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dc.contributor.authorLamb, Audrey L.
dc.contributor.authorKappock, Joseph
dc.contributor.authorSilvaggi, Nicholas R.
dc.date.accessioned2016-11-18T19:18:56Z
dc.date.available2016-11-18T19:18:56Z
dc.date.issued2015-04
dc.identifier.citationAudrey L. Lamb, T. Joseph Kappock, Nicholas R. Silvaggi Biochim Biophys Acta. Author manuscript; available in PMC 2016 Oct 5. Published in final edited form as: Biochim Biophys Acta. 2015 Apr; 1854(4): 258–268. Published online 2014 Dec 29. doi: 10.1016/j.bbapap.2014.12.021en_US
dc.identifier.urihttp://hdl.handle.net/1808/22037
dc.description.abstractX-ray crystal structures propel biochemistry research like no other experimental method, since they answer many questions directly and inspire new hypotheses. Unfortunately, many users of crystallographic models mistake them for actual experimental data. Crystallographic models are interpretations, several steps removed from the experimental measurements, making it difficult for nonspecialists to assess the quality of the underlying data. Crystallographers mainly rely on “global” measures of data and model quality to build models. Robust validation procedures based on global measures now largely ensure that structures in the Protein Data Bank (PDB) are largely correct. However, global measures do not allow users of crystallographic models to judge the reliability of “local” features in a region of interest. Refinement of a model to fit into an electron density map requires interpretation of the data to produce a single “best” overall model. This process requires inclusion of most probable conformations in areas of poor density. Users who misunderstand this can be misled, especially in regions of the structure that are mobile, including active sites, surface residues, and especially ligands. This article aims to equip users of macromolecular models with tools to critically assess local model quality. Structure users should always check the agreement of the electron density map and the derived model in all areas of interest, even if the global statistics are good. We provide illustrated examples of interpreted electron density as a guide for those unaccustomed to viewing electron density.en_US
dc.publisherElsevieren_US
dc.subjectProtein structureen_US
dc.subjectX-ray crystallographyen_US
dc.subjectMolecular modelsen_US
dc.subjectElectron density mapsen_US
dc.subjectAtomic coordinate filesen_US
dc.subjectAtomic displacement parametersen_US
dc.titleYou are lost without a map: Navigating the sea of protein structuresen_US
dc.typeArticleen_US
kusw.kuauthorLamb, Audrey L.
kusw.kudepartmentMolecular Biosciences
dc.identifier.doi10.1016/j.bbapap.2014.12.021en_US
kusw.oaversionScholarly/refereed, author accepted manuscripten_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccess


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