Small-Molecule Inhibitors of ERGIC-53
Abstract
The accelerating emergence of viral epidemics has been a deadly trend of the 21st century. Effective therapies are rarely available to combat these diseases, and in general, the world remains unprepared to manage future outbreaks. An Ebola virus outbreak from several years ago resulted in >11,000 fatalities and economic costs of >$32B, while the global economic loss from the 2003 SARS1 epidemic was ~$40B. In 2017, travel and pregnancy restrictions within the Americas were due to the Zika virus and its high correlation with a surge of infant microcephaly. Currently, the world is experiencing unprecedented hardship from the COVID-19 (SARS-CoV-2) pandemic, which has already resulted in over 3 million deaths globally. Unfortunately, unless more effective broadly acting first-line drugs are available for rapid deployment, this is neither the first nor the last time the world will be in this plight. The initiation of Operation Warp Speed in 2020 was heroic in that it provided effective anti-SARS-CoV-2 vaccines in record time. However, it is notable that this effort still took a year and, had an effective broad-spectrum antiviral been available in 2019, we may have avoided the current pandemic altogether. Our proposal aims to use artificial intelligence (AI) to develop a broad-spectrum therapeutic that inhibits a cellular protein required for the replication of a diverse array of RNA viruses responsible for outbreaks in human populations. Thus, our project addresses the FY21 PRMRP Topic Area, Emerging Viral Diseases. Traditional antiviral drug development has relied on a one-bug-one-drug strategy, resulting in only a few vaccines and therapies to address the most predominant viruses. This approach is impaired by the rapid mutation rate of most viruses (rendering previously developed targeted therapies inactive) and the high development costs associated with targeting an expanding large number of individual viruses. Crucially, viruses are intracellular parasites that require host cellular components for their propagation. Our innovative project targets a cellular protein called ERGIC-53, which is required for the reproduction of a large number of diverse virus families, including the coronaviruses, filoviruses (e.g., Ebola), orthomyxoviruses (e.g., influenza), and a number of other families with emerging pathogenic members. By targeting a host protein, we preempt escape mutants that commonly arise when directly targeting the virus. An additional attribute of the host protein target is that it is not required by the host (humans), so inhibiting the protein with an antiviral should be easily tolerated. If successful, this will be an important advance since the antiviral would be effective against many different viruses with outbreak potential, including those currently known as well as those that have not yet been identified. Our approach uses AI in conjunction with virology. The AI component uses a deep learning architecture similar to AI that is used in facial recognition. In this case, however, AI is used to look at the contours of a protein (rather than a face) at the atomic level and identify compounds that are likely to fit tightly with the protein to inhibit it. We will identify molecules that fit tightly with ERGIC-53 and that, as a result, inhibit virus propagation. The approach has a good track record as it has recently been used successfully against a large number of proteins. Several human pathogens will be used to test the hypothesis that ERGIC-53-inhibiting molecules block viruses from diverse virus families. An antiviral drug against a large number of human pathogenic viruses would be extremely useful for military and medical personnel working in the geographical locale of virus outbreaks and, potentially, for civilian populations to block nascent epidemics and pandemics. Thus, our project is of high potential impact. If our Discovery project is successful, we intend to apply for a PRMRP Expansion grant to dev
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210209
Entities
People
- Antonito T Panganiban
Organizations
- Tulane University of Louisiana
- United States Army