Innovative computer modeling technique predicts how protein molecule behavior in response to environmental conditions

In a development that could have great significance for efforts to understand how the basic molecular machinery of life works, researchers at the University of Texas Medical Branch at Galveston (UTMB) have successfully applied an innovative computer modeling technique to predicting how protein molecules will behave in response to different environmental conditions.

The scientists present their results in a paper published online this week by the Proceedings of the National Academy of Sciences (PNAS), describing how a computer model they created can predict how changes in acidity or alkalinity (as measured by pH) affect the functional properties of staphylococcal nuclease, a protein crucial to the reproduction of a species of infectious bacteria. Small alterations in pH also trigger crucial shape and function changes in proteins involved in such important processes as carrying oxygen in the blood, activating bacterial toxins, and influencing the infectivity of viruses including HIV, influenza and polio.

“The idea is, proteins fluctuate, and these fluctuations determine how the protein molecule behaves,” said Vincent Hilser, an associate professor of human biological chemistry and genetics at UTMB and senior author on the paper. “We picked pH because it’s easy to measure experimentally, it’s biologically important and it provides us with a way to connect the idea of fluctuations, binding and global protein changes. But there are implications for all sorts of other biomedically relevant properties as well.”

Hilser’s system, which he and his UTMB colleagues (including lead author Steven T. Whitten) have been developing over the last 10 years, differs fundamentally from other approaches to predicting protein structure and function. Instead of attempting to determine a protein’s precise shape at any given moment, Hilser’s “ensemble-based” model uses basic thermodynamic equations to generate more than a million possible fluctuations in the protein’s form. Then it integrates these “microstates” to calculate the protein’s most likely behavior.

To describe his method, Hilser offered the analogy of trying to understand a feature-length movie from only a few thousand frames of film. “You could have a lot of frames from one scene, and you might learn a lot about that one scene, but you won’t learn anything about the plot of the movie,” he said. “If you space them out, you might not get a lot of detail about the individual scenes, but you’ll sure get a better picture of the whole movie, and that’s the approach we take.”

One specific biomedical area where that better picture could produce significant results, Hilser said, is the design of drugs that will stay at a high serum level after administration to a patient. “Your body and your cells use pH in regulating the internalization and the degradation of every single serum drug,” Hilser said. “This sort of technology has the potential to impact anything that’s related to the internalization, degradation and recycling of proteins.”

The paper, “Local conformational fluctuations can modulate the coupling between proton binding and global structural transitions in proteins,” by Whitten, Bertrand Garcia-Moreno of Johns Hopkins University and Hilser, appears this week on the PNAS Early Edition web page.