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On the application of the expected log-likelihood gain to decision making in molecular replacement

Molecular-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....

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Detalles Bibliográficos
Autores principales: Oeffner, Robert D., Afonine, Pavel V., Millán, Claudia, Sammito, Massimo, Usón, Isabel, Read, Randy J., McCoy, Airlie J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5892874/
https://www.ncbi.nlm.nih.gov/pubmed/29652252
http://dx.doi.org/10.1107/S2059798318004357
Descripción
Sumario:Molecular-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.