TY - JOUR
T1 - Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches
AU - Niarakis, Anna
AU - Ostaszewski, Marek
AU - Mazein, Alexander
AU - Kuperstein, Inna
AU - Kutmon, Martina
AU - Gillespie, Marc E.
AU - Funahashi, Akira
AU - Acencio, Marcio Luis
AU - Hemedan, Ahmed
AU - Aichem, Michael
AU - Klein, Karsten
AU - Czauderna, Tobias
AU - Burtscher, Felicia
AU - Yamada, Takahiro G.
AU - Hiki, Yusuke
AU - Hiroi, Noriko F.
AU - Hu, Finterly
AU - Pham, Nhung
AU - Ehrhart, Friederike
AU - Willighagen, Egon L.
AU - Valdeolivas, Alberto
AU - Dugourd, Aurelien
AU - Messina, Francesco
AU - Esteban-Medina, Marina
AU - Peña-Chilet, Maria
AU - Rian, Kinza
AU - Soliman, Sylvain
AU - Aghamiri, Sara Sadat
AU - Puniya, Bhanwar Lal
AU - Naldi, Aurélien
AU - Helikar, Tomáš
AU - Singh, Vidisha
AU - Fernández, Marco Fariñas
AU - Bermudez, Viviam
AU - Tsirvouli, Eirini
AU - Montagud, Arnau
AU - Noël, Vincent
AU - Ponce-de-Leon, Miguel
AU - Maier, Dieter
AU - Bauch, Angela
AU - Gyori, Benjamin M.
AU - Bachman, John A.
AU - Luna, Augustin
AU - Piñero, Janet
AU - Furlong, Laura I.
AU - Balaur, Irina
AU - Rougny, Adrien
AU - Jarosz, Yohan
AU - Overall, Rupert W.
AU - Phair, Robert
AU - Perfetto, Livia
AU - Matthews, Lisa
AU - Rex, Devasahayam Arokia Balaya
AU - Orlic-Milacic, Marija
AU - Gomez, Luis Cristobal Monraz
AU - De Meulder, Bertrand
AU - Ravel, Jean Marie
AU - Jassal, Bijay
AU - Satagopam, Venkata
AU - Wu, Guanming
AU - Golebiewski, Martin
AU - Gawron, Piotr
AU - Calzone, Laurence
AU - Beckmann, Jacques S.
AU - Evelo, Chris T.
AU - D’Eustachio, Peter
AU - Schreiber, Falk
AU - Saez-Rodriguez, Julio
AU - Dopazo, Joaquin
AU - Kuiper, Martin
AU - Valencia, Alfonso
AU - Wolkenhauer, Olaf
AU - Kitano, Hiroaki
AU - Barillot, Emmanuel
AU - Auffray, Charles
AU - Balling, Rudi
AU - Schneider, Reinhard
N1 - Publisher Copyright:
Copyright © 2024 Niarakis, Ostaszewski, Mazein, Kuperstein, Kutmon, Gillespie, Funahashi, Acencio, Hemedan, Aichem, Klein, Czauderna, Burtscher, Yamada, Hiki, Hiroi, Hu, Pham, Ehrhart, Willighagen, Valdeolivas, Dugourd, Messina, Esteban-Medina, Peña-Chilet, Rian, Soliman, Aghamiri, Puniya, Naldi, Helikar, Singh, Fernández, Bermudez, Tsirvouli, Montagud, Noël, Ponce-de-Leon, Maier, Bauch, Gyori, Bachman, Luna, Piñero, Furlong, Balaur, Rougny, Jarosz, Overall, Phair, Perfetto, Matthews, Rex, Orlic-Milacic, Gomez, De Meulder, Ravel, Jassal, Satagopam, Wu, Golebiewski, Gawron, Calzone, Beckmann, Evelo, D’Eustachio, Schreiber, Saez-Rodriguez, Dopazo, Kuiper, Valencia, Wolkenhauer, Kitano, Barillot, Auffray, Balling, Schneider and the COVID-19 Disease Map Community.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - disease maps
KW - dynamic models
KW - large-scale community effort
KW - mechanistic models
KW - SARS-CoV-2
KW - systems biology
KW - systems medicine
UR - https://www.scopus.com/pages/publications/85185923805
U2 - 10.3389/fimmu.2023.1282859
DO - 10.3389/fimmu.2023.1282859
M3 - Article
C2 - 38414974
AN - SCOPUS:85185923805
SN - 1664-3224
VL - 14
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 1282859
ER -