Molecular Dynamics of "Fuzzy" Transcriptional Activator-Coactivator Interactions

Overview

Journal PLoS Comput Biol

Specialty Biology

Date 2016 May 14

PMID 27175900

Citations 12

Authors

Natalie S Scholes

Robert O J Weinzierl

Affiliations

Soon will be listed here.

Abstract

Transcriptional activation domains (ADs) are generally thought to be intrinsically unstructured, but capable of adopting limited secondary structure upon interaction with a coactivator surface. The indeterminate nature of this interface made it hitherto difficult to study structure/function relationships of such contacts. Here we used atomistic accelerated molecular dynamics (aMD) simulations to study the conformational changes of the GCN4 AD and variants thereof, either free in solution, or bound to the GAL11 coactivator surface. We show that the AD-coactivator interactions are highly dynamic while obeying distinct rules. The data provide insights into the constant and variable aspects of orientation of ADs relative to the coactivator, changes in secondary structure and energetic contributions stabilizing the various conformers at different time points. We also demonstrate that a prediction of α-helical propensity correlates directly with the experimentally measured transactivation potential of a large set of mutagenized ADs. The link between α-helical propensity and the stimulatory activity of ADs has fundamental practical and theoretical implications concerning the recruitment of ADs to coactivators.

Citing Articles

Conservation of function without conservation of amino acid sequence in intrinsically disordered transcriptional activation domains.

LeBlanc C, Stefani J, Soriano M, Lam A, Zintel M, Kotha S bioRxiv. 2024; .

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Fuzzy recognition by the prokaryotic transcription factor HigA2 from Vibrio cholerae.

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Commonly asked questions about transcriptional activation domains.

Udupa A, Kotha S, Staller M Curr Opin Struct Biol. 2023; 84:102732.

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Transcriptional co-activators: emerging roles in signaling pathways and potential therapeutic targets for diseases.

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Drugging Fuzzy Complexes in Transcription.

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