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Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2449))

Abstract

Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the underpinning data, a study and its conclusions cannot be reproduced at any stage of evaluation, pre- or post-publication. Likewise, an independent study without its own underpinning data also cannot be reproduced let alone be considered a replicate of the first study. The PDB is a modern marvel of achievement providing an organized open access to depositor and user of the data held there opening numerous applications. Methods for modeling protein structures and for determination of structures are still improving their precision, and artifacts of the method exist. So their accuracy is realized if they are reproduced by other methods. It is on such foundations that reproducible data mining is based. Data rates are expanding considerably be they at synchrotrons, the X-ray free electron lasers (XFELs), electron cryomicroscopes (cryoEM), or at the neutron facilities. The work of a person as a referee or user with a narrative and its underpinning data may well be complemented in future by artificial intelligence with machine learning, the former for specific refereeing and the latter for the more general validation, both ideally before publication. Examples are described involving rhenium theranostics, the anti-cancer platins and the SARS-CoV-2 main protease.

I dedicate this book chapter to Emeritus Professor Peter Main, University of York, and Dr Margaret Adams, University of Oxford. Peter taught me in the final year option in my physics degree course on molecular biophysics describing the multiple methods to elucidate biological structure and function relationships: protein crystallography, solution X-ray scattering, electron microscopy, fiber diffraction. Today this would be called integrated structural biology. Margaret was my DPhil supervisor and she taught me many things within enzyme crystallography and chemistry.

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Acknowledgments

JRH, as Editor in Chief of IUCr Journals 1996–2005 saw in detail the exemplary checks undertaken by Acta Crystallographica Section C co-editors, which included Dr Madeleine Helliwell, using the checkcif report as well as the chance to scrutinize with their own calculations the underpinning processed structure factors and derived atomic coordinates of each submitted article. Thus JRH is very grateful to all colleagues involved with Acta Crystallographica Section C at the time notably Professor Syd Hall and also Dr Madeleine Helliwell for many discussions. I am very grateful to other members of the IUCr Diffraction Data Deposition Working Group (2011–2017) which led to the Final Report held here https://www.iucr.org/resources/data/dddwg/final-report: Steve Androulakis (Australia), Sol Gruner (USA), Loes Kroon-Batenburg (Netherlands), Brian McMahon (UK), D. Marian Szebenyi (USA), Tom Terwilliger (USA), Edgar Weckert (Germany), John Westbrook (USA) and Heinz-Josef Weyer (sadly deceased, Switzerland). The work of the IUCr DDDWG has now been included in the IUCr’s Committee on Data, formed in 2017; see https://www.iucr.org/iucr/governance/advisory-committees/committee-on-data . I am very grateful to Alice Brink, Rudolf Dimper, Robbie Joosten, Loes Kroon-Batenburg, Brian McMahon, Andy Thompson and John Westbrook for their specific comments and suggestions on this chapter. These are however my own personal perspectives on all these developments and any errors are purely my own. I am very sad to report that John Westbrook passed away in October 2021. 

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Helliwell, J.R. (2022). Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 2449. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2095-3_10

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