General library-based monte carlo technique enables equilibrium sampling of semi-atomistic protein models

Artem B. Mamonov, Divesh Bhatt, Derek J. Cashman, Ying Ding, Daniel Zuckerman

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

We introduce "library-based Monte Carlo" (LBMC) simulation, which performs Boltzmann sampling of molecular systems based on precalculated statistical libraries of molecular-fragment configurations, energies, and interactions. The library for each fragment can be Boltzmann distributed and thus account for all correlations internal to the fragment. LBMC can be applied to both atomistic and coarse-grained models, as we demonstrate in this "proof-of-principle" report. We first verify the approach in a toy model and in implicitly solvated all-atom polyalanine systems. We next study five proteins, up to 309 residues in size. On the basis of atomistic equilibrium libraries of peptide-plane configurations, the proteins are modeled with fully atomistic backbones and simplified Gō-like interactions among residues. We show that full equilibrium sampling can be obtained in days to weeks on a single processor, suggesting that more accurate models are well within reach. For the future, LBMC provides a convenient platform for constructing adjustable or mixed-resolution models: the configurations of all atoms can be stored at no run-time cost, while an arbitrary subset of interactions is "turned on".

Original languageEnglish (US)
Pages (from-to)10891-10904
Number of pages14
JournalJournal of Physical Chemistry B
Volume113
Issue number31
DOIs
StatePublished - Aug 6 2009
Externally publishedYes

Fingerprint

Libraries
sampling
Sampling
proteins
Proteins
fragments
Molecular Conformation
Peptide Library
Play and Playthings
configurations
Atoms
interactions
Costs and Cost Analysis
Peptides
set theory
peptides
atoms
central processing units
platforms
costs

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry
  • Surfaces, Coatings and Films
  • Materials Chemistry

Cite this

General library-based monte carlo technique enables equilibrium sampling of semi-atomistic protein models. / Mamonov, Artem B.; Bhatt, Divesh; Cashman, Derek J.; Ding, Ying; Zuckerman, Daniel.

In: Journal of Physical Chemistry B, Vol. 113, No. 31, 06.08.2009, p. 10891-10904.

Research output: Contribution to journalArticle

Mamonov, Artem B. ; Bhatt, Divesh ; Cashman, Derek J. ; Ding, Ying ; Zuckerman, Daniel. / General library-based monte carlo technique enables equilibrium sampling of semi-atomistic protein models. In: Journal of Physical Chemistry B. 2009 ; Vol. 113, No. 31. pp. 10891-10904.
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