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dc.contributor.authorOeffner, Robert
dc.contributor.authorAfonine, Pavel V
dc.contributor.authorMillán, Claudia
dc.contributor.authorSammito, Massimo
dc.contributor.authorUsón, Isabel
dc.contributor.authorRead, Randy
dc.contributor.authorMcCoy, Airlie
dc.description.abstractMolecular-replacement phasing of macromolecular crystal structures is often fast, but if a molecular-replacement solution is not immediately obtained the crystallographer must judge whether to pursue molecular replacement or to attempt experimental phasing as the quickest path to structure solution. The introduction of the expected log-likelihood gain [eLLG; McCoy et al. (2017), Proc. Natl Acad. Sci. USA, 114, 3637-3641] has given the crystallographer a powerful new tool to aid in making this decision. The eLLG is the log-likelihood gain on intensity [LLGI; Read & McCoy (2016), Acta Cryst. D72, 375-387] expected from a correctly placed model. It is calculated as a sum over the reflections of a function dependent on the fraction of the scattering for which the model accounts, the estimated model coordinate error and the measurement errors in the data. It is shown how the eLLG may be used to answer the question `can I solve my structure by molecular replacement?'. However, this is only the most obvious of the applications of the eLLG. It is also discussed how the eLLG may be used to determine the search order and minimal data requirements for obtaining a molecular-replacement solution using a given model, and for decision making in fragment-based molecular replacement, single-atom molecular replacement and likelihood-guided model pruning.
dc.description.sponsorshipRobert D. Oeffnera, Pavel Afonineb, Claudia Millánc, Massimo Sammitoc, Isabel Usóncd, Randy J. Reada* and Airlie J. McCoye* aHaematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge, Cambs, CB2 0XY, United Kingdom b Lawrence Berkeley National Laboratory, One Cyclotron Road, BLDG 64R0121, Berkeley, CA, 94720, United States cCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac, 15, Barcelona, 08028, Spain dICREA, Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys, 23, Barcelona, E-08003, Spain eHaematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge, Cambs, CB20XY, United Kingdom Correspondence email:; Funding information Wellcome Trust (grant No. 082961/Z/07/Z to Randy J. Read); BBSRC (grant No. BB/L006014/1 to Randy J. Read; bursary No. BB/L006014/1 to Claudia Millán, Massimo Sammito); Spanish Ministry of Economy and Competitiveness (grant No. BIO2015-64216-P to Isabel Usón; grant No. BIO2013-49604-EXP to Isabel Usón; grant No. MDM2014-0435-01 to Isabel Usón; scholarship No. BES-2015-071397 to Claudia Millán).
dc.publisherInternational Union of Crystallography (IUCr)
dc.rightsAttribution 4.0 International
dc.subjectEukaryotic Initiation Factor-2
dc.subjectCrystallography, X-Ray
dc.subjectLikelihood Functions
dc.subjectDecision Making
dc.subjectProtein Conformation
dc.subjectModels, Molecular
dc.subjectProtein Domains
dc.titleOn the application of the expected log-likelihood gain to decision making in molecular replacement.
prism.issueIdentifierPt 4
prism.publicationNameActa Crystallogr D Struct Biol
dc.contributor.orcidOeffner, Robert [0000-0003-3107-2202]
dc.contributor.orcidMillán, Claudia [0000-0002-9283-2220]
dc.contributor.orcidSammito, Massimo [0000-0002-8346-9247]
dc.contributor.orcidRead, Randy [0000-0001-8273-0047]
rioxxterms.typeJournal Article/Review
pubs.funder-project-idBiotechnology and Biological Sciences Research Council (BB/L006014/1)
pubs.funder-project-idWellcome Trust (082961/Z/07/A)
pubs.funder-project-idNational Institutes of Health (NIH) (via University of California) (6801943)
pubs.funder-project-idNational Institutes of Health (NIH) (via University of California) (6801943)
pubs.funder-project-idWellcome Trust (082961/Z/07/Z)
pubs.funder-project-idNational Institute of General Medical Sciences (P01GM063210)

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Attribution 4.0 International
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