The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
The structural coverage of the human proteome before and after AlphaFold
Open accessPublished version of a preprint
Abstract
The protein structure field is experiencing a revolution. From the increased throughput of techniques to determine experimental structures, to developments such as cryo-EM that allow us to find the structures of large protein complexes or, more recently, the development of artificial intelligence tools, such as AlphaFold, that can predict with high accuracy the folding of proteins for which the availability of homology templates is limited. Here we quantify the effect of the recently released AlphaFold database of protein structural models in our knowledge on human proteins. Our results indicate that our current baseline for structural coverage of 48%, considering experimentally-derived or template-based homology models, elevates up to 76% when including AlphaFold predictions. At the same time the fraction of dark proteome is reduced from 26% to just 10% when AlphaFold models are considered. Furthermore, although the coverage of disease-associated genes and mutations was near complete before AlphaFold release (69% of Clinvar pathogenic mutations and 88% of oncogenic mutations), AlphaFold models still provide an additional coverage of 3% to 13% of these critically important sets of biomedical genes and mutations. Finally, we show how the contribution of AlphaFold models to the structural coverage of non-human organisms, including important pathogenic bacteria, is significantly larger than that of the human proteome. Overall, our results show that the sequence-structure gap of human proteins has almost disappeared, an outstanding success of direct consequences for the knowledge on the human genome and the derived medical applications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“after AlphaFold2, the structural coverage of the human proteome increased from 48% to 76% of the total residues).131”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [131]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
UCSF Chimera—A visualization system for exploratory research and analysis
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20084 · Cited by 46,047
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
Comparative Protein Modelling by Satisfaction of Spatial Restraints
Šali, A., & Blundell, T. L. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1626 · Cited by 12,977
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099
Pfam: The protein families database in 2021
Mistry, J., Chuguransky, S., Williams, L., Qureshi, M., Salazar, G. A., Sonnhammer, E. L. L., Tosatto, S. C. E., Paladin, L., Raj, S., Richardson, L. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa913 · Cited by 7,452
UniProt: the universal protein knowledgebase in 2021
The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1100 · Cited by 6,372
Accurate prediction of protein structures and interactions using a 3-track network
Baek, M., DiMaio, F., Anishchenko, I., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., et al. (2021) · doi:10.1101/2021.06.14.448402 · Cited by 5,549
Flagged first, then by citations
Cited by
Sorted by citations
Dali server: structural unification of protein families
Holm, L. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac387 · Cited by 934
Terwilliger, T. C., Liebschner, D., Croll, T. I., Williams, C. J., McCoy, A. J., Poon, B. K., Afonine, P. V., Oeffner, R. D., Richardson, J. S., Read, R. J., et al. (2024) · Nature Methods · doi:10.1038/s41592-023-02087-4 · Cited by 411
Before and after AlphaFold2: An overview of protein structure prediction
Bertoline, L. M. F., Lima, A. N., Krieger, J. E., & Teixeira, S. K. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1120370 · Cited by 330
AlphaFold, Artificial Intelligence (AI), and Allostery
Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190
Intrinsic protein disorder and conditional folding in AlphaFoldDB
Piovesan, D., Monzon, A. M., & Tosatto, S. C. E. (2022) · Protein Science · doi:10.1002/pro.4466 · Cited by 160
Metadata
- Authors
- Porta-Pardo, E., Ruiz-Serra, V., Valentini, S., & Valencia, A.
- Affiliations
- University of Trento (IT)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Corresponding author
- Valencia, Alfonso
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2022-01-24
- Volume
- 18
- Issue
- 1
- Pages
- e1009818
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC8812986
- OpenAlex
- W4226027101
- Cited by
- 131
- References
- 59
- Citations by year
- 2026: 15 · 2025: 21 · 2024: 29 · 2023: 28 · 2022: 37
- FWCI
- 10.70
- Type
- journal article
- Language
- en
- Update notices
- new_version (2022-02-03)
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Iris (University of Trento) (submittedVersion, cc-by)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by)
- Funders
- “la Caixa” Foundation (LCF/BQ/PI18/11630003)
- Spanish Ministry of Science (RYC2019-026415-I)
- Institució Catalana de Recerca i Estudis Avançats
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- AlphaFold, protein structure prediction, structural coverage, human proteome, dark proteome, homology model, disease-associated mutations, oncogenic mutations, pathogenic bacteria, protein structure model
- MeSH terms
- Humans, Models, Molecular, Protein Folding, Proteome, Proteomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
