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Published in: Chinese Medicine 1/2018

Open Access 01-12-2018 | Review

In silico approach in reveal traditional medicine plants pharmacological material basis

Authors: Fan Yi, Li Li, Li-jia Xu, Hong Meng, Yin-mao Dong, Hai-bo Liu, Pei-gen Xiao

Published in: Chinese Medicine | Issue 1/2018

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Abstract

In recent years, studies of traditional medicinal plants have gradually increased worldwide because the natural sources and variety of such plants allow them to complement modern pharmacological approaches. As computer technology has developed, in silico approaches such as virtual screening and network analysis have been widely utilized in efforts to elucidate the pharmacological basis of the functions of traditional medicinal plants. In the process of new drug discovery, the application of virtual screening and network pharmacology can enrich active compounds among the candidates and adequately indicate the mechanism of action of medicinal plants, reducing the cost and increasing the efficiency of the whole procedure. In this review, we first provide a detailed research routine for examining traditional medicinal plants by in silico techniques and elaborate on their theoretical principles. We also survey common databases, software programs and website tools that can be used for virtual screening and pharmacological network construction. Furthermore, we conclude with a simple example that illustrates the whole methodology, and we present perspectives on the development and application of this in silico methodology to reveal the pharmacological basis of the effects of traditional medicinal plants.
Literature
1.
go back to reference Schippmann U, Cunningham AB, Leaman DJ. Impact of cultivation and gathering of medicinal plants on biodiversity: global trends and issues. Rome: FAO; 2002. p. 142–67. Schippmann U, Cunningham AB, Leaman DJ. Impact of cultivation and gathering of medicinal plants on biodiversity: global trends and issues. Rome: FAO; 2002. p. 142–67.
2.
go back to reference Koutsoukas A, et al. From in silico target prediction to multi-target drug design: current databases, methods and applications. J Proteom. 2011;74(12):2554–74.CrossRef Koutsoukas A, et al. From in silico target prediction to multi-target drug design: current databases, methods and applications. J Proteom. 2011;74(12):2554–74.CrossRef
3.
go back to reference Zhang X, et al. Danshen-Chuanxiong-Honghua Ameliorates cerebral impairment and improves spatial cognitive deficits after transient focal ischemia and identification of active compounds. Front Pharmacol. 2017;8:452.CrossRefPubMedPubMedCentral Zhang X, et al. Danshen-Chuanxiong-Honghua Ameliorates cerebral impairment and improves spatial cognitive deficits after transient focal ischemia and identification of active compounds. Front Pharmacol. 2017;8:452.CrossRefPubMedPubMedCentral
4.
go back to reference Yi F, et al. In silico approach for anti-thrombosis drug discovery: P2Y1R structure-based TCMs screening. Front Pharmacol. 2016;7:531.CrossRefPubMed Yi F, et al. In silico approach for anti-thrombosis drug discovery: P2Y1R structure-based TCMs screening. Front Pharmacol. 2016;7:531.CrossRefPubMed
5.
go back to reference Yi F, et al. In silico profiling for secondary metabolites from Lepidium meyenii (maca) by the pharmacophore and ligand-shape-based joint approach. Chin Med. 2016;11(1):42.CrossRefPubMedPubMedCentral Yi F, et al. In silico profiling for secondary metabolites from Lepidium meyenii (maca) by the pharmacophore and ligand-shape-based joint approach. Chin Med. 2016;11(1):42.CrossRefPubMedPubMedCentral
6.
go back to reference Tu Y. The discovery of artemisinin (qinghaosu) and gifts from Chinese medicine. Nat Med. 2011;17(10):1217–20.CrossRefPubMed Tu Y. The discovery of artemisinin (qinghaosu) and gifts from Chinese medicine. Nat Med. 2011;17(10):1217–20.CrossRefPubMed
7.
