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Accelerated weight histogram method for exploring free energy landscapes
KTH, School of Engineering Sciences (SCI), Theoretical Physics, Theoretical & Computational Biophysics.
KTH, School of Engineering Sciences (SCI), Theoretical Physics, Statistical Physics.ORCID iD: 0000-0002-9881-7857
KTH, School of Engineering Sciences (SCI), Theoretical Physics, Theoretical & Computational Biophysics.ORCID iD: 0000-0002-7498-7763
2014 (English)In: Journal of Chemical Physics, ISSN 0021-9606, E-ISSN 1089-7690, Vol. 141, no 4, 044110- p.Article in journal (Refereed) Published
Abstract [en]

Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A major advantage of the method is its general formulation, making it a powerful platform for developing further extensions and analyzing its relation to already existing methods. Here, we demonstrate its efficiency and general applicability by calculating the potential of mean force along a reaction coordinate for both a single dimension and multiple dimensions. We make use of a non-uniform, free energy dependent target distribution in reaction coordinate space so that computational efforts are not wasted on physically irrelevant regions. We present numerical results for molecular dynamics simulations of lithium acetate in solution and chignolin, a 10-residue long peptide that folds into a beta-hairpin. We further present practical guidelines for setting up and running an AWH simulation.

Place, publisher, year, edition, pages
2014. Vol. 141, no 4, 044110- p.
Keyword [en]
Ensemble Monte-Carlo, Molecular-Dynamics, Multicanonical Ensemble, Force-Field, Protein, Simulation, Systems, Distributions, Transitions, Chignolin
National Category
Biophysics
Identifiers
URN: urn:nbn:se:kth:diva-151349DOI: 10.1063/1.4890371ISI: 000340712200018Scopus ID: 2-s2.0-84905648018OAI: oai:DiVA.org:kth-151349DiVA: diva2:748353
Funder
EU, European Research Council, 258980
Note

QC 20140919

Available from: 2014-09-19 Created: 2014-09-18 Last updated: 2017-12-05Bibliographically approved
In thesis
1. Optimizing sampling of important events in complex biomolecular systems
Open this publication in new window or tab >>Optimizing sampling of important events in complex biomolecular systems
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Proteins and DNA are large, complex molecules that carry out biological functions essential to all life. Their successful operation relies on adopting specific structures, stabilized by intra-molecular interactions between atoms. The spatial and temporal resolution required to study the mechanics of these molecules in full detail can only be obtained using computer simulations of molecular models. In a molecular dynamics simulation, a trajectory of the system is generated, which allows mapping out the states and dynamics of the molecule. However, the time and length scales characteristic of biological events are many orders of magnitude larger than the resolution needed to accurately describe the microscopic processes of the atoms. To overcome this problem, sampling methods have been developed that enhance the occurrence of rare but important events, which improves the statistics of simulation data.

This thesis summarizes my work on developing the AWH method, an algorithm that adaptively optimizes sampling toward a target function and simultaneously finds and assigns probabilities to states of the simulated system. I have adapted AWH for use in molecular dynamics simulations. In doing so, I investigated the convergence of the method as a function of its input parameters and improved the robustness of the method. I have also worked on a generally applicable approach for calculating the target function in an automatic and non-arbitrary way. Traditionally, the target is set in an ad hoc way, while now sampling can be improved by 50% or more without extra effort. I have also used AWH to improve sampling in two biologically relevant applications. In one paper, we study the opening of a DNA base pair, which due to the stability of the DNA double helix only very rarely occurs spontaneously. We show that the probability of opening depends on both nearest-neighbor and longer-range sequence effect and furthermore structurally characterize the open states. In the second application the permeability and ammonia selectivity of the membrane protein aquaporin is investigated and we show that these functions are sensitive to specific mutations.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. 47 p.
Series
TRITA-FYS, ISSN 0280-316X ; 2017:72
Keyword
molecular dynamics, free energy calculation, adaptive sampling, extended ensembles, membrane proteins, DNA
National Category
Biophysics
Research subject
Biological Physics
Identifiers
urn:nbn:se:kth:diva-217837 (URN)978-91-7729-599-0 (ISBN)
Public defence
2017-12-07, F3, Lindstedtsvägen 26, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20171117

Available from: 2017-11-17 Created: 2017-11-17 Last updated: 2017-11-21Bibliographically approved

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Lidmar, JackHess, Berk

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