# Engineering Gp2 as a small ligand scaffold

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2020 · $319,422

## Abstract

Molecular recognition ligands are critical for molecular diagnostics, targeted therapy, and biological study.
Robust, efficient discovery of stable, selective affinity ligands towards the multitude of important targets would
accelerate advances in these fields. Though numerous scaffolds – ranging from antibodies to alternative
topologies – have been developed to fill these needs, all have limitations. Importantly, the ability to efficiently
evolve binding functionality onto an ultra-small scaffold, while retaining biophysical integrity, would be a
powerful advance. Small size aids extravasation, tissue penetration, and clearance of unbound background
ligand for improved physiological performance, particularly for molecular imaging. Moreover, small single
domains facilitate production, site-specific conjugation, and designer multi-functional fusions. To this end, we
have discovered the 45-amino acid Gp2 domain via a bioinformatics approach, and we have validated its
efficacy as a ligand capable of strong, specific binding while retaining stability. Herein, we propose to advance
development of this scaffold.
The objective of this research is to engineer the framework and diverse paratope of the 45-amino acid
Gp2 domain to advance its utility as a molecular targeting scaffold and exemplify utility by development of
positron emission tomography imaging agents for PD-L1. The research plan consists of three aims. (1)
Advance combinatorial library design – with a sitewise gradient of diversity identified via high-throughput ligand
evolution and deep sequencing feedback – to enable direct selection of strong, specific binders in the Gp2
scaffold. Thousands of diverse Gp2 ligands will be evolved from a naïve combinatorial library. Deep
sequencing will reveal sitewise amino acid frequencies that will guide second-generation library designs.
These designs will be comparatively evaluated for evolutionary fitness. Evolved Gp2 ligands will be functionally
and biophysically characterized. (2) Engineer the Gp2 framework to enhance proteolytic and thermal stability,
solubility, and physiological passivity. Two innovative stability-engineering strategies will be compared to more
conventional approaches to inform evolution and identify an improved Gp2 framework. Modulation of
hydrophilicity and charge will further improve the Gp2 framework. (3) Perform preclinical development of
molecular PET imaging agents for PD-L1 capable of specific, sensitive early time point (~1 h) imaging. The
advanced paratope evolution and framework of Gp2 will be applied to develop 5 kDa domains that selectively
target PD-L1 in vivo. These will be compared to antibodies and fragments for PET imaging in xenografted
mouse tumor models.

## Key facts

- **NIH application ID:** 9895785
- **Project number:** 5R01EB023339-04
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Benjamin Hackel
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $319,422
- **Award type:** 5
- **Project period:** 2017-07-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9895785

## Citation

> US National Institutes of Health, RePORTER application 9895785, Engineering Gp2 as a small ligand scaffold (5R01EB023339-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9895785. Licensed CC0.

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