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Article

Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders

1
MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Key Laboratory of Pathogen Bioscience and Anti-Infective Medicine, Department of Bioinformatics, Center for Systems Biology, School of Life Sciences, Suzhou Medical College of Soochow University, Suzhou 215213, China
2
Experimental Center of Suzhou Medical College of Soochow University, Suzhou 215123, China
3
Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou 215123, China
4
Key Laboratory of Alkene-Carbon Fibres-Based Technology & Application for Detection of Major Infectious Diseases, Soochow University, Suzhou 215123, China
5
Jiangsu Key Laboratory of Infection and Immunity, Soochow University, Suzhou 215123, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Mol. Sci. 2024, 25(16), 8917; https://doi.org/10.3390/ijms25168917
Submission received: 18 July 2024 / Revised: 6 August 2024 / Accepted: 14 August 2024 / Published: 16 August 2024
(This article belongs to the Section Molecular Informatics)

Abstract

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug–target network and dynamic network-based drug-repurposing analysis, ubiquitin–carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.
Keywords: COVID-19; network biology; target module; connectivity map; perturbation response scanning COVID-19; network biology; target module; connectivity map; perturbation response scanning

Share and Cite

MDPI and ACS Style

Qian, J.; Yang, B.; Wang, S.; Yuan, S.; Zhu, W.; Zhou, Z.; Zhang, Y.; Hu, G. Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders. Int. J. Mol. Sci. 2024, 25, 8917. https://doi.org/10.3390/ijms25168917

AMA Style

Qian J, Yang B, Wang S, Yuan S, Zhu W, Zhou Z, Zhang Y, Hu G. Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders. International Journal of Molecular Sciences. 2024; 25(16):8917. https://doi.org/10.3390/ijms25168917

Chicago/Turabian Style

Qian, Jing, Bin Yang, Shuo Wang, Su Yuan, Wenjing Zhu, Ziyun Zhou, Yujuan Zhang, and Guang Hu. 2024. "Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders" International Journal of Molecular Sciences 25, no. 16: 8917. https://doi.org/10.3390/ijms25168917

APA Style

Qian, J., Yang, B., Wang, S., Yuan, S., Zhu, W., Zhou, Z., Zhang, Y., & Hu, G. (2024). Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders. International Journal of Molecular Sciences, 25(16), 8917. https://doi.org/10.3390/ijms25168917

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