DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cheon M. | ko |
dc.contributor.author | Heo M. | ko |
dc.contributor.author | Moon E.-J. | ko |
dc.contributor.author | Kim S. | ko |
dc.contributor.author | Chung K. | ko |
dc.contributor.author | Chang I. | ko |
dc.contributor.author | Kim H. | ko |
dc.date.accessioned | 2013-03-03T19:44:30Z | - |
dc.date.available | 2013-03-03T19:44:30Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2004 | - |
dc.identifier.citation | JOURNAL OF THE KOREAN PHYSICAL SOCIETY, v.45, no.2, pp.550 - 557 | - |
dc.identifier.issn | 0374-4884 | - |
dc.identifier.uri | http://hdl.handle.net/10203/80176 | - |
dc.description.abstract | The design and construction of a global protein energy function which can recognize the native folds of all representative proteins of different classes with a low sequence homology has been one of the important issues and a formidable task in protein science. We used perceptron learning and protein threading to construct a one-body score function of proteins, which could recognize simultaneously the native folds of 1,006 training proteins covering all available representative proteins in a sequence homology with less than 30 % between them. When the score parameters for the 1,006 training proteins were subject to a threading test, 370 (96.9 %) native folds of the 382 new distinct proteins were recognized compared to the previous score parameters obtained using 387 training-proteins, which recognized 190 (89.2 %) native folds of the 213 new proteins. We performed an analysis of the score parameters by using a singular value decomposition and a self-organizing map to elucidate the biological clustering characters of 20 amino acids. The self-organizing map analysis of the new score-parameters revealed better biological clustering of 20 amino acids, which agreed with their known properties. The same analysis for the previous score-parameters could not provide such a result because the 387 training proteins employed before did not fully cover all representative proteins of different classes of a sequence homology with less than 30 % between them. We illuminated the marked difference in the new score-parameters that relative to previous score-parameters, not only performed better in recognizing the native folds of new distinct proteins but also captured better the biological clustering characters of amino acids. | - |
dc.language | English | - |
dc.publisher | KOREAN PHYSICAL SOC | - |
dc.subject | TERTIARY STRUCTURE RECOGNITION | - |
dc.subject | AMINO-ACID-SEQUENCES | - |
dc.subject | 3-DIMENSIONAL STRUCTURE | - |
dc.subject | CONTACT ENERGIES | - |
dc.subject | FOLD RECOGNITION | - |
dc.subject | HAMILTONIANS | - |
dc.subject | POTENTIALS | - |
dc.subject | PROFILES | - |
dc.subject | PACKING | - |
dc.subject | DESIGN | - |
dc.title | Environment-dependent one-body score function for proteins by perceptron learning and protein threading | - |
dc.type | Article | - |
dc.identifier.wosid | 000223321200052 | - |
dc.identifier.scopusid | 2-s2.0-4544341857 | - |
dc.type.rims | ART | - |
dc.citation.volume | 45 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 550 | - |
dc.citation.endingpage | 557 | - |
dc.citation.publicationname | JOURNAL OF THE KOREAN PHYSICAL SOCIETY | - |
dc.contributor.localauthor | Kim H. | - |
dc.contributor.nonIdAuthor | Cheon M. | - |
dc.contributor.nonIdAuthor | Heo M. | - |
dc.contributor.nonIdAuthor | Moon E.-J. | - |
dc.contributor.nonIdAuthor | Kim S. | - |
dc.contributor.nonIdAuthor | Chung K. | - |
dc.contributor.nonIdAuthor | Chang I. | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | protein fold recognition | - |
dc.subject.keywordAuthor | protein score function | - |
dc.subject.keywordAuthor | perceptron learning | - |
dc.subject.keywordAuthor | protein threading | - |
dc.subject.keywordAuthor | self-organizing map | - |
dc.subject.keywordPlus | TERTIARY STRUCTURE RECOGNITION | - |
dc.subject.keywordPlus | AMINO-ACID-SEQUENCES | - |
dc.subject.keywordPlus | 3-DIMENSIONAL STRUCTURE | - |
dc.subject.keywordPlus | CONTACT ENERGIES | - |
dc.subject.keywordPlus | FOLD RECOGNITION | - |
dc.subject.keywordPlus | HAMILTONIANS | - |
dc.subject.keywordPlus | POTENTIALS | - |
dc.subject.keywordPlus | PROFILES | - |
dc.subject.keywordPlus | PACKING | - |
dc.subject.keywordPlus | DESIGN | - |
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