Network-based TCM Pharmacology

Network-based TCM Pharmacology

Jing ZhaoJing ZhaoModern Research Center for Traditional Chinese Medicine

Second Military Medical UniversityShanghai, China

Jan. 14, 2010

Sino-German Workshop on Computational systems biology approaches for cancer research and biomarker discovery

• Long history

• Efficacy and safety for complex chronic diseases

• Complicated mechanisms

Characteristics of the TCM

•Holistic, complementary, synergic •Multi-component, multi-target, multi-dimensional pharmacology

Pharmacology & Therapeutics 2000, 86:191-198

Complicated mechanisms of TCM

Workflow for network-based TCM pharmacology study

Zhao J, Jiang P, Zhang WD. Briefings in Bioinformatics 2009, doi:10.1093/bib/bbp063

TCM databases

• The TCM database • The 3D structure database of components from Chinese traditional medicinal herbs • Traditional Chinese Medicine Information Database (TCMID )

• Large scale Natural Product Library (both virtual and material)

• ~ 120 TCM herbs

• ~ 5000 compounds , ~ 500 new compounds

In our laboratory:

Techniques usually applied to isolate active components from TCM

• Thin layer chromatography (TLC)• Column chromatography (CC)• Medium Pressure Liquid Chromatography (MPLC)• High Pressure liquid chromatography (HPLC)• High-speed countercurrent chromatography(HSCCC)• Macroporous adsorptive resins (MAR)• Molecular imprinting technique (MIT)

Compounds isolated from TCM materials that are also drugs approved by the FDA.

Compound name CAS number

DrugBank ID

Drug Function Latin Name of Source TCM material

Ajmaline 4360-12-7 DB01426 Antiarrhythmic Radix Rauvolfiae Verticillatae

Acylanid 1111-39-3 DB00511 Anti-Arrhythmia Digitalis lanata

Atropine 51-55-8 DB00572 Anesthesia Radix Physochlainae

Azelaic Acid 123-99-9 DB00548 Dermatologic Artemisia scoparia

Benzyl Benzoate 120-51-4 DB00676 Acaricides Dianthus superbus

Caffeine 5743-12-4 DB00201 Anorexigenic Agents

Camellia sinensis

Cocaine 50-36-2 DB00907 Anesthetics pericarpium papaveris

Codeine 41444-62-6 DB00318 Analgesics Stephania cepharantha

Colchicine 64-86-8 DB01394 Gout Suppressants

Bulbus Lilii

Crystodigin 71-63-6 DB01396 Anti-Arrhythmia Digitalis purpurea

Dicoumarin 66-76-2 DB00266 Anticoagulants Daphne genkwa

Dimethyl sulfoxide 67-68-5 DB01093 Analgesics Phaseolus vulgaris

… … … … …

Collection of TCM formulae and their main ingredients

TCM formula Materials Main bioactive compounds

Shexiang Baoxin Pill Moschus, Radix rhizoma ginseng, Calculus bovis, Cortex cinnamomi, Styrax, Venenum bufonis, Borneolum syntheticum

Borneol, bufalin, chensodeoxycholic acid, cinnamaldehyde, cinnamic acid, cinobufagin, cinnamic acid, deoxycholic acid, ginsenoside Rb1, ginsenoside Rc, ginsenoside Rd, ginsenoside Re, isoborneol, muscone, resibufogenin

Yin Chen Hao Tang Flos Artemisiae,Fructus Gardeniae Jasminoidis, Radix et Rhizoma Rhei.

6,7-dimethylesculetin, chlorogenic acid, capillarisin, geniposide and rhein

Danggui Buxue decoction

Radix Angelica Sinensis, Radix Astragli

ononoside, calycosin,3-butylphthalide and ligustilide

Danggui Buxue Decoction

Radix Angelica Sinensis,Radix Astragli

Ligustilide, astragaloside IV and formononetin

Si Wu Tang Radix Angelicae Sinensis,Raidix Paeoniae Alba,Rhizoma Chuanxiong,Radix Rehmanniae preparata

ligustilide, peoniflorin, ferulaic acid and ligustrazine

Huang-Lian-Jie-Du-Tang

Coptis chinensis, Scutellaria baicalensis, Phellodendron, Gardeniae jasminoides

Geniposide, Jatrorrhizine, Palmatine, Berberine, Baicalin, Baicalein, Wogonin

Zhen Tong Tang Corydalis tuber, Aconiti sinensis tuber, Hypecoum chinese (fr), Semen Ziziphi Spinosae

Fumarine, tetrahydropalmatine, bromcholitin, tetrahydrocoptisine,

… ... …

Disease-associated networks

Asthma network

Agarwal P, Searls DB. Briefings in Bioinformatics 2008; 9:479-492.

Lee D, Park J, Kay K et al. Proc Natl Acad Sci USA 2008; 105:9880-9885.

