Development of Antiviral Therapies Against Nipah and Hendra Viruses

The proposed work addresses the FY21 PRMRP topic area of emerging viruses. The henipaviruses Nipah virus (NiV) and Hendra virus (HeV) are members of the paramyxovirus family and are emerging pathogens causing increasingly more frequent outbreaks in the Asia-Pacific region. The more familiar measles virus (MeV) is also a member of this family, but henipaviruses NiV and HeV are biosafety level four (BSL-4) pathogens. The latest outbreak of Nipah virus occurred in 2018. NiV and HeV are some of the deadliest pathogens known to humanity as infection results in respiratory and encephalitic illness with mortality rates up to 75%. The current standard of care is supportive care. Therapeutics consist of the general-purpose antiviral Ribavirin, of limited efficacy, and recently Favipiravir, developed for emerging influenza strains in Japan, as an experimental treatment. Since no U.S. Food and Drug Administration-approved therapeutics are available, we need to develop an approach to efficiently identify novel drugs to be further developed into effective interventions. Data on NiV/HeV inhibitors is limited, but more chemical inhibitors of MeV are known. Using available small-molecule structure-activity relationships from MeV inhibitors, and common molecular features of MeV and NiV in F-protein, this work creates a primitive artificial neural network (ANN) to predict new NiV inhibitors. The machine algorithm will be transferred to a supercomputer and used to perform a virtual screen of 40MM compounds to seek new anti-NiV compounds. A single, high concentration of potential antivirals will be tested for the ability to block NiV and HeV infection with minimal toxicity. Compounds will be subsequently tested for antiviral activity at several non-toxic concentrations to determine if there is a dose-dependent block of infection. Promising compounds will serve as chemical templates for analogs in pilot medicinal chemistry campaign, and x-ray protein crystallography will be attempted to demonstrate binding of the antiviral candidates to F-protein. Demonstration of a machine-learning approach to new antivirals for emerging diseases will enable identification of new antiviral candidates, in vivo proof-of-concept studies and preclinical development programs to be funded by the Department of Defense or organizations such as the National Institutes of Health National Institute of Allergies and Infectious Diseases. Less