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Integrative Structural Biology in the Era of Accurate Structure Prediction
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Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy-applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure-function relationships.
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“The programs were also shown to accurately assess their confidence at the level of individual residues and interdomain contacts (27,28,62).”
From AI-based structure prediction empowers integrative structural analysis of human nuclear pores (2022) · cites this paper as [62]
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“However, AlphaFold and RoseTTAfold have recently demonstrated unprecedented accuracy in predicting structures of monomeric proteins (27,28,(61)(62)(63)(64)(65)(66) and complexes (35,62,67,68).”
From AI-based structure prediction empowers integrative structural analysis of human nuclear pores (2022) · cites this paper as [62]
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AI-based structure prediction empowers integrative structural analysis of human nuclear pores
Mosalaganti, S., Obarska-Kosinska, A., Siggel, M., Taniguchi, R., Turoňová, B., Zimmerli, C. E., Buczak, K., Schmidt, F. H., Margiotta, E., Mackmull, M.-T., et al. (2022) · Science · doi:10.1126/science.abm9506 · Cited by 355
AlphaFold2 Can Predict Single-Mutation Effects
McBride, J. M., Polev, K., Abdirasulov, A., Reinharz, V., Grzybowski, B. A., & Tlusty, T. (2023) · Physical Review Letters · doi:10.1103/physrevlett.131.218401 · Cited by 87
Lindorff-Larsen, K., & Kragelund, B. B. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167196 · Cited by 85
Varadi, M., Nair, S., Sillitoe, I., Tauriello, G., Anyango, S., Bienert, S., Borges, C., Deshpande, M., Green, T., Hassabis, D., et al. (2022) · GigaScience · doi:10.1093/gigascience/giac118 · Cited by 32
Varadi, M., Bordin, N., Orengo, C., & Velankar, S. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102543 · Cited by 29
Metadata
- Authors
- Masrati, G., Landau, M., Ben-Tal, N., Lupas, A., Kosloff, M., & Kosinski, J.
- Affiliations
- Tel Aviv University (IL)
- Technion – Israel Institute of Technology (IL)
- Max Planck Institute for Developmental Biology (DE)
- University of Haifa (IL)
- Corresponding author
- Lupas, Andrei
- Kosloff, Mickey
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 2021-10
- Volume
- 433
- Issue
- 20
- Pages
- 167127
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W3181374387
- Cited by
- 53
- References
- 213
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 8 · 2023: 9 · 2022: 21 · 2021: 7
- FWCI
- 1.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Molecular Biology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Desy Publications Database (Deutsches Elektronen-Synchrotron DESY) (submittedVersion, other-oa)
- Funders
- Max-Planck-Gesellschaft
- Tel Aviv University
- Canadian Institutes of Health Research
- BMBF Berlin
- International Development Research Centre
- Azrieli Foundation (3512/19)
- Israel Science Foundation
- Bundesministerium für Bildung und Forschung (FKZ 031L0100)
- 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 › Receptor Mechanisms and Signaling
- Keywords
- integrative structural biology, protein structure prediction, AlphaFold2, macromolecular structure determination, protein complexes, structural polymorphism, structure-function relationship
- MeSH terms
- Animals, Humans, Models, Molecular, Protein Conformation, Proteins, Crystallography, X-Ray, Nuclear Magnetic Resonance, Biomolecular
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.
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