Scientists have used a new high-speed, in vitro selection method to isolate 9 antibody-like proteins (ALPs) that bind to the SARS-CoV-2 virus – 4 of which also exhibited neutralizing activity – within 4 days, according to a new study. While much research has focused on the identification of whole antibodies against SARS-CoV-2 – the causative agent of COVID-19 – less attention has been paid to ALPs, which include monobodies that can offer similar diagnostic and therapeutic advantages. However, established in vitro methods to select small proteins like ALPs have some drawbacks. Phage display, the most common method, generates relatively small libraries of candidates, limiting the utility of this approach in the context of recently described viruses such as SARS-CoV-2. Another method, mRNA display, generates sufficiently large libraries but is time consuming, taking up to several weeks to yield results. Seeking a solution, Taishi Kondo and colleagues refined a method they previously developed, called TRAP display, which streamlines two of the most time-consuming early steps in the mRNA display protocol. Kondo et al. used their TRAP display method to obtain – within 4 days – 9 ALPs that bind to the S1 subunit of the SARS-CoV-2 spike protein complex. Of these 9 ALPs, 4 showed affinity for the domain of the spike protein that binds the ACE2 receptor, suggesting that these ALPs may neutralize the virus’ ability to bind to ACE2 on human cells. Of these 4 ALPs with binding affinity, one blocked SARS-CoV-2’s ability to infect cultured cells in vitro. The authors then used the high-affinity ALP to capture SARS-CoV-2 viral particles from nasal swab samples, demonstrating the ALP’s potential for use in diagnostic tests. “We believe that the monobodies procured in our study will soon be useful to develop effective diagnostic tools and that such tools will contribute to the worldwide effort to overcome the COVID-19 pandemic,” the authors write.
###
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.
