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The missing link: covalent linkages in structural models.
Nicholls, Robert A; Wojdyr, Marcin; Joosten, Robbie P; Catapano, Lucrezia; Long, Fei; Fischer, Marcus; Emsley, Paul; Murshudov, Garib N.
Afiliação
  • Nicholls RA; Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom.
  • Wojdyr M; Global Phasing Limited, Sheraton House, Castle Park, Cambridge CB3 0AX, United Kingdom.
  • Joosten RP; Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.
  • Catapano L; Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom.
  • Long F; Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom.
  • Fischer M; Chemical Biology and Therapeutics and Structural Biology, St Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105-3678, USA.
  • Emsley P; Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom.
  • Murshudov GN; Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom.
Acta Crystallogr D Struct Biol ; 77(Pt 6): 727-745, 2021 Jun 01.
Article em En | MEDLINE | ID: mdl-34076588
Covalent linkages between constituent blocks of macromolecules and ligands have been subject to inconsistent treatment during the model-building, refinement and deposition process. This may stem from a number of sources, including difficulties with initially detecting the covalent linkage, identifying the correct chemistry, obtaining an appropriate restraint dictionary and ensuring its correct application. The analysis presented herein assesses the extent of problems involving covalent linkages in the Protein Data Bank (PDB). Not only will this facilitate the remediation of existing models, but also, more importantly, it will inform and thus improve the quality of future linkages. By considering linkages of known type in the CCP4 Monomer Library (CCP4-ML), failure to model a covalent linkage is identified to result in inaccurate (systematically longer) interatomic distances. Scanning the PDB for proximal atom pairs that do not have a corresponding type in the CCP4-ML reveals a large number of commonly occurring types of unannotated potential linkages; in general, these may or may not be covalently linked. Manual consideration of the most commonly occurring cases identifies a number of genuine classes of covalent linkages. The recent expansion of the CCP4-ML is discussed, which has involved the addition of over 16 000 and the replacement of over 11 000 component dictionaries using AceDRG. As part of this effort, the CCP4-ML has also been extended using AceDRG link dictionaries for the aforementioned linkage types identified in this analysis. This will facilitate the identification of such linkage types in future modelling efforts, whilst concurrently easing the process involved in their application. The need for a universal standard for maintaining link records corresponding to covalent linkages, and references to the associated dictionaries used during modelling and refinement, following deposition to the PDB is emphasized. The importance of correctly modelling covalent linkages is demonstrated using a case study, which involves the covalent linkage of an inhibitor to the main protease in various viral species, including SARS-CoV-2. This example demonstrates the importance of properly modelling covalent linkages using a comprehensive restraint dictionary, as opposed to just using a single interatomic distance restraint or failing to model the covalent linkage at all.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estruturais Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estruturais Idioma: En Ano de publicação: 2021 Tipo de documento: Article