# Designing neutralization antibodies against Sars-Cov-2

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $433,750

## Abstract

Project Summary
COVID-19 has become a worldwide pandemic whose rapid spread and mortality rate threatens millions of lives
and the global economic system. Developing effective treatment such as neutralization antibodies is an urgent
need. We propose here to develop a new method to design antibodies strongly bind to the SARS-CoV-2
receptor binding domain (RBD) that is necessary for viral entrance to human cells. We will develop a novel
approach that combines directed evolution, deep sequencing and interpretable neural network models to
efficiently identify strong and specific antibodies. This method will allow analyzing large sequencing data sets
of antibody variants against the SARS-CoV-2 RBD in order to derive superior binders that do not exist in the
original library. Iteration through directed evolution and computational design will efficiently identify
neutralization antibody candidates that can be used as potent therapeutics to treat COVID-19.

## Key facts

- **NIH application ID:** 10173204
- **Project number:** 1R21AI158114-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Wei Wang
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $433,750
- **Award type:** 1
- **Project period:** 2020-07-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10173204

## Citation

> US National Institutes of Health, RePORTER application 10173204, Designing neutralization antibodies against Sars-Cov-2 (1R21AI158114-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10173204. Licensed CC0.

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