Evidence map›Paper›PMID 19594147›Full record

ArticleThe journal of physical chemistry. B2009

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 M Zuckerman

Abstract read
In one paragraph

Article in The journal of physical chemistry. B, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. OPTIMIZATION BIAS IN ENERGY-BASED STRUCTURE PREDICTION.Journal of theoretical & computational chemistry · 2013
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Equilibrium sampling in biomolecular simulations.Annual review of biophysics · 2011
    Review
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Artem B MamonovDepartment of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Divesh Bhatt
Derek J Cashman
Ying Ding
Daniel M Zuckerman

Funding

Fast Computations for Structural Transitions in ProteinsR01GM070987 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ZUCKERMAN, DANIEL M · 2004 to 2008
$1.1M
Toward Practical, Rigorous Binding Affinity CalculationsR01GM076569 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ZUCKERMAN, DANIEL M · 2007 to 2011
$1.0M
NIGMS NIH HHS GM070987NIGMS NIH HHS GM076569NIGMS NIH HHS R01 GM070987NIGMS NIH HHS R01 GM076569
6 · The paper itself

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 Go-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".

Indexed as

Models, MolecularMonte Carlo MethodComputer SimulationPeptidesProtein ConformationProteinsThermodynamicsPeptidespolyalanineProteins

Identifiers

PMID19594147
PMCPMC2766542

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.