San Antonio scientists are using machine learning to identify potential treatments for deadly viruses
A team of San Antonio-based biomedical researchers trained a machine learning algorithm to identify more than two dozen viable treatments for diseases caused by zoonotic pathogens that can spread from animal hosts to infect humans. Scientists at the Southwest Research Institute (Swri), the University of Texas at San Antonio (UTSA), and the Biomedical Research Institute (Texas Biomed) used the Swri-developed Rhodium™ software to study bat-born Nipah and Hendra henipaviruses that are common in some parts of the world, particularly in Lusthals, in humans. Through collaboration, researchers mapped the protein structure of the...
San Antonio scientists are using machine learning to identify potential treatments for deadly viruses
A team of San Antonio-based biomedical researchers trained a machine learning algorithm to identify more than two dozen viable treatments for diseases caused by zoonotic pathogens that can spread from animal hosts to infect humans. Scientists at the Southwest Research Institute (Swri), the University of Texas at San Antonio (UTSA), and the Biomedical Research Institute (Texas Biomed) used the Swri-developed Rhodium™ software to study bat-born Nipah and Hendra henipaviruses that are common in some parts of the world, particularly in Lusthals, in humans.
Through the collaboration, researchers mapped the protein structure of the measles virus, which is in the same family of viruses as henipaviruses. Using masers as a blueprint, rhodium was practically examined and compounds evaluated for appropriate structures and binding efficiency. Out of 40 million compounds, Rhodium identified 30 potentially viable viral inhibitors for Nipah and Hendra. Although research has focused on antiviral treatments for henipaviruses, any broad-spectrum therapeutic could potentially treat related viruses, including measles.
“The results suggest that machine learning can quickly identify antiviral candidates for highly pathogenic viruses that are difficult to study due to space limitations and biosafety constraints,” said Dr. Jonathan Bohmann, a human resources scientist at Swri, who presented these findings at the Hendra@30 Henipavirus International Conference in Melbourne, Australia, in Australia, Australia. “Our algorithms allow us to best utilize resources to provide a “short list” of potential treatments for further testing.”
This Department of Defense research is funded by the Peer-Reviewed Medical Research Program (PRMRP) under the Congressional Medical Research Programs (CDMRP) and opens the door to finding treatments for Nipah and Hendra. According to the World Health Organization, 40-75% of people infected with these diseases die.
Henipaviruses are deadly pathogens. They are endemic to animal populations in Asia and Australia, but the events on livestock and humans occur regularly seasonally, which concerns due to the pandemic potential. “
Dr. Jonathan Bohmann, human resources scientist at Swri
Studying such infectious diseases requires adherence to strict safety standards and access to a BSL-4 high-containment laboratory. By virtually screening compounds, researchers save time and resources.
“Our work underscores the power of collaborative, multidisciplinary research at our San Antonio institutions to assemble a comprehensive and cohesive strategy for the development of novel antiviral drug candidates,” Dr. Stanton Mcchardy, University of Texas Professor and Director of Medicinal Chemistry and Synthesis Core Features for Innovative Effectiveness.
“Rhodium does a very good job of eliminating compounds that are toxic and finding effective disease inhibitors,” said Dr. Olena Shtanko, an assistant professor at Texas Biomed, who worked with McHardy and Bohmann by evaluating the effectiveness of the antiviral compounds identified by rhodium. “We have made quite a bit of progress in a short period of time, but more research is needed.”
SWRI's Pharmaceutical and Bioengineering Division provides FDA-unheard facilities that meet current standards for good manufacturing practices.
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