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Volume 6, Issue 4
Model the Solvent-Excluded Surface of 3D Protein Molecular Structures Using Geometric PDE-Based Level-Set Method

Qing Pan & Xue-Cheng Tai

Commun. Comput. Phys., 6 (2009), pp. 777-792.

Published online: 2009-06

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  • Abstract

This paper presents an approach to model the solvent-excluded surface (SES) of 3D protein molecular structures using the geometric PDE-based level-set method. The level-set method embeds the shape of 3D molecular objects as an isosurface or level set corresponding to some isovalue of a scattered dense scalar field, which is saved as a discretely-sampled, rectilinear grid, i.e., a volumetric grid. Our level-set model is described as a class of tri-cubic tensor product B-spline implicit surface with control point values that are the signed distance function. The geometric PDE is evolved in the discrete volume. The geometric PDE we use is the mean curvature specified flow, which coincides with the definition of the SES and is geometrically intrinsic. The technique of speeding up is achieved by use of the narrow band strategy incorporated with a good initial approximate construction for the SES. We get a very desirable approximate surface for the SES.

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@Article{CiCP-6-777, author = {Qing Pan and Xue-Cheng Tai}, title = {Model the Solvent-Excluded Surface of 3D Protein Molecular Structures Using Geometric PDE-Based Level-Set Method}, journal = {Communications in Computational Physics}, year = {2009}, volume = {6}, number = {4}, pages = {777--792}, abstract = {

This paper presents an approach to model the solvent-excluded surface (SES) of 3D protein molecular structures using the geometric PDE-based level-set method. The level-set method embeds the shape of 3D molecular objects as an isosurface or level set corresponding to some isovalue of a scattered dense scalar field, which is saved as a discretely-sampled, rectilinear grid, i.e., a volumetric grid. Our level-set model is described as a class of tri-cubic tensor product B-spline implicit surface with control point values that are the signed distance function. The geometric PDE is evolved in the discrete volume. The geometric PDE we use is the mean curvature specified flow, which coincides with the definition of the SES and is geometrically intrinsic. The technique of speeding up is achieved by use of the narrow band strategy incorporated with a good initial approximate construction for the SES. We get a very desirable approximate surface for the SES.

}, issn = {1991-7120}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/cicp/7705.html} }
TY - JOUR T1 - Model the Solvent-Excluded Surface of 3D Protein Molecular Structures Using Geometric PDE-Based Level-Set Method AU - Qing Pan & Xue-Cheng Tai JO - Communications in Computational Physics VL - 4 SP - 777 EP - 792 PY - 2009 DA - 2009/06 SN - 6 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/cicp/7705.html KW - AB -

This paper presents an approach to model the solvent-excluded surface (SES) of 3D protein molecular structures using the geometric PDE-based level-set method. The level-set method embeds the shape of 3D molecular objects as an isosurface or level set corresponding to some isovalue of a scattered dense scalar field, which is saved as a discretely-sampled, rectilinear grid, i.e., a volumetric grid. Our level-set model is described as a class of tri-cubic tensor product B-spline implicit surface with control point values that are the signed distance function. The geometric PDE is evolved in the discrete volume. The geometric PDE we use is the mean curvature specified flow, which coincides with the definition of the SES and is geometrically intrinsic. The technique of speeding up is achieved by use of the narrow band strategy incorporated with a good initial approximate construction for the SES. We get a very desirable approximate surface for the SES.

Qing Pan and Xue-Cheng Tai. (2009). Model the Solvent-Excluded Surface of 3D Protein Molecular Structures Using Geometric PDE-Based Level-Set Method. Communications in Computational Physics. 6 (4). 777-792. doi:
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