Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Détails

Ressource 1Télécharger: 38414974_BIB_6275E3C6D1A9.pdf (6381.68 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_6275E3C6D1A9
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.
Périodique
Frontiers in immunology
Auteur⸱e⸱s
Niarakis A., Ostaszewski M., Mazein A., Kuperstein I., Kutmon M., Gillespie M.E., Funahashi A., Acencio M.L., Hemedan A., Aichem M., Klein K., Czauderna T., Burtscher F., Yamada T.G., Hiki Y., Hiroi N.F., Hu F., Pham N., Ehrhart F., Willighagen E.L., Valdeolivas A., Dugourd A., Messina F., Esteban-Medina M., Peña-Chilet M., Rian K., Soliman S., Aghamiri S.S., Puniya B.L., Naldi A., Helikar T., Singh V., Fernández M.F., Bermudez V., Tsirvouli E., Montagud A., Noël V., Ponce-de-Leon M., Maier D., Bauch A., Gyori B.M., Bachman J.A., Luna A., Piñero J., Furlong L.I., Balaur I., Rougny A., Jarosz Y., Overall R.W., Phair R., Perfetto L., Matthews L., Rex DAB, Orlic-Milacic M., Gomez LCM, De Meulder B., Ravel J.M., Jassal B., Satagopam V., Wu G., Golebiewski M., Gawron P., Calzone L., Beckmann J.S., Evelo C.T., D'Eustachio P., Schreiber F., Saez-Rodriguez J., Dopazo J., Kuiper M., Valencia A., Wolkenhauer O., Kitano H., Barillot E., Auffray C., Balling R., Schneider R.
Collaborateur⸱rice⸱s
COVID-19 Disease Map Community
ISSN
1664-3224 (Electronic)
ISSN-L
1664-3224
Statut éditorial
Publié
Date de publication
2023
Peer-reviewed
Oui
Volume
14
Pages
1282859
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.
Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.
Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.
The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.
Mots-clé
Humans, COVID-19, SARS-CoV-2, Drug Repositioning, Systems Biology, Computer Simulation, disease maps, dynamic models, large-scale community effort, mechanistic models, systems biology, systems medicine
Pubmed
Open Access
Oui
Création de la notice
08/03/2024 15:18
Dernière modification de la notice
09/08/2024 15:00
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