Discovering Regulatory Post-translational Modifications (PTMs) Involved in Pharmacology and Disease Using Machine Learning and Experimental Biology

Post-Translational Modifications (PTMs) – chemical or proteinaceous alterations to proteins contained within living cells – are a rapidly expanding class of biological feature that diversify the function of proteins in a proteome. By definition, PTMs change protein structure and therefore have the potential to affect protein function by altering protein interactions, protein stability or catalytic activity (1, 2). As they have been found to occur on most proteins in the eukaryotic proteome, PTMs broadly impact nearly all known cellular processes. With ever-increasing performance of hi-throughput mass spectrometry-based proteomics, the current rate at which unique PTMs are identified far surpasses the rate at which their functional implications can be investigated experimentally. We have addressed this problem through the creation of a novel tool called SAPH-ire, which utilizes artificial neural networks to enable functional prioritization of PTMs based on meta-data collected over the last 50 years. We have also used SAPH-ire to discover novel PTM regulatory elements in several protein families – most notably those involved in G protein signaling, which mediates the action of hormones and neurotransmitters, and is also the most common target for human pharmacotherapy. I will describe a novel and well-conserved phospho-regulatory element in G protein gamma subunits, which we discovered using SAPH-ire and have shown experimentally to be a primary control point for differential kinase activation decision making, as well as kinase activation rate and amplitude. Together, these discoveries change the paradigm of how G protein signaling can be modulated, and include G protein gamma subunits as fundamental elements in this process.

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Event Details


  • Thursday, September 21, 2017
    10:55 am
Location: Georgia Tech, EBB 1005