PICS Colloquium with Professor Peter DiMaggio of Imperial College

Over the past two decades, the rapid development of high-throughput technologies within the fields of proteomics and genomics for measuring thousands of biomolecules in a single experiment has shown great promise in transforming our understanding of fundamental biology. Unfortunately, the observation of a two-fold change or greater in a protein is often not a descriptive biomarker for differentiating between normal and diseased states. We now realize that in addition to the number of protein molecules present, we also need to be able measure the various covalent modifications on proteins and understand how this affects their interactions with other proteins, nucleic acids and small molecules within the complex cellular environment. While mass spectrometry (MS) has found widespread success in its ability to quantify changes across thousands of proteins, it does not scale well in measuring protein modifications other than phosphorylation.

In this work I will present multidisciplinary technologies that enable us to utilize mass spectrometry in rather non-conventional ways to address a range of problems in this field. A central theme throughout my talk is how we can combine bespoke chemical biology, quantitative mass spectrometry and informatics tools to discover the targets and functions of protein modifications. First, I will present a computational design strategy for the engineering of small molecule cofactors to identify unknown targets of protein-modifying enzymes, with a particular emphasis on a class of enzymes that adds a methylation modification to other proteins but is aberrantly regulated in various cancers. I will then present a metabolic labelling strategy that has enabled us to shed novel insight into the functions of ADP-ribosylation, which is a relatively understudied protein modification due to the lack of analytical technologies for measuring it within cells. Throughout my talk I will highlight the computational challenges that we need to address and hope to demonstrate how progress in these fields can be greatly facilitated by a truly multidisciplinary effort, as our engineering framework leverages complementary strengths across several areas including chemical biology, computational biology and Bayesian statistics.

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More information about past and future colloquium can be found here.