Abstract
Voids and pockets in a protein, collectively called as cavities, refer to empty spaces that are enclosed by the protein molecule. Existing methods to compute, measure, and visualize the cavities in a protein molecule are sensitive to inaccuracies in the empirically determined atomic radii. This paper presents a topological framework that enables robust computation and visualization of these structures. Given a fixed set of atoms, cavities are represented as subsets of the weighted Delaunay triangulation of atom centres. A novel notion of \((\varepsilon,\pi )\)-stable cavities helps identify cavities that are stable even after perturbing the atom radii by a small value. An efficient method is described to compute these stable cavities for a given input pair of values \((\varepsilon,\pi )\). This approach is used to identify potential pockets and channels in protein structures.
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Notes
- 1.
A preliminary version of this work appeared as a short paper in the Proceedings of Eurographics Conference on Visualization [30].
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Acknowledgements
Talha Bin Masood was supported by Microsoft Corporation and Microsoft Research India under the Microsoft Research India PhD Fellowship Award. This work was supported in part by the Department of Science and Technology, India, under Grant SR/S3/EECE/0086/2012, the DST Center for Mathematical Biology, IISc, under Grant SR/S4/MS:799/12, the NYU School of Engineering, and NSF award CNS-1229185. We would like to thank Patrice Koehl for his suggestions and for sharing the source code of Proshape.
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Sridharamurthy, R., Masood, T.B., Doraiswamy, H., Patel, S., Varadarajan, R., Natarajan, V. (2016). Extraction of Robust Voids and Pockets in Proteins. In: Linsen, L., Hamann, B., Hege, HC. (eds) Visualization in Medicine and Life Sciences III. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-24523-2_15
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