Evidence map›Paper›PMID 39038177›Full record

ArticleJournal of chemical theory and computation2024

Illuminating Protein Allostery by Chemically Accurate Contact Response Analysis (ChACRA).

Daniel Burns, Vincenzo Venditti, Davit A Potoyan

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Integrating NMR and contact-response analysis reveals the allosteric network driving domain closure in Enzyme I.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. 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

3 authors.

Daniel BurnsRoy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States.ORCID 0000-0003-0739-2070
Vincenzo VendittiDepartment of Chemistry, Iowa State University, Ames, Iowa 50011, United States.ORCID 0000-0001-8734-0400
Davit A PotoyanDepartment of Chemistry, Iowa State University, Ames, Iowa 50011, United States.ORCID 0000-0002-5860-1699

Funding

Atomic-level characterization of self-regulatory mechanisms in large multidomain enzymesR35GM133488 · NIGMS · IOWA STATE UNIVERSITY · PI Vincenzo Venditti · 2019 to 2026
$2.9M
Multi-scale computational investigation of functions and mechanisms of protein-RNA phase separation.R35GM138243 · NIGMS · IOWA STATE UNIVERSITY · PI Davit POTOYAN · 2020 to 2026
$2.4M
NIGMS NIH HHS R35 GM133488NIGMS NIH HHS R35 GM138243
6 · The paper itself

Abstract

Decoding allostery at the atomic level is essential for understanding the relationship between a protein's sequence, structure, and dynamics. Recently, we have shown that decomposing temperature responses of inter-residue contacts can reveal allosteric couplings and provide useful insight into the functional dynamics of proteins. The details of this Chemically Accurate Contact Response Analysis (ChACRA) are presented here along with its application to two well-known allosteric proteins. The first protein, IGPS, is a model of ensemble allostery that lacks clear structural differences between the active and inactive states. We show that the application of ChACRA reveals the experimentally identified allosteric coupling between effector and active sites of IGPS. The second protein, ATCase, is a classic example of allostery with distinct active and inactive structural states. Using ChACRA, we directly identify the most significant residue level interactions underlying the enzyme's cooperative behavior. Both test cases demonstrate the utility of ChACRA's unsupervised machine learning approach for dissecting allostery at the residue level.

Indexed as

ProteinsAllosteric RegulationMolecular Dynamics SimulationProteins

Identifiers

PMID39038177
PMCPMC11840831

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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.