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Protein structure prediction: when is it useful?
Open accessAbstract
Computationally predicted three-dimensional structure of protein molecules has demonstrated the usefulness in many areas of biomedicine, ranging from approximate family assignments to precise drug screening. For nearly 40 years, however, the accuracy of the predicted models has been dictated by the availability of close structural templates. Progress has recently been achieved in refining low-resolution models closer to the native ones; this has been made possible by combining knowledge-based information from multiple sources of structural templates as well as by improving the energy funnel of physics-based force fields. Unfortunately, there has been no essential progress in the development of techniques for detecting remotely homologous templates and for predicting novel protein structures.
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“Very high confidence predictions in the metagenomic atlas are expected to often be reliable at a resolution sufficient for insight similar to experimentally determined structures, such as into the biochemistry of active sites (61);”
From Evolutionary-scale prediction of atomic level protein structure with a language model (2022) · cites this paper as [61]
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Cites
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
I-TASSER server for protein 3D structure prediction
Zhang, Y. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-40 · Cited by 5,124
Self-citationTM-align: a protein structure alignment algorithm based on the TM-score
Zhang, Y. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki524 · Cited by 3,774
Self-citationThe Universal Protein Resource (UniProt)
Bairoch, A. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki070 · Cited by 3,774
Scoring function for automated assessment of protein structure template quality
Zhang, Y., & Skolnick, J. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20264 · Cited by 2,392
Self-citationThe Universal Protein Resource (UniProt) in 2010
The UniProt Consortium (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp846 · Cited by 1,412
LGA: a method for finding 3D similarities in protein structures
Zemla, A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg571 · Cited by 1,069
The Universal Protein Resource (UniProt)
The UniProt Consortium (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm895 · Cited by 824
LOMETS: A local meta-threading-server for protein structure prediction
Wu, S., & Zhang, Y. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm251 · Cited by 794
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I-TASSER: a unified platform for automated protein structure and function prediction
Roy, A., Küçükural, A., & Zhang, Y. (2010) · Nature Protocols · doi:10.1038/nprot.2010.5 · Cited by 6,212
Self-citationEvolutionary-scale prediction of atomic level protein structure with a language model
Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · doi:10.1101/2022.07.20.500902 · Cited by 5,990
Improved protein structure prediction using potentials from deep learning
Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., Žídek, A., Nelson, A. W. R., Bridgland, A., et al. (2020) · Nature · doi:10.1038/s41586-019-1923-7 · Cited by 3,378
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
I-TASSER server: new development for protein structure and function predictions
Yang, J., & Zhang, Y. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv342 · Cited by 2,486
Self-citationHow 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
Self-citationXu, D. H., & Zhang, Y. (2011) · Biophysical Journal · doi:10.1016/j.bpj.2011.10.024 · Cited by 1,039
Self-citationYang, J., Roy, A., & Zhang, Y. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt447 · Cited by 1,035
Self-citationMolecular dynamics simulations: advances and applications
Gelpí, J. L., Hospital, A., Goñi, R., & Orozco, M. (2015) · Advances and Applications in Bioinformatics and Chemistry · doi:10.2147/aabc.s70333 · Cited by 996
COFACTOR: an accurate comparative algorithm for structure-based protein function annotation
Roy, A., Yang, J., & Zhang, Y. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks372 · Cited by 703
Self-citationZhang, C., Freddolino, L., & Zhang, Y. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx366 · Cited by 606
Self-citationZheng, W. H., Zhang, C., Li, Y., Pearce, R., Bell, E. W., & Zhang, Y. (2021) · Cell Reports Methods · doi:10.1016/j.crmeth.2021.100014 · Cited by 588
Self-citationSingh, R. K., Tiwari, M. K., Singh, R., & Lee, J.-K. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms14011232 · Cited by 452
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Zhang, J., Yu, L., & Zhang, Y. (2011) · Structure · doi:10.1016/j.str.2011.09.022 · Cited by 339
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Raval, A., Piana, S., Eastwood, M. P., Dror, R. O., & Shaw, D. E. (2012) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24098 · Cited by 255
Zhang, J., & Zhang, Y. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015386 · Cited by 238
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Gallicchio, E., Lapelosa, M., & Levy, R. M. (2010) · Journal of Chemical Theory and Computation · doi:10.1021/ct1002913 · Cited by 158
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Self-citationLyons, J., Dehzangi, A., Heffernan, R., Sharma, A. K., Paliwal, K. K., Sattar, A., Zhou, Y., & Yang, Y. (2014) · Journal of Computational Chemistry · doi:10.1002/jcc.23718 · Cited by 145
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Self-citationLi, Y., & Zhang, Y. (2009) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22380 · Cited by 131
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Nishi, H., Tyagi, M. G., Teng, S., Shoemaker, B. A., Hashimoto, K., Alexov, E. G., Wuchty, S., & Panchenko, A. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066273 · Cited by 117
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Zheng, W. H., Wuyun, Q., Li, Y., Liu, Q., Zhou, X., Peng, C., Zhu, Y., Freddolino, L., & Zhang, Y. (2025) · Nature Biotechnology · doi:10.1038/s41587-025-02654-4 · Cited by 129
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Zhang, C., Zheng, W., Freddolino, L., & Zhang, Y. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.03.004 · Cited by 80
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Lee, H. S., & Zhang, Y. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.23165 · Cited by 82
Self-citationZhao, Y., Zeng, C., & Massiah, M. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0124377 · Cited by 79
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Ray, A., Lindahl, E. R., & Wallner, B. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq581 · Cited by 78
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Shukla, R., & Tripathi, T. (2021) · Springer eBooks · doi:10.1007/978-981-15-8936-2_12 · Cited by 80
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Metadata
- Authors
- Zhang, Y.
- Affiliations
- University of Kansas (US)
- Corresponding author
- Zhang, Yang
- ORCID
- Zhang, Yang
- Venue
- Current Opinion in Structural Biology
- Publisher
- Elsevier BV
- Published
- 2009-04
- Volume
- 19
- Issue
- 2
- Pages
- 145-155
- ISSN
- 0959-440X (ISSN-L)
- PMC
- PMC2673339
- OpenAlex
- W2140564438
- Cited by
- 277
- References
- 57
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 1 · 2023: 7 · 2022: 9 · 2021: 17 · 2020: 16 · 2019: 21 · 2018: 14 · 2017: 22 · 2016: 16 · 2015: 22 · 2014: 18 · 2013: 23 · 2012: 24
- FWCI
- 2.09
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Current Opinion in Structural Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- KU ScholarWorks (University of Kansas) (submittedVersion, cc-by-nc-nd)
- Funders
- National Institute of General Medical Sciences (R01GM083107)
- 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
- protein structure prediction, template-based structure prediction, structural templates, knowledge-based potentials, force fields, remote homology detection, drug screening
- MeSH terms
- Algorithms, Computer Simulation, Humans, Models, Molecular, Protein Conformation, Proteins, Structure-Activity Relationship, Computational Biology, Databases, Protein
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 ›
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