Multi-resolution Approaches to Modeling the 3D Structure, Delivery, and Replication of Viral Genomes

NIH RePORTER · NIH · R01 · $284,570 · view on reporter.nih.gov ↗

Abstract

This project will develop computational approaches for quantitative studies of viral infection. At the core of these approaches is a multi-resolution description of nucleic acids and proteins that permits mixed-resolution simulations of very large biomolecular systems, accurate resolution switching from coarse to fine and vice versa, including a fully atomistic representation, and an explicit mechanism to account for biochemical transformations. Building on a recent multi-resolution model of DNA, the project will develop a computational method for determining the physical organization of viral genomes inside pressurized and self-assembled viral capsids. The method will be applied to resolve the structure of several packaged genomes at a resolution suitable for drug development applications. In parallel, a multi-resolution model of bacterial and eukaryotic cytoplasm will be developed to account for specific and nonspecific interactions of the cytoplasmic proteins with double-stranded DNA. The model will be applied to determine the spatial organization of double-stranded genomes ejected into cytoplasm and to evaluate the effect of the cytoplasm-like environment on the ejection process. The multi- resolution simulation framework will elucidate the microscopic factors governing genome ejection and the transport of an intact viral particle through a nuclear pore complex. Finally, the project will develop the first physical model of a viral genome replication, accounting for essential biochemical transformations and the effect of external forces on the reaction rates. The replication model will be used to determine how competition between DNA binding proteins of the host cell affect viral genome replication fidelity. The multi-resolution simulation methods developed through this program will be implemented in a GPU-accelerated code Atomic Resolution Brownian Dynamics. The methods and the code, along with all required documentation, examples and tutorials, will be made freely available to the research community to study a wide range of biophysical processes.

Key facts

NIH application ID
9946794
Project number
1R01GM137015-01
Recipient
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
Principal Investigator
Aleksei Aksimentiev
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$284,570
Award type
1
Project period
2020-07-01 → 2024-05-31