# Computational design and evaluation of peptide-guided protein degraders

> **NIH NIH R41** · UBIQUITX, INC. · 2024 · $306,872

## Abstract

PROJECT SUMMARY
Pharmacologically targeting intracellular proteins is a key challenge of modern drug development, requiring
innovation and the development of new technologies. This challenge is made more difficult by the fact that many
protein targets remain beyond the reach of established drug discovery technologies because they lack easy-to-
find and unique binding pockets, possess large, and flat contact areas. Indeed, ~85-90% of the human genome
is considered “undruggable,” encoding proteins that are deemed too challenging to bind with conventional
molecules. Hence, new approaches are needed for drugging intracellular protein targets. To address this unmet
need, this project seeks to develop a new class of computationally-designed mRNA therapeutics that encode
peptide-guided protein degraders, known as ubiquibodies (uAbs), for potent and selective degradation of
historically undruggable targets not addressable by conventional drugs. Specifically, uAbs are modular,
programmable proteins consisting of a genetically engineered fusion between an E3 ubiquitin ligase, linker, and
protein/peptide guide. Following ectopic expression in cells, these heterobifunctional chimeras direct the activity
of an E3 to a protein of interest (POI), leading to polyubiquitination and subsequent degradation of the POI by
the endogenous ubiquitin-proteasome pathway (UPP). The objective of this Phase I STTR is to design
customized uAbs against β-catenin and CCAAT/enhancer-binding protein homologous protein (CHOP), two
intracellular transcription factors that hold promise as drug targets for hepatocellular carcinoma (HCC), alpha-1
antitrypsin deficiency (AATD), and other liver diseases. The hypothesis of this project is that uAbs can be
designed to selectively remove cytosolic/nuclear β-catenin and CHOP, with the potential to inhibit the tumorigenic
and proteotoxic potential, respectively, of these drug targets while also limiting toxicity. The plan to address these
hypotheses includes first leveraging an artificial intelligence/machine learning (AI/ML)-powered platform to
create designer uAbs that selectively degrade cytosolic/nuclear β-catenin and CHOP (Aim 1) and then to develop
and evaluate a lipid nanoparticle (LNP)-based strategy for systemically delivering synthetic uAb-encoding
mRNAs in cultured cells and mice. The best performing mRNA-LNP formulations will then be evaluated in mice
to assess biodistribution, efficiency and duration of target degradation, and biological impacts. Overall, the
proposed studies will demonstrate a new paradigm for drugging the proteome based on computational design
of peptide-guided uAbs, with proof-of-concept studies in this Phase I proposal focused on accelerating the
removal of two key intracellular disease drivers through LNP-mediated delivery of mRNA encoding customized
uAbs. Successful completion of this project will lead to a future Phase II application that will explore the
therapeutic potential of uAbs following systemic d...

## Key facts

- **NIH application ID:** 10830693
- **Project number:** 1R41GM153081-01
- **Recipient organization:** UBIQUITX, INC.
- **Principal Investigator:** Luiz Miguel Quinn Camargo
- **Activity code:** R41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $306,872
- **Award type:** 1
- **Project period:** 2024-03-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10830693

## Citation

> US National Institutes of Health, RePORTER application 10830693, Computational design and evaluation of peptide-guided protein degraders (1R41GM153081-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10830693. Licensed CC0.

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