# Structure-Based Design of Peptide Entry Inhibitors against Ebola Virus Infection

> **NIH NIH R21** · UNIVERSITY OF NEBRASKA LINCOLN · 2022 · $209,109

## Abstract

Abstract
Ebola viruses (EBOV) along with Marburg viruses (MARV) belong to the Filoviridae family which
infects humans and nonhuman primates and causes outbreaks with a high mortality up to 90%.
We do not have approved drugs for treating this deadly viral disease and therefore it is urgent to
develop therapeutics to cope with the dangerous outbreaks. In this project, we propose to develop
peptide based inhibitors targeting the receptor binding site (RBS) to block viral infection. We will
conduct structure based design using the available co-crystal structures of the NPC1 receptor or
monoclonal antibodies bound to the viral glycoprotein. The initial evaluation will utilize pseudo-
typed viruses to test viral entry in a cell based assay. The best peptide candidates from these
assays will subsequently be tested in a BSL-4 containment facility using replication competent
viruses for entry inhibition tests. In vivo evaluations of qualified candidates will be conducted in a
virus challenge mouse model to measure protection efficacy. After all these evaluations,
promising candidates could be advanced to nonhuman primates or human clinical trials.

## Key facts

- **NIH application ID:** 10322758
- **Project number:** 5R21AI151483-02
- **Recipient organization:** UNIVERSITY OF NEBRASKA LINCOLN
- **Principal Investigator:** Shi-hua Xiang
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $209,109
- **Award type:** 5
- **Project period:** 2021-01-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10322758

## Citation

> US National Institutes of Health, RePORTER application 10322758, Structure-Based Design of Peptide Entry Inhibitors against Ebola Virus Infection (5R21AI151483-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10322758. Licensed CC0.

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