UAMS Researcher Develops Model for Predicting Drug Toxicity
| Aug. 24, 2016 | Toxicity is a common reason many drugs are pulled from market and new drug leads fail. Avoiding this outcome requires knowing when drugs are likely to cause toxicity.
As a step in this direction, University of Arkansas for Medical Sciences (UAMS) researcher Grover P. Miller, Ph.D., and collaborators have published a manuscript in the journal ACS Central Science describing their development of a model that predicts the reactivity of molecules toward biological molecules as possible causes underlying drug toxicity.
“Modeling Reactivity to Biological Macromolecules with a Deep Multitask Network,” by Miller and collaborators from Washington University in St. Louis — S. Joshua Swamidass, M.D., Ph.D.; Tyler B. Hughes, Ph.D. candidate; and Na Le Dang, M.D., Ph.D. candidate — was published July 29.
Their research is available to read on the ACS Central Science website at no cost and the researchers have provided open access to their model at http://swami.wustl.edu/xenosite/p/reactivity.
Their model did significantly better than standard methods at predicting known indicators for toxic reactions between drug molecules and DNA and protein.
For the entire data set of 2,803 molecules, their approach yielded totals of 257 (9.2 percent) and 227 (8.1 percent) molecules predicted to be reactive with DNA and protein, respectively. This selectivity is important because those interactions would have been missed by standard reactivity screening experiments used in drug discovery and development.
Miller, associate professor of biochemistry and molecular biology in the UAMS College of Medicine, credited a National Institutes of Health grant for bringing together his expertise in metabolism and experimental research and Swamidass’ expertise in computational models and statistics for developing and validating models of metabolism.
“The development of safer drugs requires knowledge of the mechanisms underlying adverse drug reactions so that they can be avoided during patient care,” Miller said. “Our model marks a significant advancement in not only identifying problem drugs but how to avoid those processes in guiding the development of safer, more effective drugs.”
ACS Central Science is a publication of the American Chemical Society that publishes select, stringently reviewed reports on research in chemistry and in allied fields, wherein chemical approaches play a key role.
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