The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Bridging prediction and reality: Comprehensive analysis of experimental and AlphaFold 2 full-length nuclear receptor structures
Open accessPublished version of a preprint
Abstract
AlphaFold 2 has revolutionized protein structure prediction, yet systematic evaluations of its performance against experimental structures for specific protein families remain limited. Here we present the first comprehensive analysis comparing AlphaFold 2-predicted and experimental nuclear receptor structures, examining root-mean-square deviations, secondary structure elements, domain organization, and ligand-binding pocket geometry. While AlphaFold2 achieves high accuracy in predicting stable conformations with proper stereochemistry, it shows limitations in capturing the full spectrum of biologically relevant states, particularly in flexible regions and ligand-binding pockets. Statistical analysis reveals significant domain-specific variations, with ligand-binding domains showing higher structural variability (CV = 29.3%) compared to DNA-binding domains (CV = 17.7%). Notably, Alphafold 2 systematically underestimates ligand-binding pocket volumes and captures only single conformational states in homodimeric receptors where experimental structures show functionally important asymmetry. These findings provide critical insights for structure-based drug design targeting nuclear receptors and establish a framework for evaluating Alphafold 2 predictions across other protein families.
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.
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
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
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861
Highly accurate protein structure prediction for the human proteome
Tunyasuvunakool, K., Adler, J., Wu, Z., Green, T., Zielinski, M., Žídek, A., Bridgland, A., Cowie, A., Meyer, C., Laydon, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03828-1 · Cited by 3,025 · cited 2×
“By researchers in the structural biology community, the proposed solution to bridge this gap is the AlphaFold 2 (AF2) system, which combines computational algorithms and artificial intelligence to efficiently predict and build structural models [27,50,51,59].”
Burley, S. K., Bhikadiya, C., Bi, C., Bittrich, S., Chen, L., Crichlow, G. V., Christie, C. H., Dalenberg, K., Di Costanzo, L., Duarte, J. M., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1038 · Cited by 1,581
How significant is a protein structure similarity with TM-score = 0.5?
Xu, J., & Zhang, Y. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq066 · Cited by 1,142
Structure of the intact PPAR-γ–RXR-α nuclear receptor complex on DNA
Chandra, V., Huang, P., Hamuro, Y., Raghuram, S., Wang, Y., Burris, T. P., & Rastinejad, F. (2008) · Nature · doi:10.1038/nature07413 · Cited by 808
A structural biology community assessment of AlphaFold2 applications
Akdel, M., Pires, D. E. V., Pardo, E. P., Jänes, J., Zalevsky, A. O., Mészáros, B., Bryant, P., Good, L. L., Laskowski, R. A., Pozzati, G., et al. (2022) · Nature Structural & Molecular Biology · doi:10.1038/s41594-022-00849-w · Cited by 675
Predicting multiple conformations via sequence clustering and AlphaFold2
Wayment-Steele, H. K., Ojoawo, A., Otten, R., Apitz, J. M., Pitsawong, W., Hömberger, M., Ovchinnikov, S., Colwell, L., & Kern, D. (2024) · Nature · doi:10.1038/s41586-023-06832-9 · Cited by 545
Glucocorticoid receptor control of transcription: precision and plasticity via allostery
