IHMValidation: Assessment of Integrative Structure Models Deposited to the Protein Data Bank

Arthur O Zalevsky; Brinda Vallat; Benjamin M Webb; Hongsuda Tangmunarunkit; Monica R Sekharan; Aref Shafaeibejestan; Sai Ganesan; Jared Sagendorf; Cy M Jeffries; Jill Trewhella; Andrea Graziadei; Juan Antonio Vizcaíno; Alexander Leitner; Juri Rappsilber; Ezra Peisach; Justin W Flatt; Jasmine Y Young; Kartik Majila; Shruthi Viswanath; Carl Kesselman; Jeffrey C Hoch; Genji Kurisu; Kyle L Morris; Sameer Velankar; Helen M Berman; Stephen K Burley; Andrej Sali

doi:10.1016/j.jmb.2025.169598

IHMValidation: Assessment of Integrative Structure Models Deposited to the Protein Data Bank

J Mol Biol. 2025 Dec 18:169598. doi: 10.1016/j.jmb.2025.169598. Online ahead of print.

Authors

Arthur O Zalevsky¹, Brinda Vallat², Benjamin M Webb³, Hongsuda Tangmunarunkit⁴, Monica R Sekharan⁵, Aref Shafaeibejestan⁴, Sai Ganesan³, Jared Sagendorf³, Cy M Jeffries⁶, Jill Trewhella⁷, Andrea Graziadei⁸, Juan Antonio Vizcaíno⁹, Alexander Leitner¹⁰, Juri Rappsilber¹¹, Ezra Peisach⁵, Justin W Flatt⁵, Jasmine Y Young⁵, Kartik Majila¹², Shruthi Viswanath¹², Carl Kesselman⁴, Jeffrey C Hoch¹³, Genji Kurisu¹⁴, Kyle L Morris¹⁵, Sameer Velankar¹⁶, Helen M Berman¹⁷, Stephen K Burley¹⁸, Andrej Sali¹⁹

Affiliations

¹ Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, the Quantitative Biosciences Institute (QBI), and the Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94157, USA. Electronic address: arthur.zalevsky@rcsb.org.
² Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Rutgers Cancer Institute, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA. Electronic address: brinda.vallat@rcsb.org.
³ Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, the Quantitative Biosciences Institute (QBI), and the Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94157, USA.
⁴ Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
⁵ Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
⁶ European Molecular Biology Laboratory, Hamburg Unit, c/o Deutsches Elektronen-Synchrotron, Notkestraße 85, 22607 Hamburg, Germany; Ilse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Be'er Sheva 8410501, Israel.
⁷ School of Life and Environmental Sciences, University of Sydney, NSW 2006, Australia; Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA.
⁸ Human Technopole, Via Rita Levi Montalcini 1, 20157 Milano, Italy.
⁹ European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust, Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
¹⁰ Institute of Molecular Systems Biology, Department of Biology, ETH Zürich, 8093 Zurich, Switzerland.
¹¹ Technische Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany; Si-M/""Der Simulierte Mensch"", a Science Framework of Technische Universität Berlin and Charité - Universitätsmedizin Berlin, Berlin, Germany.
¹² National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka 560065, India.
¹³ Biological Magnetic Resonance Data Bank, Department of Molecular Biology and Biophysics, University of Connecticut, Farmington, CT 06030-3305, USA.
¹⁴ Protein Data Bank Japan, Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan.
¹⁵ Electron Microscopy Data Bank, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK.
¹⁶ Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK.
¹⁷ Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.
¹⁸ Research Collaboratory for Structural Bioinformatics Protein Data Bank and the Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Rutgers Cancer Institute, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, La Jolla, CA 92093, USA; Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
¹⁹ Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, the Quantitative Biosciences Institute (QBI), and the Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94157, USA. Electronic address: sali@salilab.org.

PMID: 41421450
DOI: 10.1016/j.jmb.2025.169598

Abstract

PDB-IHM is a branch of the Protein Data Bank (PDB), a Worldwide Protein Data Bank (wwPDB) Core Archive, that expands its scope by allowing for additional biomolecular structure representations and types of experimental information (i.e., integrative/hybrid structure models). As of October 2025, PDB-IHM contained 374 entries, benefitting from multi-scale and multi-state representations and 17 types of experimental data. These structure models are assigned PDB accession codes and are archived alongside other experimental structures in the PDB. Rigorous interpretation of a structure model requires assessment of underlying data quality, consistency with the input data, and estimates of positional uncertainty of its components. Herein, we present the IHMValidation pipeline (https://validate.pdb-ihm.org; https://github.com/salilab/IHMValidation) based on recommendations from the wwPDB Integrative Methods Task Force plus the small-angle scattering (SAS), chemical crosslinking mass spectrometry (crosslinking-MS), and cryo-electron microscopy and tomography (3DEM) communities. The IHMValidation report (available in both PDF and HTML formats) comprises six sections: (i) overview; (ii) model details; (iii) data quality assessments; (iv) local geometry assessments (i.e., model quality); (v) fit of the model to the data used to generate it; and (vi) fit of the model to the data used for validation. Future expansions of the IHMValidation pipeline will: (i) reflect recommendations coming from additional experimental communities, including Förster resonance energy transfer (FRET) and hydrogen/deuterium exchange MS (HDX-MS); (ii) include other validation criteria, such as Bayesian likelihoods for the data; and (iii) represent estimates of structure model uncertainty based on the variation among alternative models satisfying input data.

Keywords: Protein Data Bank (PDB); Small-angle X-ray scattering (SAXS); crosslinking mass spectrometry (crosslinking-MS); integrative modeling; three-dimensional cryo-electron microscopy (3DEM).

Grants and funding

R01 GM157729/GM/NIGMS NIH HHS/United States