Evidence map›Paper›PMID 22500075›Full record

ArticleJournal of biomedicine & biotechnology2012

Predicting protein interactions by Brownian dynamics simulations.

Xuan-Yu Meng, Yu Xu, Hong-Xing Zhang, Mihaly Mezei, Meng Cui

Abstract read
In one paragraph

Article in Journal of biomedicine & biotechnology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Computational approaches for modeling GPCR dimerization.Current pharmaceutical biotechnology · 2014
    Review
  3. Review
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.

Xuan-Yu MengDepartment of Physiology and Biophysics, Virginia Commonwealth University, Richmond, VA 23298, USA.
Yu Xu
Hong-Xing Zhang
Mihaly Mezei
Meng Cui

Funding

Modeling Sweet Protein-Receptor InteractionsR21DC008996 · NIDCD · VIRGINIA COMMONWEALTH UNIVERSITY · PI CUI, MENG · 2009 to 2010
$613k
High Performance Computing Cluster for Biomedical Research at VCUS10RR027411 · NCRR · VIRGINIA COMMONWEALTH UNIVERSITY · PI CUI, MENG · 2010 to 2010
$417k
NCRR NIH HHS S10 RR027411NCRR NIH HHS S10RR027411NIDCD NIH HHS DC008996NIDCD NIH HHS R21 DC008996
6 · The paper itself

Abstract

We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.

Indexed as

AlgorithmsMolecular Dynamics SimulationProtein BindingProtein Interaction MappingProteinsStatic ElectricityThermodynamicsProteins

Identifiers

PMID22500075
PMCPMC3303761

What OpenQuestion holds

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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.