Assessing the utility of CASP14 models for molecular replacement.


Journal

Proteins
ISSN: 1097-0134
Titre abrégé: Proteins
Pays: United States
ID NLM: 8700181

Informations de publication

Date de publication:
12 2021
Historique:
revised: 20 07 2021
received: 18 06 2021
accepted: 27 07 2021
pubmed: 14 8 2021
medline: 26 2 2022
entrez: 13 8 2021
Statut: ppublish

Résumé

The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log-likelihood-gain (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

Identifiants

pubmed: 34387010
doi: 10.1002/prot.26214
pmc: PMC8881082
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1752-1769

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 209407/Z/17/Z
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/S007105/1
Pays : United Kingdom

Informations de copyright

© 2021 The Authors. Proteins: Structure, Function, and Bioinformatics published by Wiley Periodicals LLC.

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Auteurs

Claudia Millán (C)

Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, UK.

Ronan M Keegan (RM)

Department of Scientific Computing, Science and Technologies Facilities Council, UK Research and Innovation, Oxfordshire, Didcot, UK.

Joana Pereira (J)

Max Planck Institute for Developmental Biology, Tübingen, Germany.
Biozentrum, University of Basel, Basel, Switzerland.

Massimo D Sammito (MD)

Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, UK.

Adam J Simpkin (AJ)

Institute of Systems, Molecular and Integrative Biology, Liverpool, UK.

Airlie J McCoy (AJ)

Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, UK.

Andrei N Lupas (AN)

Max Planck Institute for Developmental Biology, Tübingen, Germany.

Marcus D Hartmann (MD)

Max Planck Institute for Developmental Biology, Tübingen, Germany.

Daniel J Rigden (DJ)

Institute of Systems, Molecular and Integrative Biology, Liverpool, UK.

Randy J Read (RJ)

Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge, UK.

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