SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions

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  • dc.contributor.author Torrens Fontanals, Mariona
  • dc.contributor.author Peralta-Garcia, Alejandro
  • dc.contributor.author Talarico, Carmine
  • dc.contributor.author Guixà González, Ramon, 1978-
  • dc.contributor.author Giorgino, Toni
  • dc.contributor.author Selent, Jana
  • dc.date.accessioned 2022-04-25T06:36:49Z
  • dc.date.available 2022-04-25T06:36:49Z
  • dc.date.issued 2022
  • dc.description.abstract SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Torrens-Fontanals M, Peralta-García A, Talarico C, Guixà-González R, Giorgino T, Selent J. SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions. Nucleic Acids Res. 2022 Jan 7;50(D1):D858-D866. DOI: 10.1093/nar/gkab977
  • dc.identifier.doi http://dx.doi.org/10.1093/nar/gkab977
  • dc.identifier.issn 0305-1048
  • dc.identifier.uri http://hdl.handle.net/10230/52877
  • dc.language.iso eng
  • dc.publisher Oxford University Press
  • dc.relation.ispartof Nucleic Acids Res. 2022 Jan 7;50(D1):D858-D866
  • dc.rights © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
  • dc.title SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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