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https://doi.org/10.1155/2017/4818604
Title: | Molecular Skin Surface-Based Transformation Visualization between Biological Macromolecules | Authors: | Yan, K Wang, B Cheng, H Ji, Z Huang, J Gao, Z |
Keywords: | Binding sites Computational efficiency Macromolecules Proteins Biological macromolecule Computational costs Computational framework Macromolecular dynamics Molecular skin surface Smooth surface modeling Traditional approaches Transformation process Satellites Article bioinformatics dynamics macromolecule molecular skin surface skin surface binding site chemistry computer simulation functions of the skin and its appendages human macromolecule molecular model protein database surface property Binding Sites Computer Simulation Databases, Protein Humans Macromolecular Substances Models, Molecular Skin Physiological Phenomena Surface Properties |
Issue Date: | 2017 | Publisher: | Hindawi Limited | Citation: | Yan, K, Wang, B, Cheng, H, Ji, Z, Huang, J, Gao, Z (2017). Molecular Skin Surface-Based Transformation Visualization between Biological Macromolecules. Journal of Healthcare Engineering 2017 : 4818604. ScholarBank@NUS Repository. https://doi.org/10.1155/2017/4818604 | Rights: | Attribution 4.0 International | Abstract: | Molecular skin surface (MSS), proposed by Edelsbrunner, is a C2 continuous smooth surface modeling approach of biological macromolecules. Compared to the traditional methods of molecular surface representations (e.g., the solvent exclusive surface), MSS has distinctive advantages including having no self-intersection and being decomposable and transformable. For further promoting MSS to the field of bioinformatics, transformation between different MSS representations mimicking the macromolecular dynamics is demanded. The transformation process helps biologists understand the macromolecular dynamics processes visually in the atomic level, which is important in studying the protein structures and binding sites for optimizing drug design. However, modeling the transformation between different MSSs suffers from high computational cost while the traditional approaches reconstruct every intermediate MSS from respective intermediate union of balls. In this study, we propose a novel computational framework named general MSS transformation framework (GMSSTF) between two MSSs without the assistance of union of balls. To evaluate the effectiveness of GMSSTF, we applied it on a popular public database PDB (Protein Data Bank) and compared the existing MSS algorithms with and without GMSSTF. The simulation results show that the proposed GMSSTF effectively improves the computational efficiency and is potentially useful for macromolecular dynamic simulations. © 2017 Ke Yan et al. | Source Title: | Journal of Healthcare Engineering | URI: | https://scholarbank.nus.edu.sg/handle/10635/179762 | ISSN: | 2040-2295 | DOI: | 10.1155/2017/4818604 | Rights: | Attribution 4.0 International |
Appears in Collections: | Elements Staff Publications |
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