Zambrana, Carme;
Xenos, Alexandros;
Böttcher, René;
Malod-Dognin, Noël;
Pržulj, Nataša;
(2021)
Network neighbors of viral targets and differentially expressed genes in COVID-19 are drug target candidates.
Scientific Reports
, 11
, Article 18985. 10.1038/s41598-021-98289-x.
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Abstract
The COVID-19 pandemic is raging. It revealed the importance of rapid scientific advancement towards understanding and treating new diseases. To address this challenge, we adapt an explainable artificial intelligence algorithm for data fusion and utilize it on new omics data on viral–host interactions, human protein interactions, and drugs to better understand SARS-CoV-2 infection mechanisms and predict new drug–target interactions for COVID-19. We discover that in the human interactome, the human proteins targeted by SARS-CoV-2 proteins and the genes that are differentially expressed after the infection have common neighbors central in the interactome that may be key to the disease mechanisms. We uncover 185 new drug–target interactions targeting 49 of these key genes and suggest re-purposing of 149 FDA-approved drugs, including drugs targeting VEGF and nitric oxide signaling, whose pathways coincide with the observed COVID-19 symptoms. Our integrative methodology is universal and can enable insight into this and other serious diseases.
| Type: | Article |
|---|---|
| Title: | Network neighbors of viral targets and differentially expressed genes in COVID-19 are drug target candidates |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41598-021-98289-x |
| Publisher version: | https://doi.org/10.1038/s41598-021-98289-x |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Computational biology and bioinformatics, Data integration, Data mining, Network topology |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10187866 |
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