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  Efficient Ensemble Refinement by Reweighting

Köfinger, J., Stelzl, L. S., Reuter, K., Allande, C., Reichel, K., & Hummer, G. (2019). Efficient Ensemble Refinement by Reweighting. Journal of Chemical Theory and Computation, 15(5), 3390-3409. doi:10.1021/acs.jctc.8b01231.

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 Creators:
Köfinger, Jürgen1, Author           
Stelzl, Lukas S.1, Author           
Reuter, Klaus2, Author           
Allande, César2, Author
Reichel, Katrin1, Author           
Hummer, Gerhard1, 3, Author                 
Affiliations:
1Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society, ou_2068292              
2Max Planck Computing and Data Facility, Max Planck Society, ou_2364734              
3Institute of Biophysics, Goethe University, Frankfurt am Main, Germany, ou_persistent22              

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 Abstract: Ensemble refinement produces structural ensembles of flexible and dynamic biomolecules by integrating experimental data and molecular simulations. Here we present two efficient numerical methods to solve the computationally challenging maximum-entropy problem arising from a Bayesian formulation of ensemble refinement. Recasting the resulting constrained weight optimization problem into an unconstrained form enables the use of gradient-based algorithms. In two complementary formulations that differ in their dimensionality, we optimize either the log-weights directly or the generalized forces appearing in the explicit analytical form of the solution. We first demonstrate the robustness, accuracy, and efficiency of the two methods using synthetic data. We then use NMR J-couplings to reweight an all-atom molecular dynamics simulation ensemble of the disordered peptide Ala-5 simulated with the AMBER99SB*-ildn-q force field. After reweighting, we find a consistent increase in the population of the polyproline-II conformations and a decrease of α-helical-like conformations. Ensemble refinement makes it possible to infer detailed structural models for biomolecules exhibiting significant dynamics, such as intrinsically disordered proteins, by combining input from experiment and simulation in a balanced manner.

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Language(s): eng - English
 Dates: 2018-12-072019-04-022019-05-14
 Publication Status: Published in print
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1021/acs.jctc.8b01231
 Degree: -

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Title: Journal of Chemical Theory and Computation
  Other : J. Chem. Theory Comput.
Source Genre: Journal
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Publ. Info: Washington, D.C. : American Chemical Society
Pages: - Volume / Issue: 15 (5) Sequence Number: - Start / End Page: 3390 - 3409 Identifier: ISSN: 1549-9618
CoNE: https://pure.mpg.de/cone/journals/resource/111088195283832