Decoding protein ADP-ribosylation networks in neurons using a chemical genetic ap

Project: Research project

Project Details


DESCRIPTION (provided by applicant): The objective of the proposed research is to generate chemical tools that will expand our understanding of ADP-ribosylation in neuronal physiology. ADP-ribosylation was originally thought to be catalyzed by a single enzyme, ARTD1 (ADP-ribosyltransferases 1), but a family of 17 proteins is now recognized in humans that shares structural homology to the ARTD1 catalytic domain. ARTD1, and perhaps other ARTDs, play essential roles in cellular pathways in neurons that mediate long-term memory (LTM)~ however, their roles in these processes are not well understood. Moreover, the direct protein targets of individual ARTDs in neurons are not known, hindering our ability to fully delineate the
pathway from ARTD activation to LTM. Our current lack of understanding of the specific role of ARTD1, and other ARTDs, in neurons and in other cell types has been severely limited by the lack of inhibitors of individual family members and the inability to identify the direct targets fr individual ARTDs in a cellular context. To overcome these limitations, this application describes, for the first time, the design and synthesis of (1) mono-selective inhibitors and (2) orthogonal NAD+ substrate analogs of ARTD1 mutants that are engineered to contain a unique pocket absent from wild-type ARTDs, but retain enzymatic activity. These orthogonal NAD+ analogs will be used for the identification of direct targets of ARTD1 in neurons. While initial studies wll focus on the role of ARTD1 in neurons, we anticipate that our strategy can be generalized to other ARTDs, thereby potentially providing unprecedented insights into their roles in physiology and pathophysiology.
Effective start/end date7/15/144/30/19


  • National Institutes of Health: $335,458.00
  • National Institutes of Health: $335,458.00
  • National Institutes of Health: $335,458.00


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.