Disease Class Disease

Metabolic disorders

Type 2 diabetes, Type 1 diabetes, Obesity

Cancers Colon cancer, Prostate cancer, Pancreatic cancers, Pancreatic ductal adenocarcinom(PDAC), glioblastoma, Breast cancer, Gastric cancer, melanoma, Leukemia

Central neural system diseases

Huntington disease, Inherited ataxias, Parkinson’s disease, Alzheimer's disease, Schizophrenia, Glaucoma

Cardiovascular diseases

Heart failure, Atherosclerosis

Immune diseases

HIV-1, Autoimmune disease, Asthma, Rheumatoid arthritis

Others Dupuytren’s disease, Inflammation, Hepatitis C virus, Epstein–Barr virus, Benign Prostatic Hyperplasia, multiple sclerosis brain-lesion, Autosomal Dominant Polycystic Kidney Disease (ADPKD), Usher syndrome, Osteoarthritis

Literature search results of disease-associated networks

Rahman SA, Schomburg D.Bioinformatics 2006; 22:1767-1774.

Chock points

a. bridging nodes b. High-betweenness nodes

Hwang S, Son S-W, Kim SC et al.Journal of Theoretical Biology 2008; 252:722-731.Hwang WC, Zhang A, Ramanathan M. Clin Pharmacol Ther 2008; 84:563-572.

Mathematical models and algorithms to identify potential target combinations:• the minimum knockout problem• the min-interference problem • the OPMET model • the multiple target optimal intervention (MTOI) model• software TIde (Target Identification)

Ruths DA, Nakhleh L, Iyengar MS et al. J Comput Biol 2006; 13:1546-1557.Dasika MS, Burgard A, Maranas CD. Biophysical Journal 2006; 91:382-398.Sridhar P, Song B, Kahveciy T et al. Pacific Symposium on Biocomputing 2008; 13:291-302.Yang K, Bai H, Ouyang Q et al. Mol Syst Biol 2008; 4:228.Schulz M, Bakker B, Klipp E. BMC Bioinformatics 2009; 10:344.

Database Drug(chemical) No.

Target(protein) No.

e.g. Targets of simvastatin (anticholesteremic agent)

DrugBank 4765 4566 AGT;BMP2;CASP3;CCL2;CD40;COL13A1; CYP3A3;F2;HLA-DRB5;HMGCR;ICAM1; IFNG;IL6;IL8;ITGB2;LTB;MAPK3;MMP3; MMP9;PPARA;RAC1;RHOA;SERPINE1;TNF;VEGF

TTD 4198 1675 HMGCR; PPARG

PDTD - 841 -

Matador 801 2901 Direct interaction: CYP3A4; HMGCR Indirect interaction: APOE; COG2; LDL; ENSP00000352471; LDLR; Lipoprotein(a); LPA

STITCH >68,000 >1,500,000 LPA; CYP3A4; LDLR; ENSP00000352471; APOE; HMGCR; COG2

Comparison of drug target databases

Case study 1: Antidepressant activity of St.John’s Wort

Zhao J, Jiang P, Zhang WD: Molecular networks for the study of TCM

pharmacology. Briefings in Bioinformatics 2009, doi:10.1093/bib/bbp063

Main active ingredients of JSW:• hyperforin (HP)

• hypericin (HY)

• pseudohypericin (PH)

• amentoflavone (AF)• flavonoids (FL)

the effects of the SJW active compounds on the system of neuroactive ligand-receptor interaction

Drug-target network of FDA approved antidepressants and SJW compounds.

Case study 2: The effect of Realgar-Indigo naturalis formula(RIF) on acute promyelocytic leukemia(APL)

Wang L, Zhou G-B, Liu P et al. Proc Natl Acad Sci USA 2008; 105:4826-4831.

• tetraarsenic tetrasulfide (As4S4, A) • indirubin (I) • tanshinone IIA (T)

Main active compounds of RIF

Effects of As4S4 （ A ）、 indirubin(I) and tanshinone IIA(T) on different APL-associated proteins

Functional networks of APL disease gene-encoded proteins and RIF-targeted proteins.

(A) Protein interaction network. (B) Protein-pathway association network. [D]: GO: regulation of cell differentiation; [P]: GO: regulation of cell proliferation; [B]: GO: regulation of cell differentiation, and regulation of cell proliferation

Regulations of single RIF compounds on different proteins on AML pathway.

Acknowledgements

Zhiwei Cao Tongji University

Shanghai Center of Bioinformation and Technology

Kailin Tang Shanghai Center of Bioinformation and Technology

Lin Tao Shanghai Center of Bioinformation and Technology

Weidong Zhang Second Military Medical University

Peng Jiang Second Military Medical University

Pengyuan Yang Second Military Medical University

Yaocheng Rui Second Military Medical University

Fan Li Second Military Medical University

Thanks!