Evidence map›Paper›PMID 36322413›Full record

ArticleActa crystallographica. Section D, Structural biology2022

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

Ana Medina, Elisabet Jiménez, Iracema Caballero, Albert Castellví, Josep Triviño Valls, Martin Alcorlo, Rafael Molina, Juan A Hermoso, Massimo D Sammito, Rafael Borges and 1 more

Abstract read
In one paragraph

Article in Acta crystallographica. Section D, Structural biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. AlphaFold-guided molecular replacement for solving challenging crystal structures.Acta crystallographica. Section D, Structural biology · 2025
    Article
  2. ARCIMBOLDO at low resolution: Verification for coiled coils and globular proteins.Protein science : a publication of the Protein Society · 2024
    Article
  3. AlphaFold two years on: Validation and impact.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Article
  5. Modes and model building in SHELXE.Acta crystallographica. Section D, Structural biology · 2024
    Article
  6. Journal of applied crystallography · 2023
    Article
  7. Review
  8. Predicted models and CCP4.Acta crystallographica. Section D, Structural biology · 2023
    Article
  9. The CCP4 suite: integrative software for macromolecular crystallography.Acta crystallographica. Section D, Structural biology · 2023
    Article
  10. Accelerating crystal structure determination with iterative AlphaFold prediction.Acta crystallographica. Section D, Structural biology · 2023
    Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ana MedinaCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.ORCID 0000-0001-7146-8987
Elisabet JiménezCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.ORCID 0000-0001-7521-8619
Iracema CaballeroCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.ORCID 0000-0001-8992-4194
Albert CastellvíCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.
Josep Triviño VallsCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.
Martin AlcorloDepartment of Crystallography and Structural Biology, Institute of Physical Chemistry `Rocasolano', Spanish National Research Council (CSIC), Madrid, Spain.
Rafael MolinaDepartment of Crystallography and Structural Biology, Institute of Physical Chemistry `Rocasolano', Spanish National Research Council (CSIC), Madrid, Spain.
Juan A HermosoDepartment of Crystallography and Structural Biology, Institute of Physical Chemistry `Rocasolano', Spanish National Research Council (CSIC), Madrid, Spain.
Massimo D SammitoCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.ORCID 0000-0002-8346-9247
Rafael BorgesDepartment of Biophysics and Pharmacology, Biosciences Institute, São Paulo State University (UNESP), Botucatu, Sao Paulo 18618-689, Brazil.
Isabel UsónCrystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain.

Funding

Ministerio de Ciencia e Innovación BES-2017-080368Ministerio de Ciencia e Innovación PGC2018-101370-B-100Ministerio de Ciencia e Innovación PID2020-115331GB-I00Ministerio de Ciencia e Innovación PRE2019-087953Science and Technology Facilities Council Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW
6 · The paper itself

Abstract

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.

Indexed as

PeptidesCrystallography, X-RayModels, MolecularPeptidesAlphaFoldARCIMBOLDOARCIMBOLDO_SHREDDERfragment-based molecular replacementmodel biasphasingpredictionsRoseTTAFoldverification

Identifiers

PMID36322413
PMCPMC9629495

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.