ModelCIF: An Extension of PDBx/mmCIF Data Representation for Computed Structure Models
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Abstract
ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery of Findable, Accessible, Interoperable, and Reusable (FAIR) data to users worldwide. ModelCIF describes the specific set of attributes and metadata associated with macromolecular structures modeled by solely computational methods and provides an extensible data representation for deposition, archiving, and public dissemination of predicted three-dimensional (3D) models of macromolecules. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined 3D structures of macromolecules and associated metadata. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described.
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Cites
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- Authors
- Vallat, B., Tauriello, G., Bienert, S., Haas, J., Webb, B. M., Žídek, A., Zheng, W., Peisach, E., Piehl, D. W., Anischanka, I., Sillitoe, I., Tolchard, J., Varadi, M., Baker, D., Orengo, C., Zhang, Y., Hoch, J. C., Kurisu, G., Patwardhan, A., Velankar, S., Burley, S. K., Sali, A., Schwede, T., Berman, H. M., & Westbrook, J. D.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- SIB Swiss Institute of Bioinformatics (CH)
- University of California, San Francisco (US)
- Google DeepMind (United Kingdom) (GB)
- University of Michigan (US)
- University of Washington (US)
- University College London (GB)
- European Bioinformatics Institute (GB)
- Howard Hughes Medical Institute (US)
- University of Connecticut (US)
- Institute for Protein Research, The University of Osaka (JP)
- Corresponding author
- Vallat, Brinda
- ORCID
- Vallat, Brinda
- Tauriello, Gerardo
- Bienert, Stefan
- Haas, Juergen
- Webb, Benjamin M.
- Žídek, Augustin
- Zheng, Wei
- Peisach, Ezra
- Piehl, Dennis W.
- Sillitoe, Ian
- Tolchard, James
- Baker, David
- Orengo, Christine
- Zhang, Yang
- Hoch, Jeffrey C.
- Kurisu, Genji
- Patwardhan, Ardan
- Velankar, Sameer
- Burley, Stephen K.
- Schwede, Torsten
- Berman, Helen M.
- Westbrook, John D.
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 2023-07
- Volume
- 435
- Issue
- 14
- Pages
- 168021
- ISSN
- 0022-2836 (ISSN-L)
- PMC
- PMC10293049
- OpenAlex
- W4321483489
- Cited by
- 26
- References
- 5
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 8 · 2023: 8
- FWCI
- 1.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Molecular Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion, cc-by)
- edoc (University of Basel) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- Japan Agency for Medical Research and Development (22ama121001)
- Japan Science and Technology Agency (JPMJND2205)
- US Department of Energy (DE-SC0019749)
- National Science Foundation (DBI-2112967, DBI-1756250, DBI-1756248, DBI-1832184, DBI-2129634, DBI-2019297, ACI-1548562, DBI-2112966)
- DeepMind (R01GM109046)
- Swiss Institute of Bioinformatics
- National Institute of Allergy and Infectious Diseases
- National Cancer Institute
- National Institute of General Medical Sciences
- National Institutes of Health (R01GM133198, R01GM083960, P41GM109824, R01GM109046, DBI-2112967, DBI-1756250)
- Biotechnology and Biological Sciences Research Council (BB/W017970/1, BB/S020071/1, BB/V004247/1, BB/S020144/1)
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Keywords
- FAIR data, data standards, metadata, wwPDB, data governance
- MeSH terms
- Protein Conformation, Software, Databases, Protein, Macromolecular Substances
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