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1 2009 Masaaki Kotera
2 2
3 I II / A () B1 () B2 B12 C () D A D
4
5
6
7 () () () () DNA 5-
8 KEGG PATHWAY Database
9 Xenobiotics biodegradation
10
11 KEGG PATHWAY Database
12 Human Diseases
13 Type I diabetes
14 H00069
15 New Page
16
17 P450 O-, N-, S- UDP- N - -S- N-
18 KEGG PATHWAY Database
19 Xenobiotics biodegradation
20 Drug metabolism
21
22 KEGG PATHWAY Database
23 Secondary metabolites
24
25
26 (small world)
27 EC
28 Jeong et al. Jeong et al., The large-scale organization of metabolic networks, Nature 407, (2000).
29 Arita Arita, The metabolic world of Escherichia coli is not small, Proc Natl Acad Sci U S A. 101(6): (2004).
30 Arita Arita, The metabolic world of Escherichia coli is not small, Proc Natl Acad Sci U S A. 101(6): (2004).
31 Reactant pairs (RPAIRs) AH 2 + B = A + BH 2 AH 2 A AB + C = A + BC AB A B BH 2 C BC AB + H 2 O = AH + BOH AB AH AB = A + B AB A H 2 O BOH B Kotera et al., Computational assignment of the EC numbers for genomic-scale analysis of enzymatic reactions J. Am. Chem. Soc. 126, (2004).
32 Atom alignment of the molecular graphs O6a O6a O6a O6a C6a C6a C5a O5a O5a C5a C1b C1a C1c O1a C1a Hattori et al., Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways J. Am. Chem. Soc. 125, (2003).
33 RPAIR database 5,669 5,327 -
34 Faust et al Faust et al., Metabolic pathfinding using RPAIR annotation J Mol Biol. 388(2): (2009).
35
36
37
38
39
40 Moriya et al Moriya et al., KAAS: an automatic genome annotation and pathway reconstruction server, Nucleic Acids Research 35, W182-W185 (2007).
41 Yamanishi et al Yamanishi et al., Prediction of missing enzyme genes in a bacterial metabolic network, FEBS Journal, 274 (9), (2007).
42
43 Yamanishi et al Yamanishi et al., Prediction of missing enzyme genes in a bacterial metabolic network, FEBS Journal, 274 (9), (2007).
44
45 RDM Atom alignment of the molecular graphs O6a C6a O6a O6a O6a C6a Matched subgraph C5a O5a O5a C5a R D M C1b C1c C5a C1a * C1c C5a C1b C1c C1a Reaction center O1a Differences C1a Kotera et al., Computational assignment of the EC numbers for genomic-scale analysis of enzymatic reactions J. Am. Chem. Soc, 126, (2004).
46 E-zyme chemical annotation RPAIR database RDM RDM R D M C1b C1c C5a C1a * C1c C5a! Yamanishi et al., E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs Bioinformatics, 25(12) i179-i186 (2009).
47
48 Oh et al Oh et al., Systematic Analysis of Enzyme- Catalyzed Reaction Patterns and Prediction of Microbial Biodegradation Pathways, J Chem Inf Model 47, (2007).
49 Fenner et al Fenner et al. Data-driven extraction of relative reasoning rules to limit combinatorial explosion in biodegradation pathway prediction, Bioinformatics 24 (18): (2008).
50 Kotera et al Kotera et al., Eliciting possible reaction equations and metabolic pathways involving orphan metabolites, J Chem Inf Model. 48(12): (2008).
51 G E R #1 G E R #2 Genome annotation G E R G E R Chemical annotation
52 EC EC EC EC
53 1. oxidoreductases 2. transferases 3. hydrolases 4. lyases 5. Isomerases 6. ligases EC Class Subclass Sub-subclass Complete EC number : : : : : : zeatin reductase : :
54 EC EC EC EC RS EZ 6.
55 EC Kotera et al., Computational assignment of the EC numbers for genomic-scale analysis of enzymatic reactions J. Am. Chem. Soc, 126, (2004).
56 Thioesterase domain of polypeptide, polyketide and fatty acid synthases SCOPEC Aspartate aminotransferaselike domain NAD(P)-binding Rossmann-fold domain Phosphotransferases on alcohol groups Hydro-lyase Alkyl or aryl transferase P-loop containing nucleoside triphosphate hydrolases (Trans)glycosidases Alcohol dehydrogenase using NAD(P)+ Trypsin-like serine proteases O- or S-glycosidases George et al., SCOPEC: a database of protein catalytic domains, Bioinformatics, 20, i130-i136 (2004).
57 P450 40% 55% CYP3A4 33 3A3A 4 EC 1.14
58 EC 2.4 Ross et al., Higher plant glycosyltransferases, Genome Biol. 2(2): reviews reviews (2001).
59 EC EC EC EC
60 PubMed
メタボローム技術で得られる代謝経路不明な多数の化合物の組み合わせから経路を予測する手法の開発
Title メタボローム技術で得られる代謝経路不明な多数の化合物の組み合わせから経路を予測する手法の開発 Author(s) 小寺, 正明 Citation2010 年度科学技術振興機構 ERATO 湊離散構造処理系プロジェクト講究録. p.193-203. Issue Date 2011-06 Doc URL http://hdl.handle.net/2115/48442 Type conference
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課題名 2 項関係に基づくゲノムと生命システムの機能解読 代表研究者京都大学化学研究所教授金久實 1. 代表研究者による成果概要報告 1-1. 研究開発のねらいヒトからバクテリアまで数多くの生物種において全ゲノム配列が続々と決定され ゲノム情報を基盤に細胞 個体 生態系といった高次生命システムの理解が進み 同時に創薬 医療をはじめとしたゲノム情報の有効利用が活発化している これまでに決定されたゲノムの配列情報は国際
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