Evidence map›Paper›PMID 24094405›Full record

ArticleBiophysical journal2013

Global transitions of proteins explored by a multiscale hybrid methodology: application to adenylate kinase.

Mert Gur, Jeffry D Madura, Ivet Bahar

Abstract read
In one paragraph

Article in Biophysical journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

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  9. Predicting protein conformational motions using energetic frustration analysis and AlphaFold2.Proceedings of the National Academy of Sciences of the United States of America · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Mert GurDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Jeffry D Madura
Ivet Bahar

Funding

TrainingP41GM103712 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FAEDER, JAMES · 2012 to 2021
$16.3M
Continued Development of Protein Dynamics Software ProDyR01GM099738 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET · 2012 to 2015
$1.1M
NIGMS NIH HHS P41 GM103712NIGMS NIH HHS P41-GM103712NIGMS NIH HHS R01 GM099738NIGMS NIH HHS R01-GM099738-02
6 · The paper itself

Abstract

Efficient and accurate mapping of transition pathways is a challenging problem in allosteric proteins. We propose here a to our knowledge new methodology called collective molecular dynamics (coMD). coMD takes advantage of the collective modes of motions encoded by the fold, simultaneously evaluating the interactions and energetics via a full-atomic MD simulation protocol. The basic approach is to deform the structure collectively along the modes predicted by the anisotropic network model, upon selecting them via a Monte Carlo/Metropolis algorithm from among the complete pool of all accessible modes. Application to adenylate kinase, an allosteric enzyme composed of three domains, CORE, LID, and NMP, shows that both open-to-closed and closed-to-open transitions are readily sampled by coMD, with large-scale motions of the LID dominating. An energy-barrier crossing occurs during the NMP movements. The energy barrier originates from a switch between the salt bridges K136-D118 at the LID-CORE interface and K57-E170 and D33-R156 at the CORE-NMP and LID-NMP interfaces, respectively. Despite its simplicity and computing efficiency, coMD yields ensembles of transition pathways in close accord with detailed full atomic simulations, lending support to its utility as a multiscale hybrid method for efficiently exploring the allosteric transitions of multidomain or multimeric proteins.

Indexed as

AlgorithmsMolecular Dynamics SimulationAdenylate KinaseAmino Acid SequenceAnimalsAnisotropyMolecular Sequence DataAdenylate Kinase

Identifiers

PMID24094405
PMCPMC3791301

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.