# Antiviral targeting to suppress drug resistance

> **NIH NIH U19** · SLOAN-KETTERING INST CAN RESEARCH · 2022 · $2,132,587

## Abstract

The last decades have emphasized the pandemic potential of the flaviviruses, picornaviruses and coronaviruses.
Traditional drug discovery approaches for antiviral agents have generally focused on direct-acting inhibitors of
viral targets, usually enzymes, that disrupt function and thus inhibit viral growth. However, the effectiveness of
loss-of-function antivirals can be rapidly overcome by the outgrowth of drug-resistant variants. Multi-drug therapy
is an effective solution to this problem that has been employed for HIV and hepatitis C viruses. Unfortunately,
multi-drug therapy remains an expensive, long-term approach ill-suited to rapid response to new pandemic
viruses and use in impoverished settings. To address this challenge in antiviral drug development, Project 1 will
use a combination of genetic strategies and deep mutational analysis to identify specific viral proteins and small
molecule targeting strategies with the aim of suppressing the selection of drug-resistant viral variants. We will
focus on identifying proteins that have the potential, when bound to inhibitors, to be 'dominant disruptors' of viral
RNA replication or virion function by producing or acting as 'molecular poisons' towards all developing viruses
inside an infected cell. In this scenario, the drug-susceptible parent viruses can act as dominant killers of drugresistant
variants, thus blocking the propagation of resistance. Our data have identified both viral proteases and
capsid protein targets as having potential to induce dominant-disruptor phenotypes upon binding smallmolecules
drugs. In addition, deep mutational scanning and biochemical methods will enable us to identify
specific small-molecule binding sites on diverse viral targets that further avoid resistance by targeting locations
at which mutations are not tolerated due to fitness cost. The combination of these approaches will yield both
genetically validated viral targets, and particular regions of viral targets, that can suppress the formation of drug
resistance as well as approaches for small-molecule targeting that are unlikely to allow the selection for
resistance through classical mutational variation. These targets can then enter the consortium pipeline for rapid
progression to screening, hit-to-lead development and validation in animal models of infection.

## Key facts

- **NIH application ID:** 10513871
- **Project number:** 1U19AI171399-01
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** John Damon Chodera
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,132,587
- **Award type:** 1
- **Project period:** 2022-05-16 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10513871

## Citation

> US National Institutes of Health, RePORTER application 10513871, Antiviral targeting to suppress drug resistance (1U19AI171399-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10513871. Licensed CC0.

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