Virtual Screening for the Antiviral Drug Discovery of Coronavirus

There are currently no approved antiviral drugs for treating coronavirus infections. In the face of an acute outbreak, we hope to adopt a more efficient approach to develop antiviral drugs. There are two main methods for drug screening, including high-throughput screening (HTS) and virtual screening. The HTS method realizes automatic operation and sensitive detection, but the positive rate is low (less than 1/10000), thus the cost is relatively high. However, the positive rate of high-throughput virtual screening is generally around 5%-20%. And the results of virtual screening can be combined with experimental screening to complement each other. Thus, virtual screening has become a classic and efficient method for lead compound discovery. Creative Biostructure can perform large-scale high-throughput virtual screening against multiple public/commercial chemical databases and our established databases of commonly used antiviral drugs, winning valuable time for your project on the development of antiviral drugs specific for coronaviruses.

Application of Virtual Screening in Antiviral Drug Discovery

Once the crystal structure of the viral protein (potential drug target) is obtained, we can use virtual screening technology to screen preclinical candidate drugs. Using the technique of homology modeling, we can even construct a three-dimensional (3D) structural model of the target for virtual screening only when the amino acid sequence of the viral protein is known.

For a sudden outbreak of infectious disease, finding suitable candidates from old drugs or pharmacologically active molecules that are already on the market or in clinical trials has a time advantage over developing new drugs from scratch. Using the virtual screening technology, we can simulate the binding conformation of each old drug molecule in the viral protein pocket, and evaluate its theoretical binding strength through scoring function and free energy calculation, thereby analyzing the possibility of the molecule becoming a potential inhibitor. Current studies have used virtual screening technology to screen out some promising drug candidates against coronavirus infection.

Virtual Screening for the Antiviral Drug Discovery of CoronavirusFigure 1. Structure-based virtual screening for potential drug discovery of SARS-CoV-2. (Wu C.; et al. 2020)

Virtual Screening Services for the Antiviral Drug Discovery of Coronavirus

Creative Biostructure provides custom virtual screening services for coronavirus antiviral drugs with our structure-based drug discovery platform. Using the known 3D structure of the target or model obtained by homology modeling, we search for compounds that may bind to the target protein through virtual screening. Our virtual screening service can significantly improve the hit rate and reduce the cost of traditional screening.

We provide a full set of virtual drug screening services to customers with virtual screening needs of antiviral drugs, including but not limited to target structure determination, homology modeling, compound library preparation, and virtual screening based on molecular docking. Based on the target structure, Creative Biostructure can carry out high-throughput virtual screening against multiple public and commercial chemical databases (such as ZINC drug database, FDA approved, and DrugBank). In addition, we can also utilize the in-house antiviral virtual compound library to conduct virtual screening.

The customer only needs to offer biological information related to the target, such as the structural model of the target or the amino acid sequence of the protein. With a full understanding of the research system, we usually adopt the multi-model approach and parallel and/or serial screening strategies. Our expertise has helped a lot in improving the hit rate, thanks to our keen instincts transformed from years of experience.

Contact us to discuss your project!


  1. Wu C.; et al. Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods. Acta Pharmaceutica Sinica B. 2020.

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