# Developing computational methods to identify of endogenous substrates of E3 ubiquitin ligases and molecular glue degraders > **NIH NIH F30** · DREXEL UNIVERSITY · 2024 · $48,852 ## Abstract Project Summary/ Abstract: The E1-E2-E3 ligase cascade is responsible for tagging substrate proteins with ubiquitin. Addition of ubiquitin then directs the tagged protein along one of several paths, including marking it for proteasome-mediated degradation. The E3 ligase is responsible for recognition of substrate proteins, and thus encodes the specificity of ubiquitin transfer. The human proteome comprises about 600 known E3 ligases, each with a distinct substrate specificity that allows it to engage a prescribed subset of the proteome. Given that one of the prototypical consequences of ubiquitination is to mark a protein for destruction, it is unsurprising that dysregulation or mutation of E3 ligases can lead to a disruption of cellular homeostatic balance: accordingly, E3 ligases have been implicated in a wide variety of diseases including autoimmune disease and cancer. Intriguingly, certain disease-associated mutations have been found to alter the substrate specificity of an E3 ligase – these mutations not only impact the cellular levels of proteins within the E3’s normal interactome, but rather they change the E3 ligase’s interactome. Similar effects have also been observed from certain small molecules, termed molecular glues, that also modify the substrate specificity of an E3 ligase: these compounds typically redirect an E3 ligase to ubiquitinate some “neo-substrate”, ultimately leading to degradation of this protein. Thus, molecular glues afford the possibility of targeting disease-causing proteins that were previously thought to be undruggable. To date, however, the transient nature of E3 ligase’s interactions with their substrates (and neo-substrates) has served as a bottleneck for identifying both endogenous and “glue-able” substrates of E3 ligases. To address this, here I propose to develop cutting-edge structure-based machine learning methods to (1) computationally identify endogenous substrates of E3 ligases, and (2) rationally design molecular glues that degrade a traditionally undruggable target protein. After carefully benchmarking the underlying methods for each task, I will apply the former to comprehensively catalog substrates of three specific disease-relevant E3 ligases. In parallel, I will apply my approach for the latter to design molecular glues intended to degrade ADAR1, a key protein that promotes resistance to immune checkpoint blockade therapy and is thus a potential target for intervention in many different cancers. Beyond the immediate scope of this proposal, I anticipate that the methods developed through these studies will help illuminate the underlying biology of many other E3 ligases, and will facilitate development of molecular glue degraders targeting key drivers in many other diseases. ## Key facts - **NIH application ID:** 10930694 - **Project number:** 5F30EB034594-02 - **Recipient organization:** DREXEL UNIVERSITY - **Principal Investigator:** Victoria Mischley - **Activity code:** F30 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $48,852 - **Award type:** 5 - **Project period:** 2023-07-01 → 2027-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10930694 ## Citation > US National Institutes of Health, RePORTER application 10930694, Developing computational methods to identify of endogenous substrates of E3 ubiquitin ligases and molecular glue degraders (5F30EB034594-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10930694. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*