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Related Experiment Video

Updated: Jun 3, 2026

Structure of HIV-1 Capsid Assemblies by Cryo-electron Microscopy and Iterative Helical Real-space Reconstruction

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Published on: August 9, 2011

Modelling the self-assembly of virus capsids.

Iain G Johnston¹, Ard A Louis, Jonathan P K Doye

¹Rudolf Peierls Centre for Theoretical Physics, 1 Keble Road, Oxford OX1 3NP, UK.

Journal of Physics. Condensed Matter : an Institute of Physics Journal

|March 11, 2011

Summary

Computer simulations reveal how virus capsid self-assembly depends on energy landscapes and crowding. The model captures experimental features like hysteresis and kinetic traps, offering insights into viral structure formation.

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Simple and Robust in vivo and in vitro Approach for Studying Virus Assembly

Simple and Robust in vivo and in vitro Approach for Studying Virus Assembly

Published on: March 1, 2012

Area of Science:

Computational biophysics
Virology
Statistical mechanics

Background:

Virus capsid self-assembly is a complex process crucial for viral replication.
Understanding the factors governing efficient and reversible capsid formation is essential.
Previous models often lack the complexity to capture experimentally observed phenomena.

Purpose of the Study:

To investigate the self-assembly of simple icosahedral virus capsid structures using computer simulations.
To explore the relationship between potential energy landscapes and assembly efficiency.
To examine the impact of macromolecular crowding on capsid formation dynamics.

Main Methods:

Utilizing a coarse-grained computer simulation model based on Wales (2005).
Analyzing thermodynamic and geometric factors influencing assembly.
Studying the effects of macromolecular crowding agents.
Generalizing the model to higher triangulation numbers (T=3).

Main Results:

The model reproduces experimentally observed features such as sigmoidal assembly dynamics, hysteresis, and kinetic traps.
Crowding agents can decrease yields under optimal conditions but increase them away from the optimum.
Assembly dynamics become more complex with increased model complexity (T=3).

Conclusions:

Potential energy landscape structure is key to understanding virus capsid self-assembly efficiency.
Macromolecular crowding has a nuanced effect on capsid yields, dependent on parameter regimes.
The coarse-grained model provides valuable insights into the fundamental principles of viral self-assembly.