Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations

Stelzl, L. S., Kells, A., Rosta, E., & Hummer, G. (2017). Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations. Journal of Chemical Theory and Computation, 13(12), 6328-6342. doi:10.1021/acs.jctc.7b00373.

Item is

Basisdaten

einblenden: ausblenden:
Genre: Zeitschriftenartikel

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Stelzl, Lukas S.1, Autor           
Kells, Adam2, Autor
Rosta, Edina2, Autor
Hummer, Gerhard1, 3, Autor                 
Affiliations:
1Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society, ou_2068292              
2Department of Chemistry, King’s College London, London SE1 1UL, United Kingdom, ou_persistent22              
3Institute for Biophysics, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany, ou_persistent22              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: We present an algorithm to calculate free energies and rates from molecular simulations on biased potential energy surfaces. As input, it uses the accumulated times spent in each state or bin of a histogram and counts of transitions between them. Optimal unbiased equilibrium free energies for each of the states/bins are then obtained by maximizing the likelihood of a master equation (i.e., first-order kinetic rate model). The resulting free energies also determine the optimal rate coefficients for transitions between the states or bins on the biased potentials. Unbiased rates can be estimated, e.g., by imposing a linear free energy condition in the likelihood maximization. The resulting “dynamic histogram analysis method extended to detailed balance” (DHAMed) builds on the DHAM method. It is also closely related to the transition-based reweighting analysis method (TRAM) and the discrete TRAM (dTRAM). However, in the continuous-time formulation of DHAMed, the detailed balance constraints are more easily accounted for, resulting in compact expressions amenable to efficient numerical treatment. DHAMed produces accurate free energies in cases where the common weighted-histogram analysis method (WHAM) for umbrella sampling fails because of slow dynamics within the windows. Even in the limit of completely uncorrelated data, where WHAM is optimal in the maximum-likelihood sense, DHAMed results are nearly indistinguishable. We illustrate DHAMed with applications to ion channel conduction, RNA duplex formation, α-helix folding, and rate calculations from accelerated molecular dynamics. DHAMed can also be used to construct Markov state models from biased or replica-exchange molecular dynamics simulations. By using binless WHAM formulated as a numerical minimization problem, the bias factors for the individual states can be determined efficiently in a preprocessing step and, if needed, optimized globally afterward.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2017-04-172017-10-232017-12-12
 Publikationsstatus: Erschienen
 Seiten: 15
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1021/acs.jctc.7b00373
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Journal of Chemical Theory and Computation
  Andere : J. Chem. Theory Comput.
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Washington, D.C. : American Chemical Society
Seiten: - Band / Heft: 13 (12) Artikelnummer: - Start- / Endseite: 6328 - 6342 Identifikator: Anderer: 1549-9618
CoNE: https://pure.mpg.de/cone/journals/resource/111088195283832