DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Dong-Sup | - |
dc.contributor.advisor | 김동섭 | - |
dc.contributor.author | Kang, Hyo-A | - |
dc.contributor.author | 강효아 | - |
dc.date.accessioned | 2011-12-12T07:29:37Z | - |
dc.date.available | 2011-12-12T07:29:37Z | - |
dc.date.issued | 2010 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=455154&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/27197 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2010.08, [ iv, 31 p. ] | - |
dc.description.abstract | Protein tyrosine nitration is a covalent protein modification that occurs during oxidative stress, development, and biological aging. Recent research findings about protein tyrosine nitration have proposed that this modification is related to various pathogenesis such as Alzheimer’s disease, Parkinson’s disease, inflammatory disease, and age related disorder. Although these proposes shows the importance of protein tyrosine nitration, little is known about protein tyrosine nitration sequence pattern and structural characteristics. In this research we analyzed protein tyrosine nitration sequences and structures statistically. The number of protein tyrosine nitration examples is 669. These examples were generated from various samples such as Non-Small Cell Lung Cancer (NSCLC), mitochondria with type II diabetes, liver cancer cell line, Huh7, and ischemic rat brain by a novel proteomics method. We performed sequence analysis, secondary structure prediction, and geometric pattern analysis of predicted tertiary structures. From these studies we could get considerable findings. Around protein tyrosine nitration site, amino acids that have hydrophobic side chains exist more frequently. In previous researches, it seemed that negative charged residues were enriched and sulfur contain residues were depleted. However, in this research, the results showed that positive charged residues and sulfur contain residues are more preferred. We could not find position specific motif, but, we could find that there are some specific sequence order: H-[R|C|H]-H-[TDFY]-Y (H means hydrophobic residues). From clique graph searching process, we suggests that structures of GI 10945258913‘s 218 residue, GI 109466561‘s 516 residue, and GI 109240538‘s 109 residue could be geometric templates. | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | PTN sequence | - |
dc.subject | PTN structure | - |
dc.subject | PTN selectivity | - |
dc.subject | Protein Tyrosine Nitration | - |
dc.subject | PTN motif | - |
dc.subject | PTN 모티프 | - |
dc.subject | PTN 시퀀스 | - |
dc.subject | PTN 구조 | - |
dc.subject | PTN 선택성 | - |
dc.subject | 단백질 타이로신 나이트로화 | - |
dc.title | Protein tyrosine nitration properties analysis and prediction based on peptide sequences and predicted structures | - |
dc.title.alternative | 펩타이드 서열과 예측 구조를 이용한 단백질 타이로신 나이트로화 특성 분석과 예측 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 455154/325007 | - |
dc.description.department | 한국과학기술원 : 바이오및뇌공학과, | - |
dc.identifier.uid | 020083993 | - |
dc.contributor.localauthor | Kim, Dong-Sup | - |
dc.contributor.localauthor | 김동섭 | - |
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