Recombinant protein expression technology has revolutionized human health research, enabling
scientists to generate large quantities of protein for small-molecule drug discovery campaigns, for the
development of protein-based drugs, and for studying protein structure and function. Yet while researchers are
adept at producing proteins with known genetic sequences, they possess entirely inadequate knowledge about
the protein's post-translational modifications, both during recombinant expression and when the proteins are
isolated from endogenous sources. Alterations in a protein's post-translational modifications can change the
protein from an active enzyme to a dead one; they can change a protein-based drug from a life-saving
molecule to one that is either ineffective or worse, dangerously immunogenic; these seemingly simple “add-
ons” to proteins can be the defining features that determine whether the protein functions as designed or not.
Characterizing proteins' PTMs is a necessary prerequisite for identifying disease states, modulating protein
binding and function, and producing safe and effective protein-based drugs and vaccines. The long term goals
of my research program are to expedite the analysis of post-translational modifications (PTMs) on proteins, to
use these analytical tools to answer critical health-related challenges, and to widely distribute the technology.
We are pursuing both near-term advancements, such as developing a robust solution to quantifying aberrant
disulfide bonds in recombinant proteins, as well as long-range, revolutionary changes in the way proteins are
analyzed, by laying the foundational infrastructure needed to bring artificial intelligence solutions to the field of
PTM analysis. We will develop and launch these technologies in the context of meaningful biological problems
where field advancements cannot be made without information about proteins' PTMs. Solutions in the fields of
HIV vaccine design, cancer treatment, and antibody therapy will be targeted first.