# Project 3: Antigen design

> **NIH NIH U19** · UNIVERSITY OF WASHINGTON · 2024 · $5,122,197

## Abstract

PROJECT SUMMARY – PROJECT 3: ANTIGEN DESIGN
Project 3 focuses on developing generalizable approaches to the modeling, design, and evaluation of
native-like antigens for arenaviruses, phenuiviruses, and paramyxoviruses. Powerful machine-learning (ML)
methods enable stabilization of antigens in desired conformations and oligomeric states by structure prediction
and sequence redesign. In Aim 1, we will develop methods for accurate structure prediction of viral
glycoproteins, high-throughput ranking of constructs, and ML-based and deep mutational scanning
(DMS)-guided design of stabilized antigens. These methods will be used to develop generalizable design
strategies for phenuivirus Gn antigens with improved production yields and thermostability while preserving
antigenicity. These methods will also be used to generate design strategies for single-chain and heteromeric
antigens that stabilize native-like conformations of Gn-Gc heterodimers across Phenuiviridae. In Aim 2, we will
develop similarly generalizable ML-based and DMS-guided approaches to stabilize oligomeric arenavirus and
paramyxovirus antigens in particular conformations that elicit potent neutralizing antibodies. To design trimeric,
prefusion-stabilized arenavirus glycoprotein complex (GPC) and paramyxovirus fusion (F) proteins, we will use
sequence redesign, refine antigenic backbone, and generate de novo backbone. We will develop ML-based
sequence design and de novo backbone generation strategies that enable design of thermostable, monomeric
paramyxovirus receptor binding proteins (RBPs) and soluble, native-like tetrameric RBPs. In Aim 3, we will
use biochemical, structural, and immunological characterization of designed antigens to evaluate the accuracy
and generalizability of our design approaches and down-select to the most promising constructs. We will build
upon the Institute for Protein Design’s extensive infrastructure for protein production and characterization,
using measurements of yield, thermostability, and antigenicity to map the strengths and limitations of different
computational design approaches and refine design strategies. Serological and structural characterization of
sera from immunized mice at the UW, Fred Hutchinson Cancer Center, and UTMB will identify constructs that
elicit potent neutralizing antibody responses. To rigorously evaluate these constructs and distinguish lead
candidates, we will leverage small animal challenge models being developed by UTMB to identify constructs
that confer effective protection.

## Key facts

- **NIH application ID:** 10861413
- **Project number:** 1U19AI181881-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Neil King
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $5,122,197
- **Award type:** 1
- **Project period:** 2024-08-12 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10861413

## Citation

> US National Institutes of Health, RePORTER application 10861413, Project 3: Antigen design (1U19AI181881-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10861413. Licensed CC0.

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