# Predictive Structure-based Guidelines for Identifying Optimal PEGylation Sites within Proteins and Understanding the Context-Dependence of Non-covalent Interaction Strength

> **NIH NIH R15** · BRIGHAM YOUNG UNIVERSITY · 2020 · $435,750

## Abstract

Predictive Structure-based Guidelines for Identifying Optimal PEGylation Sites within Proteins and
Understanding the Context-Dependence of Non-covalent Interaction Strength
 Our goal is to develop structure-based tools for identifying optimal PEGylation sites within peptides/proteins
and to use these tools to enhance peptide/protein pharmacokinetic properties. Our central hypothesis is that
optimal PEGylation sites should be characterized by the ability of the attached PEG to enhance peptide/protein
conformational stability. Our rationale for this hypothesis is that unstable, unfolded or misfolded proteins tend to
be non-functional and have more pharmacokinetic problems than folded proteins (i.e., are more aggregation-
prone, more susceptible to proteolysis, and more readily recognized by antibodies). Therefore increases in
protein conformational stability should also enhance protein pharmacokinetic properties However, current
PEGylation efforts lack predictive tools for increasing protein stability; instead, a trial-and-error approach prevails,
which frequently results in diminished biological activity relative to the non-PEGylated protein. Using our growing
molecular-level understanding of PEG-based protein stabilization, we will develop predictive structure-based
tools for generating PEGylated peptides/proteins with enhanced pharmacokinetic properties and undiminished
function, thereby accelerating the development of better PEGylated protein drugs. We also seek to understand
and predict how location, microenvironment, and structural context affect the strength of non-covalent
interactions, including salt-bridges, cation-π interactions, and n to π* interactions, among others.

## Key facts

- **NIH application ID:** 9965611
- **Project number:** 2R15GM116055-02
- **Recipient organization:** BRIGHAM YOUNG UNIVERSITY
- **Principal Investigator:** Joshua L Price
- **Activity code:** R15 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $435,750
- **Award type:** 2
- **Project period:** 2015-09-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9965611

## Citation

> US National Institutes of Health, RePORTER application 9965611, Predictive Structure-based Guidelines for Identifying Optimal PEGylation Sites within Proteins and Understanding the Context-Dependence of Non-covalent Interaction Strength (2R15GM116055-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9965611. Licensed CC0.

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