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MrParse: finding homologues in the PDB and the EBI AlphaFold database for molecular replacement and more.
Simpkin, Adam J; Thomas, Jens M H; Keegan, Ronan M; Rigden, Daniel J.
Affiliation
  • Simpkin AJ; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom.
  • Thomas JMH; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom.
  • Keegan RM; UKRI-STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
  • Rigden DJ; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom.
Acta Crystallogr D Struct Biol ; 78(Pt 5): 553-559, 2022 May 01.
Article in En | MEDLINE | ID: mdl-35503204
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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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteins Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Acta Crystallogr D Struct Biol Year: 2022 Document type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteins Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Acta Crystallogr D Struct Biol Year: 2022 Document type: Article Affiliation country: United kingdom
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