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An algebraic spline model of molecular surfaces for energetic computations
Wenqi Zhao1, Guoliang Xu, Chandrajit Bajaj
1Center for Computational Visualization, Institute of Computational Engineering and Sciences, University of Texas at Austin, 201 East 24th Street, C0200, Austin, Texas 78712, USA. wzhao@ices.utexas.edu
None:
In this paper, we describe a new method to generate a smooth algebraic spline (AS) approximation of the molecular surface (MS) based on an initial coarse triangulation derived from the atomic coordinate information of the biomolecule, resident in the Protein data bank (PDB). Our method first constructs a triangular prism scaffold covering the PDB structure, and then generates a piecewise polynomial F on the Bernstein-Bezier (BB) basis within the scaffold. An ASMS model of the molecular surface is extracted as the zero contours of F, which is nearly C1 and has dual implicit and parametric representations. The dual representations allow us easily do the point sampling on the ASMS model and apply it to the accurate estimation of the integrals involved in the electrostatic solvation energy computations. Meanwhile comparing with the trivial piecewise linear surface model, fewer number of sampling points are needed for the ASMS, which effectively reduces the complexity of the energy estimation.
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