go back to reference Zaman MA, Oparil S, Calhoun DA. Drugs targeting the renin-angiotensin-aldosterone system. Nat Rev Drug Discov. 2002;1(8):621–36.CrossRefPubMed Zaman MA, Oparil S, Calhoun DA. Drugs targeting the renin-angiotensin-aldosterone system. Nat Rev Drug Discov. 2002;1(8):621–36.CrossRefPubMed
8.
go back to reference Ghosh AK, Gemma S. Structure-based design of drugs and other bioactive molecules. Hoboken: John Wiley & Sons; 2015. p. 397–409.CrossRef Ghosh AK, Gemma S. Structure-based design of drugs and other bioactive molecules. Hoboken: John Wiley & Sons; 2015. p. 397–409.CrossRef
9.
go back to reference Rubio-Perez C, et al. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities. Cancer Cell. 2015;27(3):382–96.CrossRefPubMed Rubio-Perez C, et al. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities. Cancer Cell. 2015;27(3):382–96.CrossRefPubMed
10.
go back to reference Zhang Y, et al. Pathway of PPAR-gamma coactivators in thermogenesis: a pivotal traditional Chinese medicine-associated target for individualized treatment of rheumatoid arthritis. Oncotarget. 2016;7(13):15885–900.PubMedPubMedCentral Zhang Y, et al. Pathway of PPAR-gamma coactivators in thermogenesis: a pivotal traditional Chinese medicine-associated target for individualized treatment of rheumatoid arthritis. Oncotarget. 2016;7(13):15885–900.PubMedPubMedCentral
11.
go back to reference Ehrman TM, Barlow† DJ, Hylands‡ PJ. Phytochemical informatics of Traditional Chinese medicine and therapeutic relevance. J Chem Inf Model. 2007;47(6):2316–34.CrossRefPubMed Ehrman TM, Barlow† DJ, Hylands‡ PJ. Phytochemical informatics of Traditional Chinese medicine and therapeutic relevance. J Chem Inf Model. 2007;47(6):2316–34.CrossRefPubMed
12.
go back to reference Liu C, et al. Uncovering pharmacological mechanisms of Wu-tou decoction acting on rheumatoid arthritis through systems approaches: drug-target prediction, network analysis and experimental validation. Scientific Rep. 2015;5:9463.CrossRef Liu C, et al. Uncovering pharmacological mechanisms of Wu-tou decoction acting on rheumatoid arthritis through systems approaches: drug-target prediction, network analysis and experimental validation. Scientific Rep. 2015;5:9463.CrossRef
13.
go back to reference Gao B, et al. Platelet P2Y12 receptors are involved in the haemostatic effect of notoginsenoside Ft1, a saponin isolated from Panax notoginseng. Br J Pharmacol. 2014;171(1):214.CrossRefPubMed Gao B, et al. Platelet P2Y12 receptors are involved in the haemostatic effect of notoginsenoside Ft1, a saponin isolated from Panax notoginseng. Br J Pharmacol. 2014;171(1):214.CrossRefPubMed
14.
go back to reference Ji W, et al. Water-compatible molecularly imprinted polymers for selective solid phase extraction of dencichine from the aqueous extract of Panax notoginseng. J Chromatogr B. 2016;1008:225.CrossRef Ji W, et al. Water-compatible molecularly imprinted polymers for selective solid phase extraction of dencichine from the aqueous extract of Panax notoginseng. J Chromatogr B. 2016;1008:225.CrossRef
15.
go back to reference Esparza E, et al. Bioactive maca (Lepidium meyenii) alkamides are a result of traditional Andean postharvest drying practices. Phytochemistry. 2015;116:138–48.CrossRefPubMed Esparza E, et al. Bioactive maca (Lepidium meyenii) alkamides are a result of traditional Andean postharvest drying practices. Phytochemistry. 2015;116:138–48.CrossRefPubMed
16.
go back to reference Li Z, et al. Antioxidant and anti-inflammatory activities of berberine in the treatment of diabetes mellitus. Evid Based Complement Altern Med eCAM. 2014;2014(33):289264. Li Z, et al. Antioxidant and anti-inflammatory activities of berberine in the treatment of diabetes mellitus. Evid Based Complement Altern Med eCAM. 2014;2014(33):289264.
