Making protein dynamics FAIR : Research platforms for the collection, dissemination, and analysis of molecular dynamics simulations

Molecular dynamics (MD) simulations are a well-established technique to characterize the structural motions of biological systems at atomic resolution. However, accessing, viewing, and sharing MD trajectories is typically restricted by large file sizes and the need for specialized software, which li...

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Detalles Bibliográficos
Autor: Torrens Fontanals, Mariona
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:CBUC, CESCA
Repositorio:TDR. Tesis Doctorales en Red
OAI Identifier:oai:www.tdx.cat:10803/673525
Acceso en línea:http://hdl.handle.net/10803/673525
Access Level:acceso abierto
Palabra clave:Molecular dynamics simulations
Simulacions de dinàmica molecular
Online repository
Repositori online
G protein-coupled receptors
Receptors acoblats a proteïnes G
SARS-CoV-2
Data sharing
Compartició de dades
577
Descripción
Sumario:Molecular dynamics (MD) simulations are a well-established technique to characterize the structural motions of biological systems at atomic resolution. However, accessing, viewing, and sharing MD trajectories is typically restricted by large file sizes and the need for specialized software, which limits the audience to which this data is available. The aim of this thesis is to extend the outreach of MD simulations by providing online resources that facilitate the dissemination, visual inspection, and analysis of this data. For that, we present GPCRmd and SCoV2-MD, two online resources focused on proteins with high biomedical interest: G protein-coupled receptors (GPCRs) and the proteome of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), respectively. We also showcase the capabilities of GPCRmd and SCoV2-MD for exploring key aspects of protein dynamics. Overall, these platforms have the potential to promote data “Findability, Accessibility, Interoperability, and Reusability” in the MD field, supporting the FAIR principles for scientific data management.