@article {162693, title = {IHMValidation: Assessment of Integrative Structure Models Deposited to the Protein Data Bank.}, journal = {J Mol Biol}, year = {2025}, month = {2025 Dec 18}, pages = {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 F{\"o}rster 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.

}, issn = {1089-8638}, doi = {10.1016/j.jmb.2025.169598}, author = {Zalevsky, Arthur O and Vallat, Brinda and Webb, Benjamin M and Tangmunarunkit, Hongsuda and Sekharan, Monica R and Shafaeibejestan, Aref and Ganesan, Sai and Sagendorf, Jared and Jeffries, Cy M and Trewhella, Jill and Graziadei, Andrea and Vizca{\'\i}no, Juan Antonio and Leitner, Alexander and Rappsilber, Juri and Peisach, Ezra and Flatt, Justin W and Young, Jasmine Y and Majila, Kartik and Viswanath, Shruthi and Kesselman, Carl and Hoch, Jeffrey C and Kurisu, Genji and Morris, Kyle L and Velankar, Sameer and Berman, Helen M and Burley, Stephen K and Sali, Andrej} } @article {93056, title = {CM1-driven assembly and activation of yeast γ-tubulin small complex underlies microtubule nucleation}, journal = {Elife}, volume = {10}, year = {2021}, month = {05/2021}, abstract = {

Microtubule (MT) nucleation is regulated by the γ-tubulin ring complex (γTuRC), conserved from yeast to humans. In Saccharomyces cerevisiae, γTuRC is composed of seven identical γ-tubulin small complex (γTuSC) sub-assemblies, which associate helically to template MT growth. γTuRC assembly provides a key point of regulation for the MT cytoskeleton. Here, we combine crosslinking mass spectrometry, X-ray crystallography, and cryo-EM structures of both monomeric and dimeric γTuSCs, and open and closed helical γTuRC assemblies in complex with Spc110p to elucidate the mechanisms of γTuRC assembly. γTuRC assembly is substantially aided by the evolutionarily conserved CM1 motif in Spc110p spanning a pair of adjacent γTuSCs. By providing the highest resolution and most complete views of any γTuSC assembly, our structures allow phosphorylation sites to be mapped, surprisingly suggesting that they are mostly inhibitory. A comparison of our structures with the CM1 binding site in the human γTuRC structure at the interface between GCP2 and GCP6 allows for the interpretation of significant structural changes arising from CM1 helix binding to metazoan γTuRC.

}, author = {Brilot, AF and Lyon, SA and Zelter, Alex and Viswanath, Shruthi and Maxwell, A and MacCoss, MJ and Muller, EJ and Sali, Andrej and Davis, TN and Agard, DA} } @article {85185, title = {Using Integrative Modeling Platform to Compute, Validate, and Archive a Model of a Protein Complex Structure.}, journal = {Protein Sci}, volume = {30}, year = {2021}, month = {2020 Nov 09}, pages = {250-261}, abstract = {

Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data-dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org). This article is protected by copyright. All rights reserved.

}, issn = {1469-896X}, doi = {10.1002/pro.3995}, author = {Saltzberg, Daniel J and Viswanath, Shruthi and Echeverria, Ignacia and Chemmama, Ilan E and Webb, Ben and Sali, Andrej} }