Novel method for assigning probabilities to human protein interactions

The Stowers Institute's Proteomics Center has published a novel method of using normalized spectral counts derived from a series of affinity purifications analyzed by mass spectrometry (APMS) to generate a probabilistic measure of the preference of proteins to associate with one another.

The work - which allows for the assignment of probabilities not only to the interactions within well-defined protein assemblies, but also to interactions between complexes — was posted today to the Web site of the Proceedings of the National Academy of Sciences (PNAS).

Large-scale APMS studies have played important roles in the assembly and analysis of comprehensive protein interaction networks for lower eukaryotes, such as yeast. But the development of such networks for human proteins has been slowed by the high cost and significant technical challenges associated with systematic studies of protein interactions.

The Stowers Institute's Proteomics Center has addressed this challenge by developing a method for building local and focused protein networks. With this computational approach, the probability for two proteins to associate is calculated from the bait-to-prey relationship alone, an improvement over other methods requiring systematic reciprocal bait-prey interactions or co-purification of preys by a third bait.

“Previous protein interaction networks built using protein mass spectrometry data were largely based on binary ‘yes/no' data, where a protein is present in a sample or it is not,” explains Michael Washburn, Ph.D., Director of Proteomics and senior author on the paper. “We were interested in quantitative proteomics approaches. We were able to develop a method to generate more information-rich networks, where the preference of two proteins to associate within a defined complex or within a larger network assembly can be estimated using Baysian probabilities. The new approach adds more information to the analysis of protein complexes and networks, since not all proteins interact in the same way.”

The work not only provides a significant advancement in proteomic analysis, it also holds promise in facilitating the development of treatments for disease.

“By having insight regarding the most probable contacts within a multiprotein complex, we can devise targeted strategies to disrupt specific interactions,” said Mihaela Sardiu, Ph.D., Postdoctoral Research Associate and lead author on the paper. “This could be useful for developing new drugs for disrupting protein complexes involved in disease.”

The Proteomics Center is one of three technology development centers that support research at the Stowers Institute. In addition to collaborating with Stowers Institute independent research teams, the centers pursue cutting-edge solutions to the evolving challenges of basic biomedical research.

“The Stowers Institute's Proteomics Center is providing technology solutions that fundamentally change the way that Stowers researchers approach their work,” said Robb Krumlauf, Ph.D., Scientific Director. “Because of the support provided by our technology development centers, Stowers research teams can approach long-standing problems in new and innovative ways, elevating their research and results.”