17.
go back to reference Liu H-K. Artemisinin, GABA signaling and cell reprogramming: when an old drug meets modern medicine. Sci Bull. 2017;62(6):386–7.CrossRef Liu H-K. Artemisinin, GABA signaling and cell reprogramming: when an old drug meets modern medicine. Sci Bull. 2017;62(6):386–7.CrossRef
18.
go back to reference Boonen J, et al. Alkamid database: chemistry, occurrence and functionality of plant N-alkylamides. J Ethnopharmacol. 2012;142(3):563–90.CrossRefPubMed Boonen J, et al. Alkamid database: chemistry, occurrence and functionality of plant N-alkylamides. J Ethnopharmacol. 2012;142(3):563–90.CrossRefPubMed
19.
go back to reference Umashankar V, Nandhitha S, Kalabharath P. InPACdb—Indian plant anticancer compounds database. Bioinformation. 2009;4(2):71–4.CrossRef Umashankar V, Nandhitha S, Kalabharath P. InPACdb—Indian plant anticancer compounds database. Bioinformation. 2009;4(2):71–4.CrossRef
20.
go back to reference Kim S-K, et al. TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine. BMC Complement Altern Med. 2015;15(1):218.CrossRefPubMedPubMedCentral Kim S-K, et al. TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine. BMC Complement Altern Med. 2015;15(1):218.CrossRefPubMedPubMedCentral
21.
go back to reference Fang X, et al. CHMIS-C: a comprehensive herbal medicine information system for cancer. J Med Chem. 2005;48(5):1481–8.CrossRefPubMed Fang X, et al. CHMIS-C: a comprehensive herbal medicine information system for cancer. J Med Chem. 2005;48(5):1481–8.CrossRefPubMed
22.
go back to reference Chen L, et al. Identification of compound–protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds. Mol Genet Genomics. 2016;291(6):2065–79.CrossRefPubMed Chen L, et al. Identification of compound–protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds. Mol Genet Genomics. 2016;291(6):2065–79.CrossRefPubMed
23.
go back to reference Loub WD, et al. NAPRALERT: computer handling of natural product research data. J Chem Inf Comput Sci. 1985;25(2):99–103.CrossRefPubMed Loub WD, et al. NAPRALERT: computer handling of natural product research data. J Chem Inf Comput Sci. 1985;25(2):99–103.CrossRefPubMed
24.
go back to reference Ihlenfeldt WD, et al. Enhanced CACTVS browser of the open NCI database. J Chem Inf Comput Sci. 2002;42(1):46.CrossRefPubMed Ihlenfeldt WD, et al. Enhanced CACTVS browser of the open NCI database. J Chem Inf Comput Sci. 2002;42(1):46.CrossRefPubMed
25.
26.
go back to reference Xue R, et al. TCMID: Traditional Chinese medicine integrative database for herb molecular mechanism analysis. Nucleic Acids Res. 2013;41(Database issue):D1089.PubMed Xue R, et al. TCMID: Traditional Chinese medicine integrative database for herb molecular mechanism analysis. Nucleic Acids Res. 2013;41(Database issue):D1089.PubMed
28.
go back to reference Luo M, Reid T-E, Simon Wang X. Discovery of natural product-derived 5-HT1A receptor binders by cheminfomatics modeling of known binders, high throughput screening and experimental validation. Comb Chem High Throughput Screen. 2015;18(7):685–92.CrossRefPubMedPubMedCentral Luo M, Reid T-E, Simon Wang X. Discovery of natural product-derived 5-HT1A receptor binders by cheminfomatics modeling of known binders, high throughput screening and experimental validation. Comb Chem High Throughput Screen. 2015;18(7):685–92.CrossRefPubMedPubMedCentral
29.
