English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Efficient Ensemble Refinement by Reweighting

MPS-Authors
/persons/resource/persons194635

Köfinger,  Jürgen
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

/persons/resource/persons220228

Stelzl,  Lukas S.
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

/persons/resource/persons110250

Reuter,  Klaus
Max Planck Computing and Data Facility, Max Planck Society;

Allande,  César
Max Planck Computing and Data Facility, Max Planck Society;

/persons/resource/persons194653

Reichel,  Katrin
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

/persons/resource/persons15259

Hummer,  Gerhard       
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;
Institute of Biophysics, Goethe University, Frankfurt am Main, Germany;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

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.


Cite as: https://hdl.handle.net/21.11116/0000-0003-9E43-0
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.