Antiviral drug discovery and development: challenges and future directions

The coronavirus disease 2019 (COVID-19) pandemic has stimulated extensive endeavors toward the development of therapeutic interventions targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human proteins for viral infection control, encompassing numerous potential drugs and thousands of patients participating in clinical trials. These concerted efforts have resulted in significant advancements in antiviral drug discovery and development. In this review, we present a comprehensive timeline detailing the development of antiviral drugs, tracing the progression from early viral inhibitors to modern broad-spectrum antiviral agents. We also outline the current status of advancements in antiviral drug discovery, encompassing target-based strategies, innovative mechanism-based approaches, and pharmacokinetic optimization. Furthermore, we discuss the challenges and future prospects gained from COVID-19 and other infectious diseases, covering knowledge of artificial intelligence strategies, the utilization of medicinal chemistry tools, and advancements in nanotechnology applications. The application of artificial intelligence in drug discovery is increasingly prevalent, particularly in the areas of protein structure prediction, drug target identification, and bioactivity forecasting. Nanotechnology has played a crucial role in the delivery of antiviral drugs and the development of vaccines, exemplified by the use of lipid nanoparticles in mRNA vaccines. Additionally, we highlight potential future directions for drug discovery, such as targeting membraneless organelles (liquid‒liquid phase separation).

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Publication Details

Journal
Signal Transduction and Targeted Therapy
Published
2026-02-25
DOI
https://doi.org/10.1038/s41392-025-02539-7
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Antiviral drug discovery and development: challenges and future directions

Xueping Hu, Shujing Xu, Meehyein Kim, Ping Li et al.
Signal Transduction and Targeted Therapy
Computational Drug Discovery Methods
article

Antiviral drug discovery and development: challenges and future directions

Xueping Hu, Shujing Xu, Meehyein Kim, Ping Li, Xinyong Liu, Peng Zhan, Shaoqing Du
article en

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has stimulated extensive endeavors toward the development of therapeutic interventions targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human proteins for viral infection control, encompassing numerous potential drugs and thousands of patients participating in clinical trials. These concerted efforts have resulted in significant advancements in antiviral drug discovery and development. In this review, we present a comprehensive timeline detailing the development of antiviral drugs, tracing the progression from early viral inhibitors to modern broad-spectrum antiviral agents. We also outline the current status of advancements in antiviral drug discovery, encompassing target-based strategies, innovative mechanism-based approaches, and pharmacokinetic optimization. Furthermore, we discuss the challenges and future prospects gained from COVID-19 and other infectious diseases, covering knowledge of artificial intelligence strategies, the utilization of medicinal chemistry tools, and advancements in nanotechnology applications. The application of artificial intelligence in drug discovery is increasingly prevalent, particularly in the areas of protein structure prediction, drug target identification, and bioactivity forecasting. Nanotechnology has played a crucial role in the delivery of antiviral drugs and the development of vaccines, exemplified by the use of lipid nanoparticles in mRNA vaccines. Additionally, we highlight potential future directions for drug discovery, such as targeting membraneless organelles (liquid‒liquid phase separation).

Signal Transduction and Targeted TherapyVol. 11(1)
Qingdao University (CN), Qingdao University of Science and Technology (CN), Shandong University (CN), Institut des Sciences Moléculaires (FR), Korea Research Institute of Chemical Technology (KR), Shandong University of Science and Technology (CN)
Good health and well-being
Openalex Percentile: Top 44%
Computational Drug Discovery Methods
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