The recent coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exerted considerable impact on global health. To prepare for rapidly mutating viruses and for the forthcoming pandemic, effective therapies targeting the critical stages of the viral life cycle need to be developed. Viruses are dependent on the interaction between the receptor-binding domain (RBD) of the viral Spike (S) protein (S-RBD) and the angiotensin-converting enzyme 2 (ACE2) receptor to efficiently establish infection and the following replicate. Targeting this interaction provides a promising strategy to inhibit the entry process of the virus, which in turn has both preventive and therapeutic effects. In this study, we developed a robust and straightforward assay based on the Yeast-Two Hybrid system (Y2H) for identifying inhibitors targeting the S-RBD-ACE2 interaction of SARS-CoV-2. Through high-throughput screening, two compounds were identified as potential entry inhibitors. Among them, IMB-1C was superior in terms of pseudovirus entry inhibition and toxicity. It could bind to both ACE2 and S-RBD and induce conformational change in the S-RBD+ACE2 complex. This is the first study to verify the feasibility of utilizing the Y2H system to discover potent SARS-CoV-2 inhibitors targeting the receptor recognition stage. This approach may also be applied in the discovery of other virus receptor recognition inhibitors.

Rising drug resistance undermines current anti-influenza virus therapies. Although targeting the hemagglutinin (HA)–sialic acid receptor interaction is a promising strategy, progress is impeded by the lack of subtype-independent screening models. Herein, we established a fluorescence-based cell high-throughput model using fluorescein isothiocyanate-conjugated Sambucus Nigra Lectin (FITC-SNA) as a stable HA surrogate and α-2,6-sialyltransferase (ST6GAL1)-overexpressing MDCK cells to mimic the HA–receptor interface. This platform was designed to serve as an efficient primary screening tool to rapidly filter large compound libraries for potential binders to the receptor-binding interface. Screening 10,000 compounds identified Obatoclax Mesylate and Ethylparaben as primary hits. Both exhibited broad-spectrum HA inhibition activity, validating the model’s capability to identify compounds interfering with viral attachment. Further cellular antiviral assays revealed cytotoxicity for both compounds, resulting in low selectivity indexes (SIs), indicating that while these molecules effectively target the interaction site, they require substantial structural optimization for therapeutic use. Molecular docking confirmed their binding to type A H1N1, H3N2, and B/Victoria HA proteins, while ADMET predictions highlighted specific structural optimization needs to mitigate toxicity. In conclusion, this subtype-independent, highly specific high-throughput screening (HTS) model provides an efficient and reliable platform for early-stage influenza drug discovery and lead compound development.