Weikum, E. R., Knuesel, M. T., Ortlund, E. A., & Yamamoto, K. R. (2017) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.152 · Cited by 533
Sampling alternative conformational states of transporters and receptors with AlphaFold2
del Alamo, D., Sala, D., Mchaourab, H. S., & Meiler, J. (2022) · eLife · doi:10.7554/elife.75751 · Cited by 511
Flagged first, then by citations
Research works printed but not linked: 47
- 10.1093/nar/28.1.235 · DOI · Paper page
- 10.1007/978-3-030-52321-3 · DOI
- 10.1021/jacsau.3c00188 · DOI
- 10.1038/s41467-017-00981-y · DOI
- 10.1016/j.cbpa.2008.07.001 · DOI
- 10.1107/S0907444909042073 · DOI · Paper page
- 10.1021/acs.jpcb.6b02057 · DOI
- 10.1093/nar/gkac1052 · DOI · Paper page
- 10.1074/jbc.C200420200 · DOI
- 10.1016/j.str.2022.04.005 · DOI · Paper page
- 10.1093/bioadv/vbae187 · DOI
- 10.1038/s41401-022-00938-y · DOI
- 10.1038/s41592-022-01685-y · DOI · Paper page
- 10.1073/pnas.2221745120 · DOI
- 10.1186/1472-6807-8-49 · DOI
- 10.1016/j.isci.2022.104496 · DOI
- 10.1093/bioinformatics/bts345 · DOI
- 10.1021/acs.jcim.2c00467 · DOI
- 10.1124/mol.112.079285 · DOI
- 10.1038/ncomms9013 · DOI
- 10.1124/mol.119.116806 · DOI
- 10.1038/nsmb.2778 · DOI · Paper page
- 10.1007/978-1-4939-9585-1_4 · DOI
- 10.1126/scisignal.2002515 · DOI
- 10.1038/s41598-024-60220-7 · DOI
- 10.1038/s41594-022-00914-4 · DOI
- 10.1074/jbc.M109.026682 · DOI
- 10.1021/acs.jctc.4c00222 · DOI
- 10.1530/JME-13-0173 · DOI
- 10.1093/bioinformatics/btac202 · DOI · Paper page
- 10.1002/(SICI)1097-0282(199603)38:3%3C305::AID-BIP4%E3.0.CO;2-Y · DOI
- 10.1038/nrd.2016.230 · DOI · Paper page
- 10.3389/fendo.2017.00016 · DOI
- 10.1016/j.str.2022.08.004 · DOI
- 10.3390/biom12070985 · DOI
- Team C.D.: Chai-1: decoding the molecular interactions of life. 2024. bioRxiv https://doi.org/10.1101/2024.10.10.615955. · DOI · Paper page
- 10.1021/jm500442z · DOI
- 10.3390/membranes12020229 · DOI
- 10.1210/me.2010-0083 · DOI
- 10.1038/s41586-021-03828-1 · DOI · Paper page
- 10.1093/nar/gkab1061 · DOI · Paper page
- 10.1002/prot.22613 · DOI
- 10.1080/07391102.2018.1559099 · DOI
- 10.1002/prot.20264 · DOI · Paper page
- 10.1073/pnas.2206737119 · DOI
- Zhorov B.S. and Dong K.: Pyrethroids in an alphafold2 model of the insect sodium channel. Insects 2022; 1310.3390/insects13080745. https://www.mdpi.com/2075-4450/13/8/745. · DOI
- 10.3389/fmolb.2023.1083575 · DOI
Metadata
- Authors
- Mazhibiyeva, A., Pham, T. T., Pats, K., Lukac, M., & Molnár, F.
- Affiliations
- Nazarbayev University (KZ)
- ITMO University (RU)
- Department of Computer Networks and Engineering, Hiroshima City University, 3-4-1 Oozukahigashi, Asaminami-ku, Hiroshima-shi, 731–3166, Japan
- Corresponding author
- Molnár, Ferdinand
- Venue
- Computational and Structural Biotechnology Journal
- Published
- 2025-01-01
- Volume
- 27
- Pages
- 1998-2013
- ISSN
- 2001-0370 (ISSN-L)
- PMC
- PMC12149446
- OpenAlex
- W4410398694
- Cited by
- 13
- References
- 11
- Citations by year
- 2026: 8 · 2025: 5
- FWCI
- 3.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Nazarbayev University Repository (Nazarbayev University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Nazarbayev University (091019CRP2108)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Keywords
- AlphaFold2, nuclear receptors, protein structure prediction, forecast evaluation, binding pocket, DNA-binding domain, conformational heterogeneity, structure-based drug design, full-length protein structure
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
