Assembly of Biomolecular Gigastructures and Visualization with the Vulkan Graphics API

Abstract

Building and displaying all-atom models of biomolecular structures with millions or billions of atoms, like virus particles or cells, remain a challenge due to the sheer size of the data, the required levels of automated building, and the visualization limits of today's graphics hardware. Based on concepts introduced with the CellPack program, we report new algorithms to create such large-scale models using an intermediate coarse-grained "pet representation"of biomolecules with 1/10th the normal size. Pet atoms are placed such that they optimally trace the surface of the original molecule with just ∼1/50th the original atom number and are joined with covalent bonds. Molecular dynamics simulations of pet molecules allow for efficient packing optimization, as well as the generation of realistic DNA/RNA conformations. This pet world can be expanded back to the all-atom representation to be explored and visualized with full details. Essential for the efficient interactive visualization of gigastructures is the use of multiple levels of detail (LODs), where distant molecules are drawn with a heavily reduced polygon count. We present a grid-based algorithm to create such LODs for all common molecular graphics styles (including ball-and-sticks, ribbons, and cartoons) that do not require monochrome molecules to hide LOD transitions. As a practical application, we built all-atom models of SARS-CoV-2, HIV, and an entire presynaptic bouton with 1 μm diameter and 3.6 billion atoms, using modular building blocks to significantly reduce GPU memory requirements through instancing. We employ the Vulkan graphics API to maximize performance on consumer grade hardware and describe how to use the mmCIF format to efficiently store such giant models. An implementation is available as part of the YASARA molecular modeling and simulation program from www.YASARA.org. The free YASARA View program can be used to explore the presented models, which can be downloaded from www.YASARA.org/petworld, a Creative Commons platform for sharing giant biomolecular structures.