# Identifying favorable regions of the conformational landscapes of peptides and peptidomimetics

> **NIH NIH R35** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $379,131

## Abstract

PROJECT SUMMARY
Therapeutic Potential of Macromolecules: The human interactome, potentially comprising over 650,000
protein-protein interactions (PPIs), remains an underexplored frontier for therapeutics discovery. As just one
example, the interaction between the melanoma antigen, MAGE-A4, and an E3 ligase, RAD18, is hypothesized
to increase DNA damage tolerance, leading to increased resistance of cancer cells to chemotherapies.
Disrupting this interaction could increase the efficacy of chemotherapies.
Macromolecule therapeutics (e.g., peptides and peptidomimetics) are well-suited to disrupt disease-causing
PPIs. However, their design is non-intuitive with challenges including entropic costs associated with protein
binding and limited cell permeability. While existing strategies to decrease the entropic cost, like peptide stapling
and cyclization, have yielded potent therapeutics, they often result in molecules locked in a rigid conformation
that struggle to access their targets within cells due to poor permeability. Interestingly, some bioactive peptides
and peptidomimetics have been identified benefit from some lack of rigidity for cell permeability. Identifying the
role of macromolecule conformation, i.e., degree of disorder, in desirable properties including protein binding
and cell permeability will facilitate the development of a new class of therapeutics.
We propose that compact, yet non-rigid, macromolecules offer valuable, yet under exploited scaffolds for
bioactive macromolecules. This proposal aims to address key biological questions: How does macromolecule
conformation impact binding to “undruggable” protein surfaces and other essential characteristics, such as cell
permeability?
Accelerating Innovation in Macromolecule Therapeutic Design: Our vision is to accelerate the design of
macromolecule-based therapeutics by developing rapid characterization strategies that guide predictive
algorithms. These methods will provide unprecedented comparisons of macromolecule conformation, guiding
the design of macromolecular therapeutics. Three key challenges are addressed in this proposal:
 1. Conformational Characterization: We will establish colorimetric and fluorimetric assays to assess
 average conformation and dynamics of disordered peptides and peptidomimetics.
 2. Predictive Algorithm Development: Develop algorithms capable of identifying sequence spaces that
 favor conformations with a desired degree of disorder.
 3. Protein-Protein Interaction Disruption: By leveraging favorable sequences with desired
 conformations, we will identify effective, cell permeable, disruptors of protein-protein interactions using
 the MAGE-A4 and E3 ligase interaction as a model system.
Innovation and Impact: We aim to provide powerful predictive capabilities that leverage rapid conformational
characterization to guide the design of potent macromolecule therapeutics, specifically for PPI disruption.

## Key facts

- **NIH application ID:** 10941025
- **Project number:** 1R35GM155350-01
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Abigail Knight
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $379,131
- **Award type:** 1
- **Project period:** 2024-09-01 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10941025

## Citation

> US National Institutes of Health, RePORTER application 10941025, Identifying favorable regions of the conformational landscapes of peptides and peptidomimetics (1R35GM155350-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10941025. Licensed CC0.

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