Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김덕수 | - |
dc.date.accessioned | 2018-03-22T07:05:13Z | - |
dc.date.available | 2018-03-22T07:05:13Z | - |
dc.date.issued | 2013-09 | - |
dc.identifier.citation | Journal of global optimization, 2013, 57(1), p.217-250 | en_US |
dc.identifier.issn | 0925-5001 | - |
dc.identifier.uri | https://link.springer.com/article/10.1007%2Fs10898-012-9886-3 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/50661 | - |
dc.description.abstract | A molecular structure determines a molecular function(s) and a correct understanding of molecular structure is important for biotechnology. The computational prediction of molecular structure is a frequent requirement for important biomolecular applications such as a homology modeling, a docking simulation, a protein design, etc. where the optimization of molecular structure is fundamental. One of the core problems in the optimization of protein structure is the optimization of side-chains called the side-chain positioning problem. The side-chain positioning problem, assuming the rigidity of backbone and a rotamer library, attempts to optimally assign a rotamer to each residue so that the potential energy of protein is minimized in its entirety. The optimal solution approach using (mixed) integer linear programming, with the dead-end elimination technique, suffers even for moderate-sized proteins because the side-chain positioning problem is NP-hard. On the other hand, popular heuristic approaches focusing on speed produce solutions of low quality. This paper presents an efficient algorithm, called the BetaSCP, for the side-chain positioning problem based on the beta-complex which is a derivative geometric construct of the Voronoi diagram. Placing a higher priority on solution quality, the BetaSCP algorithm produces a solution very close to the optima within a reasonable computation time. The effectiveness and efficiency of the BetaSCP are experimentally shown via a benchmark test against well-known algorithms using twenty test models selected from Protein Data Bank. | en_US |
dc.description.sponsorship | This research was sponsored by the National Research Lab grant funded by the National Research Foundation (NRF) of Korea (No. 2011-0020410). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Science + Business Media | en_US |
dc.subject | Protein structure optimization | en_US |
dc.subject | Protein design | en_US |
dc.subject | Rotamer | en_US |
dc.subject | Voronoi diagram | en_US |
dc.subject | Quasi-triangulation | en_US |
dc.subject | Beta-complex | en_US |
dc.subject | Integer linear programming | en_US |
dc.subject | Optimal | en_US |
dc.subject | Heuristic | en_US |
dc.subject | BetaSCP | en_US |
dc.subject | SCWRL | en_US |
dc.subject | RASP | en_US |
dc.title | Protein structure optimization by side-chain positioning via beta-complex | en_US |
dc.type | Article | en_US |
dc.relation.volume | 57 | - |
dc.identifier.doi | 10.1007/s10898-012-9886-3 | - |
dc.relation.page | 217-250 | - |
dc.relation.journal | JOURNAL OF GLOBAL OPTIMIZATION | - |
dc.contributor.googleauthor | Ryu, Joong-hyun | - |
dc.contributor.googleauthor | Kim, Deok-Soo | - |
dc.relation.code | 2013010715 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DIVISION OF MECHANICAL ENGINEERING | - |
dc.identifier.pid | dskim | - |
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