Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures

Helen M Berman, Paul D Adams, Alexandre Bonvin, Stephen K Burley, Bridget Carragher, Wah Chiu, Frank Dimaio, Thomas E Ferrin, Margaret J Gabanyi, Thomas D Goddard, Patrick R Griffin, Juergen Haas, Christian A Hanke, Jeffrey C Hoch, Gerhard Hummer, Genji Kurisu, Catherine L Lawson, Alexander Leitner, John L Markley

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards , building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here. Introduction When the Protein Data Bank (PDB) (Protein Data Bank, 1971) was first established in 1971, X-ray crystallography was the only method for determining three-dimensional structures of biological macromolecules at sufficient resolution to build atomic models. A decade later, structures of biomolecules in solution could also be determined by nuclear magnetic resonance (NMR) spectroscopy (Williamson et al., 1985). Recently, three-dimensional cryoelectron microscopy (3DEM) (Henderson et al., 1990) began to achieve unprecedented near-atomic resolution for large complex assemblies. Increasingly, investigators are also modeling structures based on data from more than one method (Rout and Sali, 2019). These integrative/hybrid approaches to structure determination consist of collecting information about a system using multiple experimental and computational methods, followed by integrative/hybrid modeling that converts this information into integrative/hybrid structure models. For succinctness, we will use the term integra-tive hereafter to refer to integrative/hybrid approaches, modeling, and models.
Original languageEnglish
Pages (from-to)1745-1759
JournalStructure
Volume27
Issue number12
DOIs
Publication statusPublished - Dec 2019

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