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Parallel Computation of Alpha Complexes for Biomolecules

Authors Talha Bin Masood , Tathagata Ray, Vijay Natarajan

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Author Details

Talha Bin Masood
  • Scientific Visualization Group, Linköping University, Norrköping, Sweden
Tathagata Ray
  • BITS Pilani, Hyderabad Campus, Hyderabad, India
Vijay Natarajan
  • Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India

Funding

  • Natarajan, Vijay: This work is partially supported by a Swarnajayanti Fellowship from the Department of Science and Technology, India (DST/SJF/ETA-02/2015-16); a Mindtree Chair research grant; and the Robert Bosch Centre for Cyber Physical Systems, IISc.

Acknowledgements

Part of this work was done when the first author was at Indian Institute of Science, Bangalore. The authors would like to thank Sathish Vadhiyar and Nikhil Ranjanikar for helpful discussions and suggestions during the early phase of this work.

Cite AsGet BibTex

Talha Bin Masood, Tathagata Ray, and Vijay Natarajan. Parallel Computation of Alpha Complexes for Biomolecules. In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 17:1-17:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.SoCG.2020.17

Abstract

The alpha complex, a subset of the Delaunay triangulation, has been extensively used as the underlying representation for biomolecular structures. We propose a GPU-based parallel algorithm for the computation of the alpha complex, which exploits the knowledge of typical spatial distribution and sizes of atoms in a biomolecule. Unlike existing methods, this algorithm does not require prior construction of the Delaunay triangulation. The algorithm computes the alpha complex in two stages. The first stage proceeds in a bottom-up fashion and computes a superset of the edges, triangles, and tetrahedra belonging to the alpha complex. The false positives from this estimation stage are removed in a subsequent pruning stage to obtain the correct alpha complex. Computational experiments on several biomolecules demonstrate the superior performance of the algorithm, up to a factor of 50 when compared to existing methods that are optimized for biomolecules.

Subject Classification

ACM Subject Classification
  • Theory of computation → Parallel algorithms
  • Computing methodologies → Shape modeling
  • Applied computing → Molecular structural biology
Keywords
  • Delaunay triangulation
  • parallel algorithms
  • biomolecules
  • GPU

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