As of late March 2020, the 2019 novel coronavirus (COVID-19) had caused more than 20,000 deaths worldwide and forced millions of people into mandatory isolation, resulting in major challenges to the global economy. COVID-19 invades human lung cells and uses the ribosomes in those cells as factories to rapidly synthesize proteins for viral replication. These cause the death of lung cells and damage to the lung tissue. The replicated viruses are then released from dead cells into the mucus, the bloodstream, and through the digestive system. These viruses lead to the failure of lungs, livers and other organs and finally to the deaths of infected patients.
Compared with its relatives SARS and MERS, COVID-19 has spread more rapidly. These coronaviruses invade lung cells by attaching their spike-like surface proteins to the cells’ ACE2 receptor. COVID-19 mutates its spike-like proteins so that it has a stronger binding capability. This explains why COVID-19 can infect people faster than either SARS or MERS. In addition, people infected by COVID-19 may not show any symptoms in the first 14 days, however, they can still pass the virus to other people. This makes detecting and treating COVID-19 even more challenging.
While vaccines are being tested in clinical trials to trigger the human body to generate antibodies for combating COVID-19, vaccine development is expensive and time-consuming. An economic and efficient therapeutic strategy is to repurpose existing drugs. That requires understanding these three steps, which are essential for the rapid replication of COVID-19 in human cells:
- COVID-19 enters lung cells through the respiratory tract
- The synthesis of viral RNA in lung cells begins
- Polyproteins encoded by viral RNA are cleaved into individual functional units for virus replication and packaging
Computational Platform Improves the Search for an Inhibitor
The international scientific community is in a race to develop antiviral agents for targeting these steps to inhibit the rapid replication of COVID-19. For example, Arbidol and Remdesivir are in clinical trials to test their ability to prevent viral entry into host cells and inhibit RNA synthesis, respectively. However, these antiviral agents have relatively low binding affinity with their targets.
Inspired by Villanova University’s values of Veritas, Unitas, and Caritas, my Chemical and Biological Engineering research group has implemented its computational platforms to identify FDA-approved drugs that can inhibit the viral protease 3C-like protease (3CLpro) that is essential for the cleavage of viral polyprotein for COVID-19 replication. Our computational platform can identify small molecule inhibitors for protein targets causing diseases, significantly accelerating pace of the drug discovery and reducing costs.
The success of this platform was evidenced by a recent project in which our group successfully identified two natural products from green coffee beans to inhibit Fosfomycin-resistant Listeria monocytogenes, a deadly foodborne pathogen that causes the high-mortality disease Listeriosis. The results from the Listeria project—"Synergistic Effect of Chlorogenic Acid and Caffeic Acid with Fosfomycin on Growth Inhibition of a Resistant Listeria monocytogenes Strain”—were recently published and selected as the cover image story in ACS Omega, an impactful journal of the American Chemical Society. In addition, Villanova University filed a provisional patent for the work, and PhD students Tianhua Zhai (2nd year) and Betty Zhang (3rd year) were awarded first prize for their contribution to this project in the College’s Engineers Week Graduate Poster Competition. They also presented their research during the Biomedical Engineering Society’s 2019 conference in Philadelphia.
Applying the Platform to COVID-19
Once we learned of COVID-19 and recognized it as a global health challenge, our research group immediately went to work applying our computational platform. COVID-19’s replication in the human body heavily depends on its proteases, which play an essential role in the cleavage of virus proteins and the assembly of the viral shell. Fortunately, the structure of the main protease 3CLpro has been published and it can be a key drug target against the virus. Zhai and Zhang investigated the structure of 3CLp at the atom level and identified key inhibitor binding pockets, after which a deep virtual drug screening was performed on the computational platform. Fortunately, 13 potential small-molecule inhibitors have been identified for 3CLp from the FDA-approved drugs. In addition, our group also studied the common structures shared by all known antivirus agents against 3CLpro. The 13 drug candidates and the common drug structures may provide useful information for further clinical experiments. We are reaching out to international scholars for potential collaborations to combat the COVID-19 pandemic.