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Local computational methods to improve the interpretability and analysis of cryo-EM maps.
Kaur, Satinder; Gomez-Blanco, Josue; Khalifa, Ahmad A Z; Adinarayanan, Swathi; Sanchez-Garcia, Ruben; Wrapp, Daniel; McLellan, Jason S; Bui, Khanh Huy; Vargas, Javier.
  • Kaur S; Departament of Anatomy and Cell Biology, McGill University 3640 Rue University, Montréal, QC, Canada.
  • Gomez-Blanco J; Departament of Anatomy and Cell Biology, McGill University 3640 Rue University, Montréal, QC, Canada.
  • Khalifa AAZ; Departament of Anatomy and Cell Biology, McGill University 3640 Rue University, Montréal, QC, Canada.
  • Adinarayanan S; Departament of Anatomy and Cell Biology, McGill University 3640 Rue University, Montréal, QC, Canada.
  • Sanchez-Garcia R; Biocomputing Unit, Centro Nacional de Biotecnología-CSIC C/Darwin 3, Cantoblanco, Madrid, Spain.
  • Wrapp D; Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA.
  • McLellan JS; Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA.
  • Bui KH; Departament of Anatomy and Cell Biology, McGill University 3640 Rue University, Montréal, QC, Canada.
  • Vargas J; Departmento de Óptica, Universidad Complutense de Madrid, Madrid, Spain. jvargas@fis.ucm.es.
Nat Commun ; 12(1): 1240, 2021 02 23.
Article in English | MEDLINE | ID: covidwho-1387330
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ABSTRACT
Cryo-electron microscopy (cryo-EM) maps usually show heterogeneous distributions of B-factors and electron density occupancies and are typically B-factor sharpened to improve their contrast and interpretability at high-resolutions. However, 'over-sharpening' due to the application of a single global B-factor can distort processed maps causing connected densities to appear broken and disconnected. This issue limits the interpretability of cryo-EM maps, i.e. ab initio modelling. In this work, we propose 1) approaches to enhance high-resolution features of cryo-EM maps, while preventing map distortions and 2) methods to obtain local B-factors and electron density occupancy maps. These algorithms have as common link the use of the spiral phase transformation and are called LocSpiral, LocBSharpen, LocBFactor and LocOccupancy. Our results, which include improved maps of recent SARS-CoV-2 structures, show that our methods can improve the interpretability and analysis of obtained reconstructions.

Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2021 Document Type: Article Affiliation country: S41467-021-21509-5

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2021 Document Type: Article Affiliation country: S41467-021-21509-5