Broad-Spectrum Inhibitors of Future Emerging Viruses
Abstract
The goal of our project is to design a concrete approach for proactive acquisition of broad-spectrum antivirals against emerging viruses ahead of outbreaks that occur in human populations. If successful, our approach can be implemented for design of broad-spectrum antivirals for use by military and medical personnel at risk of infection during deployment to affected geographical locales. The project addresses three of the Fiscal Year 2018 Peer Reviewed Medical Research Program Topic Areas, ?emerging infectious diseases,? ?vaccine development for infectious diseases,? and ?Guillain-Barr‚ Syndrome.? Emerging viruses (viruses that suddenly appear in human populations during outbreaks) mainly arise from vertebrate animal species and are transmitted to people directly or by way of arthropod vectors, including mosquitos and ticks. Viruses associated with these outbreaks are diverse and come from different families of viruses that have different replication strategies. In this Discovery Project, we will use a family called the ?flaviviruses? to model our approach to antiviral design. Viruses in the family include known human pathogens including Dengue fever, Yellow fever, West Nile, and Zika virus. Infection with these viruses can cause minor symptoms including fever as well as more serious medical problems including encephalitis, hemorrhagic fever, and damage to the central and peripheral nervous system. Though this initial Discovery Project focuses on members of the flavivirus family, an important goal of the project is to determine whether the approach can serve as a paradigm for identifying antivirals against additional families of viruses with emerging pathogenic species. An innovative aspect of our project is that, to identify molecules that bind and inactivate a component of the virus, we will use a highly focused form of computer-based artificial intelligence (AI). The AI approach is fundamentally different than other approaches used in drug design and is related to technology in use and under development for well-known uses including facial and voice recognition. In essence, the AI of our project is designed to evaluate the molecular and atomic profile and structure of components essential to the virus (rather than, for example, facial features), thereby enabling identification of small molecules (future drugs) that inhibit these components. As with AI designed for other purposes, this computer-based system learns from success and mistakes so that analysis becomes progressively more sophisticated. It is important to point out that the AI we will use has been validated in the purpose for which it was designed. Comparison with other approaches indicates superior performance of the AI system in conventional benchmark tests. The AI system identified inhibitors of different chemical classes than those of other approaches. The AI system is also markedly faster than alternatives allowing virtual screening of extremely large sets of molecules in a few hours rather than several weeks. Finally, the approach has been validated by identification of several molecules that interact with and inactivate their intended target including a viral target. Conventional antiviral drug design typically focuses on a single virus target. Our proposal is further innovative in that we will use an untested approach in which we screen multiple related protein targets in parallel. We will first use AI to target three related members of the flavivirus family. We will then determine whether the molecules we identify actually inhibit these three viruses. We will then see whether the inhibitor(s) are effective against related members of the virus family. If they are, this would indicate that the molecules are likely to useful against an expanded number of flavivirus family members including unidentified or evolving species that may cause future outbreaks. If our Discovery Project is successful, we will use an analogous approach to
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 05, 2019
- Source ID
- W81XWH1910100
Entities
People
- Antonito T Panganiban
Organizations
- Tulane University of Louisiana
- United States Army