COVID-19; Drug discovery; Mechanistic modeling; Signaling pathway; Systems biology; Biochemistry; Molecular Biology; Genetics; Computer Science Applications; Computational Theory and Mathematics; Computational Mathematics
Résumé :
[en] Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.
Disciplines :
Biotechnologie
Auteur, co-auteur :
Rian, Kinza; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
Esteban-Medina, Marina; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain ; Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain
Hidalgo, Marta R; Bioinformatics and Biostatistics Unit, Centro de Investigación Príncipe Felipe (CIPF), 46012, Valencia, Spain
Çubuk, Cankut; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
Falco, Matias M; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain ; Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain
Loucera, Carlos; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain ; Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain
Gunyel, Devrim; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
OSTASZEWSKI, Marek ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
Peña-Chilet, María; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain. maria.pena.chilet.ext@juntadeandalucia.es ; Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain. maria.pena.chilet.ext@juntadeandalucia.es ; Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain. maria.pena.chilet.ext@juntadeandalucia.es
Dopazo, Joaquín ; Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es ; Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es ; Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es ; Functional Genomics Node (INB-ELIXIR-es), Sevilla, Spain. joaquin.dopazo@juntadeandalucia.es
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Mechanistic modeling of the SARS-CoV-2 disease map.
Ministerio de Economía y Competitividad Instituto de Salud Carlos III FP7 People: Marie-Curie Actions
Subventionnement (détails) :
This work is supported by grants SAF2017–88908-R from the Spanish Ministry of Economy and Competitiveness, PT17/0009/0006, ACCI2018/29 from CIBER-ISCIII and COV20/00788 from the ISCIII, co-funded with European Regional Development Funds (ERDF), the grant “Large-scale drug repurposing in rare diseases by genomic Big Data analysis with machine learning methods” from the Fundación BBVA (G999088Q), as well as H2020 Programme of the European Union grants Marie Curie Innovative Training Network “Machine Learning Frontiers in Precision Medicine” (MLFPM) (GA 813533).
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