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Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER

Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions t...

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Autores principales: Medina, Ana, Jiménez, Elisabet, Caballero, Iracema, Castellví, Albert, Triviño Valls, Josep, Alcorlo, Martin, Molina, Rafael, Hermoso, Juan A., Sammito, Massimo D., Borges, Rafael, Usón, Isabel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9629495/
https://www.ncbi.nlm.nih.gov/pubmed/36322413
http://dx.doi.org/10.1107/S2059798322009706
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author Medina, Ana
Jiménez, Elisabet
Caballero, Iracema
Castellví, Albert
Triviño Valls, Josep
Alcorlo, Martin
Molina, Rafael
Hermoso, Juan A.
Sammito, Massimo D.
Borges, Rafael
Usón, Isabel
author_facet Medina, Ana
Jiménez, Elisabet
Caballero, Iracema
Castellví, Albert
Triviño Valls, Josep
Alcorlo, Martin
Molina, Rafael
Hermoso, Juan A.
Sammito, Massimo D.
Borges, Rafael
Usón, Isabel
author_sort Medina, Ana
collection PubMed
description Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios.
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spelling pubmed-96294952022-11-14 Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER Medina, Ana Jiménez, Elisabet Caballero, Iracema Castellví, Albert Triviño Valls, Josep Alcorlo, Martin Molina, Rafael Hermoso, Juan A. Sammito, Massimo D. Borges, Rafael Usón, Isabel Acta Crystallogr D Struct Biol Ccp4 Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios. International Union of Crystallography 2022-10-20 /pmc/articles/PMC9629495/ /pubmed/36322413 http://dx.doi.org/10.1107/S2059798322009706 Text en © Medina, Jiménez et al. 2022 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Ccp4
Medina, Ana
Jiménez, Elisabet
Caballero, Iracema
Castellví, Albert
Triviño Valls, Josep
Alcorlo, Martin
Molina, Rafael
Hermoso, Juan A.
Sammito, Massimo D.
Borges, Rafael
Usón, Isabel
Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER
title Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER
title_full Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER
title_fullStr Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER
title_full_unstemmed Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER
title_short Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER
title_sort verification: model-free phasing with enhanced predicted models in arcimboldo_shredder
topic Ccp4
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9629495/
https://www.ncbi.nlm.nih.gov/pubmed/36322413
http://dx.doi.org/10.1107/S2059798322009706
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