Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches
Creators: name: Niarakis, Anna
name: Ostaszewski, Marek
name: Mazein, Alexander
name: Kuperstein, Inna
name: Kutmon, Martina
name: Gillespie, Marc E.
name: Funahashi, Akira
name: Acencio, Marcio Luis
name: Hemedan, Ahmed
name: Aichem, Michael
name: Klein, Karsten
name: Czauderna, Tobias
name: Burtscher, Felicia
name: Yamada, Takahiro G.
name: Hiki, Yusuke
name: Hiroi, Noriko F.
name: Hu, Finterly
name: Pham, Nhung
name: Ehrhart, Friederike
name: Willighagen, Egon L.
name: Valdeolivas, Alberto
name: Dugourd, Aurelien
name: Messina, Francesco
name: Esteban-Medina, Marina
name: Peña-Chilet, Maria
name: Rian, Kinza
name: Soliman, Sylvain
name: Aghamiri, Sara Sadat
name: Puniya, Bhanwar Lal
name: Naldi, Aurélien
name: Helikar, Tomáš
name: Singh, Vidisha
name: Fernández, Marco Fariñas
name: Bermudez, Viviam
name: Tsirvouli, Eirini
name: Montagud, Arnau
name: Noël, Vincent
name: Ponce-De-Leon, Miguel
name: Maier, Dieter
name: Bauch, Angela
name: Gyori, Benjamin M.
name: Bachman, John A.
name: Luna, Augustin
name: Piñero, Janet
name: Furlong, Laura I.
name: Balaur, Irina
name: Rougny, Adrien
name: Jarosz, Yohan
name: Overall, Rupert
name: Phair, Robert
name: Perfetto, Livia
name: Matthews, Lisa
name: Rex, Devasahayam Arokia Balaya
name: Orlic-Milacic, Marija
name: Gomez, Luis Cristobal Monraz
name: De Meulder, Bertrand
name: Ravel, Jean Marie
name: Jassal, Bijay
name: Satagopam, Venkata
name: Wu, Guanming
name: Golebiewski, Martin
name: Gawron, Piotr
name: Calzone, Laurence
name: Beckmann, Jacques S.
name: Evelo, Chris T.
name: D’Eustachio, Peter
name: Schreiber, Falk
name: Saez-Rodriguez, Julio
name: Dopazo, Joaquin
name: Kuiper, Martin
name: Valencia, Alfonso
name: Wolkenhauer, Olaf
name: Kitano, Hiroaki
name: Barillot, Emmanuel
name: Auffray, Charles
name: Balling, Rudi
name: Schneider, Reinhard
Publisher: name: Humboldt-Universität zu Berlin
Year: 2024
Subjects: subject: SARS-CoV-2
subject: systems biology
subject: disease maps
subject: mechanistic models
subject: dynamic models
subject: systems medicine
subject: large-scale community effort
subject: 610 Medizin und Gesundheit

description: Introduction: 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.