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Medina A, Jiménez E, Caballero I, Castellví A, Triviño Valls J, Alcorlo M, Molina R, Hermoso JA, Sammito MD, Borges R, Usón I. Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER. Acta Crystallogr D Struct Biol 2022; 78:1283-1293. [PMID: 36322413 PMCID: PMC9629495 DOI: 10.1107/s2059798322009706] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/03/2022] [Indexed: 11/23/2022] Open
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.
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Affiliation(s)
- Ana Medina
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Elisabet Jiménez
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Iracema Caballero
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Albert Castellví
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Josep Triviño Valls
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Martin Alcorlo
- Department of Crystallography and Structural Biology, Institute of Physical Chemistry ‘Rocasolano’, Spanish National Research Council (CSIC), Madrid, Spain
| | - Rafael Molina
- Department of Crystallography and Structural Biology, Institute of Physical Chemistry ‘Rocasolano’, Spanish National Research Council (CSIC), Madrid, Spain
| | - Juan A. Hermoso
- Department of Crystallography and Structural Biology, Institute of Physical Chemistry ‘Rocasolano’, Spanish National Research Council (CSIC), Madrid, Spain
| | - Massimo D. Sammito
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Rafael Borges
- Department of Biophysics and Pharmacology, Biosciences Institute, São Paulo State University (UNESP), Botucatu, Sao Paulo 18618-689, Brazil
| | - Isabel Usón
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain,ICREA, Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, 08003 Barcelona, Spain,Correspondence e-mail:
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Simpkin AJ, Thomas JMH, Keegan RM, Rigden DJ. MrParse: finding homologues in the PDB and the EBI AlphaFold database for molecular replacement and more. ACTA CRYSTALLOGRAPHICA SECTION D STRUCTURAL BIOLOGY 2022; 78:553-559. [PMID: 35503204 PMCID: PMC9063843 DOI: 10.1107/s2059798322003576] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 03/29/2022] [Indexed: 11/10/2022]
Abstract
Crystallographers have an array of search-model options for structure solution by molecular replacement (MR). The well established options of homologous experimental structures and regular secondary-structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may be carried out locally or may use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help to streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any experimental homologues found using eLLG, which indicates the likelihood that a given search model will work in MR. Inbuilt displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians.
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