Evidence map›Paper›PMID 23139645›Full record

ArticleJournal of chemical theory and computation2012

Exploring residue component contributions to dynamical network models of allostery.

Adam T Vanwart, John Eargle, Zaida Luthey-Schulten, Rommie E Amaro

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.

0numbers the graph read from it
0cells of the map it votes in
88citing 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.

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3 · Its place in the literature

Who cites it

88 citing papers in PubMed.

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  11. BaNDyT: Bayesian Network modeling of molecular Dynamics Trajectories.bioRxiv : the preprint server for biology · 2024
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28 more citing papers are in PubMed but not listed here.

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

4 authors.

Adam T VanwartDepartment of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093.
John Eargle
Zaida Luthey-Schulten
Rommie E Amaro

Funding

WHOLE CELL SIMULATIONP41RR005969 · NCRR · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI STONE, JOHN H · 1990 to 2011
$19.8M
A Structural Systems Biology Approach to Drug DiscoveryDP2OD007237 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI AMARO, ROMMIE E · 2010 to 2015
$2.9M
NCRR NIH HHS P41 RR005969NIH HHS DP2 OD007237
6 · The paper itself

Abstract

Allosteric regulation in biological systems is of considerable interest given the vast number of proteins that exhibit such behavior. Network models obtained from molecular dynamics simulations have been shown to be powerful tools for the analysis of allostery. In this work, different coarse-grain residue representations (nodes) are used together with a dynamical network model to investigate models of allosteric regulation. This model assumes that allosteric signals are dependent on positional correlations of protein substituents, as determined through molecular dynamics simulations, and uses correlated motion to generate a signaling weight between two given nodes. We examine four types of network models using different node representations in Cartesian coordinates: the (i) residue alpha-carbons, (ii) sidechain center of mass, (iii) backbone center of mass, and the entire (iv) residue center of mass. All correlations are filtered by a dynamic contact map that defines the allowable interactions between nodes based on physical proximity. We apply the four models to imidazole glycerol phosphate synthase (IGPS), which provides a well-studied experimental framework in which allosteric communication is known to persist across disparate protein domains (e.g. a protein dimer interface). IGPS is modeled as a network of nodes and weighted edges. Optimal allosteric pathways are traced using the Floyd Warshall algorithm for weighted networks, and community analysis (a form of hierarchical clustering) is performed using the Girvan-Newman algorithm. Our results show that dynamical information encoded in the residue center of mass must be included in order to detect residues that are experimentally known to play a role in allosteric communication for IGPS. More broadly, this new method may be useful for predicting pathways of allosteric communication for any biomolecular system in atomic detail.

Identifiers

PMID23139645
PMCPMC3489502

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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.