A team led by researchers at the University of Toronto has created a platform, called SIMPL2, that revolutionizes the study of protein-protein interactions by simplifying detection while improving measurement accuracy.
Interactions between proteins play a significant role in biological processes, including those involved in disease. The team behind the SIMPL2 platform designed it to optimize researchers' ability to measure protein-protein interactions for targeted drug therapies. While protein-protein interactions have previously been considered 'undruggable' using small molecules, the platform addresses this challenge by facilitating the measurement of these interactions – improving our understanding of the types of molecules needed to control them.
"Many methods have been developed to measure interactions between proteins, especially more recently as the significance of protein interactions in disease has become more apparent," said Zhong Yao, first author on the study and senior research associate of U of T's Donnelly Centre for Cellular and Biomolecular Research . "However, all of these methods have shortcomings, including high costs and complicated procedures that delay results. The biggest advantages of our SIMPL2 platform are that it produces more reliable measurements and is comparatively cheaper to use."
The study was published recently in the journal Molecular Systems Biology .
Yao started working on the protein interaction measurement problem while developing the original SIMPL (Split-Intein Medicated Protein Ligation) system . SIMPL2 is an update of SIMPL that involves the use of the split luciferase enzyme for detection of protein interactions through luminescence. In addition to improving identification of interactions, the entire measurement process occurs through one medium: liquid. This simplifies the process considerably by reducing the number of steps required to carry out measurements.
"One of the issues with SIMPL was that we had to use an additional process, called ELISA, to identify the proteins spliced by the SIMPL platform," said Yao. "It was a painful process that made an otherwise effective technology more complicated and expensive to use than it needed to be. SIMPL2 only requires one step, which can be performed manually, or it can be automated for even more efficiency in high-throughput studies."
To test the new platform's sensitivity and applicability, the research team used it to measure interactions between proteins affected by modulators. Protein modulators include molecules that inhibit interactions between proteins, those that facilitate protein interactions and those that facilitate the degradation of target proteins. SIMPL2 was found to perform well in identifying these interactions, even in cases where the interactions were weak.
While quantum computers and AI have made it easier to design small molecules for drug therapies, this has led to a need to develop much faster methods for validating the efficacy of new drugs. SIMPL2 can meet that need, as it can be used to test interactions between new molecules and their target proteins in cultured human cells. It is also capable of keeping apace with the rate at which new molecules are being designed.
"We designed SIMPL2 to be a universal method for studying protein interactions that is rapid and inexpensive, as well as highly sensitive," said Igor Stagljar, principal investigator on the study and professor of biochemistry at U of T's Temerty Faculty of Medicine. "Now that we have optimized the platform, our next step is to use it to study interactions that play key roles in diseases, like cancer, to learn how to develop drug therapies. This work will involve the use of quantum computers and AI in collaboration with Alán Aspuru-Guzik's lab at U of T and Insilico Medicine, a global leader in generative AI drug discovery."
This research was supported by FACIT and Ontario Genomics.
