Detection of gas bubbles and local voids in molecular simulations using burbuja
Year: 2026
Type: article
Abstract: We present burbuja (Baring Unseen Regions of Bubbles Using Joint-Density Analysis), an automated software tool for detecting and characterizing gas bubbles and other local voids in molecular structures and trajectories containing explicit aqueous solvent. We describe the burbuja algorithm and demonstrate its accuracy and utility across a range of example systems, including globular proteins, a membrane system, a coarse-grained membrane trajectory with 25,000 frames, a large envelope capsid containing approximately 150 million atoms, and a very large respiratory aerosol system containing approximately 1 billion atoms. Burbuja supports optional GPU acceleration and can be run as a standalone command-line utility or through a Python-based API, facilitating integration with existing community tools for molecular system preparation and analysis. Burbuja is open-source and freely available at https://github.com/Abrahammc90/Burbuja.git.
Source: Protein Science
DOI: 10.1002/pro.70562
Institution: University of California San Diego
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,480
OpenAlex ID: W7155166749