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

Medientyp: E-Artikel

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

Beteiligte: Niarakis, Anna [Verfasser:in]; Ostaszewski, Marek [Verfasser:in]; Mazein, Alexander [Verfasser:in]; Kuperstein, Inna [Verfasser:in]; Kutmon, Martina [Verfasser:in]; Gillespie, Marc E. [Verfasser:in]; Funahashi, Akira [Verfasser:in]; Acencio, Marcio Luis [Verfasser:in]; Hemedan, Ahmed [Verfasser:in]; Aichem, Michael [Verfasser:in]; Klein, Karsten [Verfasser:in]; Czauderna, Tobias [Verfasser:in]; Burtscher, Felicia [Verfasser:in]; Yamada, Takahiro G. [Verfasser:in]; Hiki, Yusuke [Verfasser:in]; Hiroi, Noriko F. [Verfasser:in]; Hu, Finterly [Verfasser:in]; Pham, Nhung [Verfasser:in]; Ehrhart, Friederike [Verfasser:in]; Willighagen, Egon L. [Verfasser:in]; Valdeolivas, Alberto [Verfasser:in]; Dugourd, Aurélien [Verfasser:in]; Messina, Francesco [Verfasser:in]; Esteban-Medina, Marina [Verfasser:in]; Peña-Chilet, Maria [Verfasser:in]; Rian, Kinza [Verfasser:in]; Soliman, Sylvain [Verfasser:in]; Aghamiri, Sara Sadat [Verfasser:in]; Puniya, Bhanwar Lal [Verfasser:in]; Naldi, Aurélien [Verfasser:in]; Helikar, Tomáš [Verfasser:in]; Singh, Vidisha [Verfasser:in]; Fernández, Marco Fariñas [Verfasser:in]; Bermudez, Viviam [Verfasser:in]; Tsirvouli, Eirini [Verfasser:in]; Montagud, Arnau [Verfasser:in]; Noël, Vincent [Verfasser:in]; Ponce-de-Leon, Miguel [Verfasser:in]; Maier, Dieter [Verfasser:in]; Bauch, Angela [Verfasser:in]; Gyori, Benjamin M. [Verfasser:in]; Bachman, John A. [Verfasser:in]; Luna, Augustin [Verfasser:in]; Piñero, Janet [Verfasser:in]; Furlong, Laura I. [Verfasser:in]; Balaur, Irina [Verfasser:in]; Rougny, Adrien [Verfasser:in]; Jarosz, Yohan [Verfasser:in]; Overall, Rupert W. [Verfasser:in]; Phair, Robert [Verfasser:in]; Perfetto, Livia [Verfasser:in]; Matthews, Lisa [Verfasser:in]; Rex, Devasahayam Arokia Balaya [Verfasser:in]; Orlic-Milacic, Marija [Verfasser:in]; Gomez, Luis Cristobal Monraz [Verfasser:in]; De Meulder, Bertrand [Verfasser:in]; Ravel, Jean Marie [Verfasser:in]; Jassal, Bijay [Verfasser:in]; Satagopam, Venkata [Verfasser:in]; Wu, Guanming [Verfasser:in]; Golebiewski, Martin [Verfasser:in]; Gawron, Piotr [Verfasser:in]; Calzone, Laurence [Verfasser:in]; Beckmann, Jacques S. [Verfasser:in]; Evelo, Chris T. [Verfasser:in]; D’Eustachio, Peter [Verfasser:in]; Schreiber, Falk [Verfasser:in]; Sáez Rodríguez, Julio [Verfasser:in]; Dopazo, Joaquin [Verfasser:in]; Kuiper, Martin [Verfasser:in]; Valencia, Alfonso [Verfasser:in]; Wolkenhauer, Olaf [Verfasser:in]; Kitano, Hiroaki [Verfasser:in]; Barillot, Emmanuel [Verfasser:in]; Auffray, Charles [Verfasser:in]; Balling, Rudi [Verfasser:in]; Schneider, Reinhard [Verfasser:in]

Erschienen: 13 February 2024

Sprache: Englisch

DOI: 10.3389/fimmu.2023.1282859

Identifikator:

Schlagwörter: Disease maps ; dynamic models ; large-scale community effort ; mechanistic models ; SARS-CoV-2 ; Systems Biology ; Systems Medicine

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Anmerkungen:

Beschreibung: 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. Methods: 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: 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. Discussion: 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.

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