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PreprintCited by 1Protein Structure and DynamicsGenomics and Chromatin DynamicsMachine Learning in Bioinformatics

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Assessment of machine-learning predictions for MED25 ACID domain interactions with transactivation domains

Open access
Monté, Didier, Lens, Zoé, Dewitte, Frédérique, Villeret, Vincent, Verger, Alexis·2023·FEBS Letters
DOI 10.1101/2023.11.30.569364

Preprint — published as 10.1002/1873-3468.14837

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Abstract

Human Mediator complex subunit MED25 binds transactivation domains (TADs) present in various cellular and viral proteins using two binding interfaces found on opposite sides of its ACID domain, and referenced as H1 and H2. Here, we use and compare deep learning methods to characterize Human MED25-TADs interfaces and assess the predicted models to published experimental data. For the H1 interface, AlphaFold produces predictions with high reliability scores that agree well with experimental data, while the H2 interface predictions appear inconsistent, preventing reliable binding modes. Despite these limitations, we experimentally assess the validity of Lana-1 and IE62 MED25 interface predictions. AlphaFold predictions also suggest the existence of a unique hydrophobic pocket for Arabidopsis MED25 ACID domain.

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Metadata

Authors
Monté, D., Lens, Z., Dewitte, F., Villeret, V., & Verger, A.
Affiliations
Centre National de la Recherche Scientifique (FR)
Corresponding author
Verger, Alexis
ORCID
Venue
FEBS Letters
Publisher
openRxiv
Published
2023-11-30
Volume
598
Issue
7
Pages
758-773
ISSN
0014-5793 (ISSN-L)
DOI
10.1101/2023.11.30.569364
OpenAlex
W4392371013
Cited by
1
References
2
Citations by year
2025: 1
FWCI
0.14
Type
journal article
Language
en
Open access
Locations
  • FEBS Letters (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
Keywords
MED25, Mediator complex, transactivation domain, protein-protein interaction, AlphaFold, deep learning protein structure prediction, viral transcriptional activator, LANA-1, hydrophobic pocket, Arabidopsis
MeSH terms
Humans, Transcription Factors, Viral Envelope Proteins, Reproducibility of Results, Transcriptional Activation, Trans-Activators, Immediate-Early Proteins, Mediator Complex

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