Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.
Details
Serval ID
serval:BIB_6275E3C6D1A9
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.
Journal
Frontiers in immunology
Working group(s)
COVID-19 Disease Map Community
ISSN
1664-3224 (Electronic)
ISSN-L
1664-3224
Publication state
Published
Issued date
2023
Peer-reviewed
Oui
Volume
14
Pages
1282859
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Publication Status: epublish
Abstract
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.
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.
Keywords
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
Yes
Create date
08/03/2024 16:18
Last modification date
09/08/2024 16:00