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Rendering protein structures inside cells at the atomic level with
Unreal Engine

View ORCID ProfileMuyuan Chen
doi: https://doi.org/10.1101/2023.12.08.570879
Muyuan Chen
1Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator
Laboratory, Stanford University, Menlo Park, CA 94025, USA

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  * ORCID record for Muyuan Chen
  * For correspondence: muyuanc@stanford.edu

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Abstract

While the recent development of cryogenic electron tomography
(CryoET) makes it possible to identify various macromolecules inside
cells and determine their structure at near-atomic resolution, it
remains challenging to visualize the complex cellular environment at
the atomic level. One of the main hurdles in cell visualization is to
render the millions of molecules in real time computationally. Here,
using a video game engine, we demonstrate the capability of rendering
massive biological macromolecules at the atomic level within their
native environment. To facilitate the visualization, we also provide
tools that help the interactive navigation inside the cells, as well
as software that converts protein structures identified using CryoET
to a scene that can be explored with the game engine.

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Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has
granted bioRxiv a license to display the preprint in perpetuity. It
is made available under a CC-BY 4.0 International license.

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Posted December 11, 2023.
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Rendering protein structures inside cells at the atomic level with
Unreal Engine
Muyuan Chen
bioRxiv 2023.12.08.570879; doi: https://doi.org/10.1101/
2023.12.08.570879
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Rendering protein structures inside cells at the atomic level with
Unreal Engine
Muyuan Chen
bioRxiv 2023.12.08.570879; doi: https://doi.org/10.1101/
2023.12.08.570879

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