# In silico modeling of subcellular infection by diverse families of RNA virus

> **NIH NIH R01** · UNIVERSITY OF VIRGINIA · 2024 · $563,593

## Abstract

PROJECT SUMMARY/ABSTRACT
RNA viruses are the leading source of existing and emerging pathogens. Many species overtake host cells
with just a dozen or so viral components, making subcellular infections tractable for mathematical modeling
and analysis. Such models have the potential to identify fragilities in a viral life cycle, examine differences in
susceptibility among humans, and serve as templates for reconfiguration in response to novel outbreaks.
However, it has not been clear how to build such models in a scalable way, and thus fewer than ten have been
developed among the several hundred RNA viruses that infect humans. A new modeling strategy was recently
proposed, which starts with a common mass-action topology that is then customized to different virus families
by parameter inference. The generic approach lumps together biochemical processes that are specific to
different virus families, and it is unclear whether these distinctions are needed to create models that are
broadly predictive. The objective of this application is to evaluate the relative merits of generic and familyspecific
approaches for modeling subcellular infection by RNA viruses. We focus on coxsackievirus B3 and
dengue virus as two species of RNA virus from different families (Picornaviridae and Flaviviridae) for which
generic and family-specific models are available or immediately feasible. The overarching hypothesis is that
RNA viruses are similarly organized around modules for entry, replication, and other core processes, but the
modules fundamentally differ by virus family. The specific aims are to: 1) Compare lumped viral entry to
family-specific modules; 2) Refactor the viral replication module; and 3) Add antiviral conduits between
modules. Our approach leverages deep transcriptome profiles from several thousand single cells and several
hundred relevant human organs; it also invokes a new abstraction (the phase-field crystal model) for a key
intermediate of RNA viruses. Computational and experimental tests will be performed using temperature as a
system-wide perturbation of biochemical rate parameters at surface (33°C), body (37°C), and febrile (40°C)
temperatures. This multi-pronged assessment across different modules will clarify a best-available path
toward building foundational models for all major families of RNA viruses that infect humans.

## Key facts

- **NIH application ID:** 10993807
- **Project number:** 1R01AI186222-01
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Kevin A Janes
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $563,593
- **Award type:** 1
- **Project period:** 2024-05-28 → 2029-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10993807

## Citation

> US National Institutes of Health, RePORTER application 10993807, In silico modeling of subcellular infection by diverse families of RNA virus (1R01AI186222-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10993807. Licensed CC0.

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