FIBOS: R and Python packages for analyzing protein packing and structure
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Summary
Advances in prediction of the 3D structures of most known proteins through machine learning methods have achieved unprecedented accuracies. However, although these computed structure models (CSMs) are overall remarkably good, they still challenge accuracy at the atomic level, especially in refinement of interatomic packing. The Occluded Surface (OS) algorithm is widely used for atomic packing analysis. But it lacks implementations in high-level languages like R and Python, limiting its accessibility. We introduce FIBOS, an R and Python package incorporating the OS methodology with enhancements. It embeds efficient Fortran code from the original OS. It also improves the original algorithm by using Fibonacci spirals to distribute surface dots, reducing anisotropy and ensuring a more even point distribution. As a case study using FIBOS, we compared packing densities between experimental protein structures and AlphaFold predictions. While average packing densities are similar, AlphaFold models exhibit comparatively greater variability and less homogeneity, potentially reflecting local inaccuracies. The FIBOS package provides an accessible tool for protein packing density analysis in R and Python, facilitating structural assessment in the era of extensive computational protein models.
Availability and implementation
The R and Python packages code are available at https://github.com/insilico-unifei/fibos-R and https://github.com/insilico-unifei/fibos-py .
