Journal article
Identification of Iron-Sulfur (Fe-S) Cluster and Zinc (Zn) Binding Sites Within Proteomes Predicted by DeepMind's AlphaFold2 Program Dramatically Expands the Metalloproteome Zachary J. Wehrspan dagger Robert T. McDonnell dagger and Adrian H. Elcock double up arrow
Journal of molecular biology, Vol.434(2), 167377
01/30/2022
DOI: 10.1016/j.jmb.2021.167377
PMCID: PMC8785651
PMID: 34838520
Abstract
DeepMind's AlphaFold2 software has ushered in a revolution in high quality, 3D protein structure prediction. In very recent work by the DeepMind team, structure predictions have been made for entire proteomes of twenty-one organisms, with >360,000 structures made available for download. Here we show that thousands of novel binding sites for iron-sulfur (Fe-S) clusters and zinc (Zn) ions can be identified within these predicted structures by exhaustive enumeration of all potential ligand-binding orientations. We demonstrate that AlphaFold2 routinely makes highly specific predictions of ligand binding sites: for example, binding sites that are comprised exclusively of four cysteine sidechains fall into three clusters, representing binding sites for 4Fe-4S clusters, 2Fe-2S clusters, or individual Zn ions. We show further: (a) that the majority of known Fe-S cluster and Zn binding sites documented in UniProt are recovered by the AlphaFold2 structures, (b) that there are occasional disputes between AlphaFold2 and UniProt with AlphaFold2 predicting highly plausible alternative binding sites, (c) that the Fe-S cluster binding sites that we identify in E. coli agree well with previous bioinformatics predictions, (d) that cysteines predicted here to be part of ligand binding sites show little overlap with those shown via chemoproteomics techniques to be highly reactive, and (e) that AlphaFold2 occasionally appears to build erroneous disulfide bonds between cysteines that should instead coordinate a ligand. These results suggest that AlphaFold2 could be an important tool for the functional annotation of proteomes, and the methodology presented here is likely to be useful for predicting other ligand-binding sites. (c) 2021 Elsevier Ltd. All rights reserved.
Details
- Title: Subtitle
- Identification of Iron-Sulfur (Fe-S) Cluster and Zinc (Zn) Binding Sites Within Proteomes Predicted by DeepMind's AlphaFold2 Program Dramatically Expands the Metalloproteome Zachary J. Wehrspan dagger Robert T. McDonnell dagger and Adrian H. Elcock double up arrow
- Creators
- Zachary J. Wehrspan - University of IowaRobert T. McDonnell - University of IowaAdrian H. Elcock - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of molecular biology, Vol.434(2), 167377
- DOI
- 10.1016/j.jmb.2021.167377
- PMID
- 34838520
- PMCID
- PMC8785651
- NLM abbreviation
- J Mol Biol
- ISSN
- 0022-2836
- eISSN
- 1089-8638
- Publisher
- Elsevier
- Number of pages
- 21
- Grant note
- R35 GM122466 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA Integrated DNA Technologies, Coralville, IA The University of Iowa
- Language
- English
- Date published
- 01/30/2022
- Academic Unit
- Physics and Astronomy; Biochemistry and Molecular Biology
- Record Identifier
- 9984288722002771
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