A University of Arkansas chemist has received a $1.5 million grant “to develop mathematical models to improve the reliability and efficiency of computer-aided drug design,” according to a news release.
The National Institutes of Health awarded the grant to Feng Wang, associate professor of physical chemistry in the J. William Fulbright College of Arts and Sciences.
“The research could reduce the cost of drug discovery and lead to improvements in public health,” according to the release. “Computer-aided drug design is a critical component of drug discovery and the further development of more efficient, or targeted, pharmaceuticals.” But existing models used to develop these designs are less accurate in showing “the interactions between drug molecules, their targets and their shared environment.”
Wang has a new method to create models “that more accurately predict guest-host interactions and the binding affinities of proteins and ligands — molecules that attach to proteins to form a complex that regulates a biological function,” the release shows. His method is called adaptive force matching, and it’s “an automated protocol that maps the complex landscape of molecular energy into simple mathematical forms.”
The importance of Wang’s research will be to “enable predictive simulations of fundamental properties of drug candidates,” he said. His research method will “shift the focus from creating a general-purpose force field to a rigorous protocol that will enable more efficient and accurate computational studies of the structure and function of drug candidates.”
One goal of the research will be to develop “simulations to identify so-called nisin derivatives, the foundation for a class of drugs — generally referred to as lanitbiotics — that hold great promise in addressing bacterial infections that are resistant to common antibiotics,” according to the release.