University of Houston Awarded $1.26M NIH Grant to Outsmart Superbugs
UH researchers receive $1.26 million NIH grant for antibiotic-resistance study
University of Houston researchers will use artificial intelligence and quantum sensing methods in an effort to identify bacterial mutations that could lead to antibiotic resistance before they emerge.
Chemistry professors Yuhong Wang and Shoujun Xu received a four-year, $1.26 million grant from the National Institutes of Health to study two bacterial proteins involved in protein synthesis, the university said. The work will focus on elongation factors G and Tu, known as EF-G and EF-Tu, which are essential to ribosome function.
The researchers aim to examine how mutations change the shape and behavior of those proteins, potentially allowing bacteria to evade antibiotic treatments. Their work is intended to support development of treatments for antibiotic-resistant infections such as methicillin-resistant Staphylococcus aureus, or MRSA.
The project combines AlphaFold-based computational screening with laboratory measurements using an atomic magnetometer, a highly sensitive sensor more commonly associated with quantum physics research. The team plans to use the AI tool to model protein forms and screen possible drug compounds, then test selected candidates with its force-spectroscopy methods.
Xu said the laboratory’s approach, called dual force spectroscopy imaging, is designed to test multiple molecular interactions at once. The researchers use magnetic fields and microscopic magnetic beads to measure binding forces and protein movements.
The new award brings Wang and Xu’s NIH support for ribosome-related research to more than $3.5 million over 11 years, according to the university. Earlier work by the group found that a mutation at a protein’s GTP-binding site could trigger a structural change elsewhere in the molecule.
Ultimately, the researchers hope to build software that assesses a bacterial protein sequence for likely mutation hotspots, helping drug developers design inhibitors aimed at anticipated resistant variants.