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"At a fundamental level, many diseases can be traced to a molecule not binding correctly," said Wesley Errington, a University of Minnesota biomedical engineering postdoctoral researcher and lead author of the study. "By understanding how we can manipulate these 'dials' that control molecular behavior, we have developed a new programming language that can be used to predict how molecules will bind."
The need for a mathematical framework to decode this programming language is highlighted by the researchers' finding that, even when the interacting molecule chains have just three binding sites each, there are a total of 78 unique binding configurations, most of which cannot be experimentally observed. By dialing the parameters in this new mathematical model, researchers can quickly understand how these different binding configurations are affected, and tune them for a wide range of biological and medical applications.
"We think we've hit on rules that are fundamental to all molecules, such as proteins, DNA, and medicines, and can be scaled up for more complex interactions," said Errington "It's really a molecular signature that we can use to study and to engineer molecular systems. The sky is the limit with this approach."
In addition to Sarkar and Errington, the research team included Bence Bruncsics from the Budapest University of Technology and Economics who was a visiting masters' student in the Sarkar lab at the University of Minnesota. The team also partnered with the Institute for Therapeutics Discovery & Development (ITDD) in the University of Minnesota's College of Pharmacy for the lab experiments to test the computational model. The research was funded by the National Institutes of Health. Source:
University of Minnesota College of Science and Engineering Journal reference:
Errington, W.J., et al. (2019) Mechanisms of noncanonical binding dynamics in multivalent protein–protein interactions. The Proceedings of the National Academy of Sciences . doi.org/10.1073/pnas.1902909116 .
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