* 张燕玲, 黄明峰, 乔延江 ( 北京中医药大学中药信息工程研究室, 北京 100102) 2 Intersection 15 221 31 177 15 073 32 376 2 IL-6 JAK /STAT 2 coronary heart disease CHD 1 % 390 1 CHD CHD 1 OMIM Table 1 Coronary heart disease related genes from OMIM database CHD #608320 ADCAD1 #610947 ADCAD2 1 CHD OMIM * 601398 VEGFB B * 300034 AGTR2 II OMIM * # CHD 2 2 58 CHD 18 15 2013-01-06 2008BAI51B01 81173522 * Tel 010 84738661 E-mail yjqiao @ 263. net #608446 MYOCARDIAL INFARCTION % 611139 CHDS8 % 612030 CHDS9 % 108725 ATHS * 163731 NOS1 28 9 1 CHD 2721
1 Fig. 1 Coronary heart disease related targets from literatures CHD GP IIb /IIIa β 14 CHD DrugBank 2 150 176 2 2 Table 2 DrugBank Coronary heart disease drugs and related targets from DrugBank database ID DB06209 P2Y 12 DB00584 DB00678 II II DB00227 HMG-CoA HMG-CoA α-l DB01020 α-2 DB01115 L α-1c α-1d α-1s α-1h α2 β2 A1 DB06779 III A DB00343 γ-1 DB00457 α-1a α-1b α-1d DB00727 A DB01170 2722
CHD CHD Reactome 149 CHD 179 CHD 2 Cytoscape2. 8. 2 Plugins Advanced Network Merge union 3 CHD 15 221 31 177 2 15 073 32 376 3 2 Fig. 2 Coronary heart disease network 8 hub 3-4 hub hub 5 3 3. 1 k P k k 3. 2 Barabasi-Albert BA Fig. 3 Coronary heart disease drug action network 6 P k ~ K - γ log γ γ < 3 CHD CHD 4 P k = - 1. 736k - 0. 668 P k = - 1. 658k - 0. 761 P k k log 5 7 9-10 CHD 6. 920 2723
6. 739-6 5 ~ 7 2 5 ~ 7 11-12 27 2 27 6 - Fig. 6 Path length-frequency statistics figure of CHD disease network upper and drug action network down 2724 3. 3 1 100% 3. 4 13 2. 488
2. 532 16 CGRP 4 CHD Intersection CGRP 7 CHD CGRP 5 771 5 179 1 571 8 b IL-6 IL-6 IL-6R gp130 CHD 2 JAK1 JAK2 TYK2 JAK /STAT JAK JAK1 JAK2 JAK3 Tyk2 17 4 gp130 IL-6 IL-6 IL-6R gp130 Jak STAT STAT1 STAT3 STAT5 SH2 DNA Bcl-xL Bcl-2 Mcl- 1 CyclinD1 c-myc c-jun Fas VEGF 18 JAK /STAT JAK /STAT 19 Funamoto 20 gp130 STAT3 IL-6 JAK /STAT 7 Fig. 7 The intersection of CHD disease network and drug action IL-6 JAK-STAT network 5 CHD CHD calcitonin gene-related peptide CGRP 8 a CGRP 4 CGRP CHD 14 CGRP CHD CHD 15 CGRP 2725
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Action mechanism of drugs for preventing and treating coronary heart disease based on biological networks ZHANG Yan-ling HUANG Ming-feng QIAO Yan-jiang * Research Center of Traditional Chinese Medicine Information Engineering Beijing University of Chinese Medicine Beijing 100102 China Abstract Coronary heart disease CHD related genes and targets as well as drug targets for preventing and treating CHD were taken as the study objects to build a CHD disease network and a drug action network preventing and treating CHD. Such topological characteristic parameters of the networks as degree distribution characteristic path length connectivity and heterogeneity were analyzed to verify the reliability of the networks. On that basis the intersection calculation was conducted for both networks to analyze the drug action mechanism of their sub-networks. The disease network are composed of 15 221 nodes and 31 177 sides while the drug action network preventing and treating CHD has 15 073 nodes and 32 376 sides. Both of their topological characteristic parameters showed scale-free small world structural characteristics. Two reaction pathways in the sub-networks calcitonin gene-related peptide and IL-6 activated JAK / STAT were taken as examples to discuss the indirect action mechanism for preventing and treating CHD. The results showed that the biological network analysis method combining the disease network and the drug action network is helpful to further studies on the action mechanism of the drugs and significant to the prevention and treatment of diseases. Key words coronary heart disease disease network drug action network network characteristics action mechanism doi 10. 4268 /cjcmm20131634 2014 2012 941-2013 37 2 http / /tsqb. cintcm. com 16 100700 010 64014411-3212 2727