Please use this identifier to cite or link to this item: https://doi.org/10.1155/2017/4818604
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dc.titleMolecular Skin Surface-Based Transformation Visualization between Biological Macromolecules
dc.contributor.authorYan, K
dc.contributor.authorWang, B
dc.contributor.authorCheng, H
dc.contributor.authorJi, Z
dc.contributor.authorHuang, J
dc.contributor.authorGao, Z
dc.date.accessioned2020-10-26T02:59:23Z
dc.date.available2020-10-26T02:59:23Z
dc.date.issued2017
dc.identifier.citationYan, 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
dc.identifier.issn2040-2295
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/179762
dc.description.abstractMolecular 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.
dc.publisherHindawi Limited
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.subjectBinding sites
dc.subjectComputational efficiency
dc.subjectMacromolecules
dc.subjectProteins
dc.subjectBiological macromolecule
dc.subjectComputational costs
dc.subjectComputational framework
dc.subjectMacromolecular dynamics
dc.subjectMolecular skin surface
dc.subjectSmooth surface modeling
dc.subjectTraditional approaches
dc.subjectTransformation process
dc.subjectSatellites
dc.subjectArticle
dc.subjectbioinformatics
dc.subjectdynamics
dc.subjectmacromolecule
dc.subjectmolecular skin surface
dc.subjectskin surface
dc.subjectbinding site
dc.subjectchemistry
dc.subjectcomputer simulation
dc.subjectfunctions of the skin and its appendages
dc.subjecthuman
dc.subjectmacromolecule
dc.subjectmolecular model
dc.subjectprotein database
dc.subjectsurface property
dc.subjectBinding Sites
dc.subjectComputer Simulation
dc.subjectDatabases, Protein
dc.subjectHumans
dc.subjectMacromolecular Substances
dc.subjectModels, Molecular
dc.subjectSkin Physiological Phenomena
dc.subjectSurface Properties
dc.typeArticle
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.doi10.1155/2017/4818604
dc.description.sourcetitleJournal of Healthcare Engineering
dc.description.volume2017
dc.description.page4818604
dc.published.statepublished
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