Dynamics with Configurational Entropy.

Authors:  Markus Fleck; Anton A Polyansky; Bojan Zagrovic
Journal:  J Chem Theory Comput       Date:  2018-06-08       Impact factor: 6.578

3.  Conformational Entropy of Intrinsically Disordered Proteins from Amino Acid Triads.

Authors:  Anupaul Baruah; Pooja Rani; Parbati Biswas
Journal:  Sci Rep       Date:  2015-07-03       Impact factor: 4.379

4.  Analysis of factors influencing hydration site prediction based on molecular dynamics simulations.

Authors:  Ying Yang; Bingjie Hu; Markus A Lill
Journal:  J Chem Inf Model       Date:  2014-10-07       Impact factor: 4.956

5.  Assessing the stability of free-energy perturbation calculations by performing variations in the method.

Authors:  Francesco Manzoni; Ulf Ryde
Journal:  J Comput Aided Mol Des       Date:  2018-03-13       Impact factor: 3.686

6.  Predicting the Most Stable Aptamer/Target Molecule Complex Configuration Using a Stochastic-Tunnelling Basin-Hopping Discrete Molecular Dynamics Method: A Novel Global Minimum Search Method for a Biomolecule Complex.

Authors:  Hung-Wei Yang; Shin-Pon Ju; Yu-Sheng Lin
Journal:  Comput Struct Biotechnol J       Date:  2019-06-20       Impact factor: 7.271

7.  Dynamics in natural and designed elastins and their relation to elastic fiber structure and recoil.

Authors:  Ma Faye Charmagne A Carvajal; Jonathan M Preston; Nour M Jamhawi; T Michael Sabo; Shibani Bhattacharya; James M Aramini; Richard J Wittebort; Ronald L Koder
Journal:  Biophys J       Date:  2021-07-31       Impact factor: 3.699

8.  Correlation as a determinant of configurational entropy in supramolecular and protein systems.

Authors:  Andrew T Fenley; Benjamin J Killian; Vladimir Hnizdo; Adam Fedorowicz; Dan S Sharp; Michael K Gilson
Journal:  J Phys Chem B       Date:  2014-04-18       Impact factor: 2.991

9.  Computational and In Vitro Investigation of (-)-Epicatechin and Proanthocyanidin B2 as Inhibitors of Human Matrix Metalloproteinase 1.

Authors:  Kyung Eun Lee; Shiv Bharadwaj; Umesh Yadava; Sang Gu Kang
Journal:  Biomolecules       Date:  2020-09-28

10.  Exploring ligand dynamics in protein crystal structures with ensemble refinement.

Authors:  Octav Caldararu; Vilhelm Ekberg; Derek T Logan; Esko Oksanen; Ulf Ryde
Journal:  Acta Crystallogr D Struct Biol       Date:  2021-07-29       Impact factor: 7.652

  10 in total

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