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Total network controllability analysis discovers explainable drugs for Covid-19 treatment

BACKGROUND: The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against vi...

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Autores principales: Wei, Xinru, Pan, Chunyu, Zhang, Xizhe, Zhang, Weixiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478273/
https://www.ncbi.nlm.nih.gov/pubmed/37670359
http://dx.doi.org/10.1186/s13062-023-00410-9
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author Wei, Xinru
Pan, Chunyu
Zhang, Xizhe
Zhang, Weixiong
author_facet Wei, Xinru
Pan, Chunyu
Zhang, Xizhe
Zhang, Weixiong
author_sort Wei, Xinru
collection PubMed
description BACKGROUND: The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets. RESULTS: We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach’s effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients. CONCLUSIONS: Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13062-023-00410-9.
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spelling pubmed-104782732023-09-06 Total network controllability analysis discovers explainable drugs for Covid-19 treatment Wei, Xinru Pan, Chunyu Zhang, Xizhe Zhang, Weixiong Biol Direct Research BACKGROUND: The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets. RESULTS: We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach’s effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients. CONCLUSIONS: Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13062-023-00410-9. BioMed Central 2023-09-05 /pmc/articles/PMC10478273/ /pubmed/37670359 http://dx.doi.org/10.1186/s13062-023-00410-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wei, Xinru
Pan, Chunyu
Zhang, Xizhe
Zhang, Weixiong
Total network controllability analysis discovers explainable drugs for Covid-19 treatment
title Total network controllability analysis discovers explainable drugs for Covid-19 treatment
title_full Total network controllability analysis discovers explainable drugs for Covid-19 treatment
title_fullStr Total network controllability analysis discovers explainable drugs for Covid-19 treatment
title_full_unstemmed Total network controllability analysis discovers explainable drugs for Covid-19 treatment
title_short Total network controllability analysis discovers explainable drugs for Covid-19 treatment
title_sort total network controllability analysis discovers explainable drugs for covid-19 treatment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478273/
https://www.ncbi.nlm.nih.gov/pubmed/37670359
http://dx.doi.org/10.1186/s13062-023-00410-9
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