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High-throughput Screening for Broad-spectrum Chemical Inhibitors of RNA Viruses
Published on: May 5, 2014
Indirect-Acting Pan-Antivirals vs. Respiratory Viruses: A Fresh Perspective on Computational Multi-Target Drug
Valeria V Kleandrova1, Marcus T Scotti2, Alejandro Speck-Planche2
1Laboratory of Fundamental and Applied Research of Quality and Technology of Food Production, Moscow State University of Food Production, Volokolamskoe Shosse 11, 125080, Moscow, Russian Federation.
Abstract:
Respiratory viruses continue to afflict mankind. Among them, pathogens such as coronaviruses [including the current pandemic agent known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] and the one causing influenza A (IAV) are highly contagious and deadly. These can evade the immune system defenses while causing a hyperinflammatory response that can damage different tissues/organs. Simultaneously targeting several immunomodulatory proteins is a plausible antiviral strategy since it could lead to the discovery of indirect-acting pan-antiviral (IAPA) agents for the treatment of diseases caused by respiratory viruses. In this context, computational approaches, which are an essential part of the modern drug discovery campaigns, could accelerate the identification of multi-target immunomodulators. This perspective discusses the usefulness of computational multi-target drug discovery for the virtual screening (drug repurposing) of IAPA agents capable of boosting the immune system through the activation of the toll-like receptor 7 (TLR7) and/or the stimulator of interferon genes (STING) while inhibiting key inflammation-related proteins such as caspase-1 and tumor necrosis factor-alpha (TNF-α).
Insights
Computational drug discovery can identify novel antiviral therapies. This approach screens for compounds that boost immune responses via TLR7/STING and inhibit inflammation by targeting caspase-1 and TNF-α for respiratory viruses.
Area of Science:
- * Virology and Immunology
- * Computational Drug Discovery
Background:
- * Respiratory viruses like SARS-CoV-2 and influenza A pose significant global health threats.
- * These viruses evade immune defenses and trigger harmful hyperinflammatory responses.
- * Developing broad-spectrum antiviral agents is crucial for managing respiratory viral infections.
Purpose of the Study:
- * To explore computational multi-target drug discovery for identifying indirect-acting pan-antiviral (IAPA) agents.
- * To investigate the potential of activating immune pathways (TLR7/STING) and inhibiting inflammatory targets (caspase-1, TNF-α).
- * To highlight the role of computational methods in accelerating the discovery of novel antiviral treatments.
Main Methods:
- * Utilizing computational approaches for virtual screening and drug repurposing.
- * Focusing on multi-target drug discovery strategies.
- * Identifying compounds that modulate specific immune and inflammatory pathways.
Main Results:
- * Computational methods can accelerate the identification of multi-target immunomodulators.
- * Virtual screening can identify IAPA agents with potential therapeutic benefits.
- * The strategy involves simultaneous targeting of immune-boosting and inflammation-inhibiting proteins.
Conclusions:
- * Computational multi-target drug discovery is a promising strategy for developing IAPA agents.
- * Targeting TLR7/STING activation and caspase-1/TNF-α inhibition offers a viable antiviral approach.
- * This approach can lead to effective treatments for diseases caused by respiratory viruses.
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