# Biomolecular Recognition with Synthetic Protein Mimics

> **NIH NIH R35** · NEW YORK UNIVERSITY · 2024 · $41,623

## Abstract

Abstract
Interactions of proteins with other biomolecules regulate fundamental cellular events and misregulation of these
interactions leads to disease states. Proteins often utilize small folded domains for recognition of other
biomolecules. The basic hypothesis guiding our research is that by mimicking these folded domains we can
specifically inhibit chosen protein complex formation with rationally designed synthetic molecules. Based on this
hypothesis, we have developed a suite of Protein Domain Mimics (PDMs) that faithfully reproduce binding
epitopes on protein surfaces. This work has created a foundation for the development of a new class of
structure–based therapeutics. Equipped with our platform of PDMs, we will focus on a currently intractable
class of targets in IDPs or Intrinsically Disordered Proteins. Therapeutic targeting of intrinsically disordered
proteins is attractive because they interact with a multitude of partners and influence numerous signaling
pathways. However, targeting of IDPs remains underexplored. We hypothesize that we can engage cellular IDPs
with biomolecular receptors and scavenge them away from their natural binding partners. This strategy would
constitute a distinct mechanism for targeting of IDP-mediated protein-protein interactions. In a new direction for
the group, we will develop encodable ligands to sequence-specifically target double-stranded RNA, the most
abundant class of cellular RNA. dsRNA has proven to be recalcitrant to therapeutic intervention; although, it is
central to many biological events. In preliminary results, we have discovered a new class of molecular scaffold
that can be engineered to provide sequence-specific recognition of dsRNA. Studies in each Aim will advance
general approaches to inhibit protein-protein and protein-RNA complexes, and establish PDMs as distinct
constructs spanning the molecular size space between small molecules and proteins.

## Key facts

- **NIH application ID:** 11099256
- **Project number:** 3R35GM130333-06S1
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** Paramjit S Arora
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $41,623
- **Award type:** 3
- **Project period:** 2019-02-01 → 2029-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11099256

## Citation

> US National Institutes of Health, RePORTER application 11099256, Biomolecular Recognition with Synthetic Protein Mimics (3R35GM130333-06S1). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/11099256. Licensed CC0.

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