go back to reference Yi Y-D, Chang I-M. An overview of traditional Chinese herbal formulae and a proposal of a new code system for expressing the formula titles. Evid Based Complement Altern Med. 2004;1(2):125–32.CrossRef Yi Y-D, Chang I-M. An overview of traditional Chinese herbal formulae and a proposal of a new code system for expressing the formula titles. Evid Based Complement Altern Med. 2004;1(2):125–32.CrossRef
31.
go back to reference Kerns EH, Li D. Drug-like properties: concepts, structure design and methods. Oxford: Elsevier LTD; 2008. p. 125–6. Kerns EH, Li D. Drug-like properties: concepts, structure design and methods. Oxford: Elsevier LTD; 2008. p. 125–6.
32.
go back to reference Lipinski CA, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1. Adv Drug Deliv Rev. 2001;46(1–3):3–26.CrossRefPubMed Lipinski CA, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1. Adv Drug Deliv Rev. 2001;46(1–3):3–26.CrossRefPubMed
33.
go back to reference Veber DF, et al. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002;45(12):2615–23.CrossRefPubMed Veber DF, et al. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002;45(12):2615–23.CrossRefPubMed
34.
go back to reference Eldehna WM, et al. Synthesis and cytotoxic activity of biphenylurea derivatives containing indolin-2-one moieties. Molecules. 2016;21(6):762.CrossRefPubMedCentral Eldehna WM, et al. Synthesis and cytotoxic activity of biphenylurea derivatives containing indolin-2-one moieties. Molecules. 2016;21(6):762.CrossRefPubMedCentral
35.
go back to reference Van De Waterbeemd H, Gifford E. ADMET in silico modelling: towards prediction paradise? Nature reviews. Drug Discov. 2003;2(3):192. Van De Waterbeemd H, Gifford E. ADMET in silico modelling: towards prediction paradise? Nature reviews. Drug Discov. 2003;2(3):192.
36.
go back to reference Dhiman V, et al. Characterization of stress degradation products of amodiaquine dihydrochloride by liquid chromatography with high-resolution mass spectrometry and prediction of their properties by using ADMET predictor. J Sep Sci. 2017;40(23):4530–40.CrossRefPubMed Dhiman V, et al. Characterization of stress degradation products of amodiaquine dihydrochloride by liquid chromatography with high-resolution mass spectrometry and prediction of their properties by using ADMET predictor. J Sep Sci. 2017;40(23):4530–40.CrossRefPubMed
37.
go back to reference Willmann S, Lippert J, Schmitt W. From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools. Expert Opin Drug Metab Toxicol. 2005;1(1):159–68.CrossRefPubMed Willmann S, Lippert J, Schmitt W. From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools. Expert Opin Drug Metab Toxicol. 2005;1(1):159–68.CrossRefPubMed
38.
go back to reference Morris GM, Limwilby M. Molecular docking. New York: Humana Press; 2008. p. 365–82. Morris GM, Limwilby M. Molecular docking. New York: Humana Press; 2008. p. 365–82.
40.
go back to reference Najmanovich RJ, et al. Analysis of binding site similarity, small-molecule similarity and experimental binding profiles in the human cytosolic sulfotransferase family. Bioinformatics. 2007;23(2):e104.CrossRefPubMed Najmanovich RJ, et al. Analysis of binding site similarity, small-molecule similarity and experimental binding profiles in the human cytosolic sulfotransferase family. Bioinformatics. 2007;23(2):e104.CrossRefPubMed
41.
go back to reference Ewing TJA, et al. DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases. J Comput Aided Mol Des. 2001;15(5):411–28.CrossRefPubMed Ewing TJA, et al. DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases. J Comput Aided Mol Des. 2001;15(5):411–28.CrossRefPubMed
42.
go back to reference Yang H, et al. X-ray crystallographic structure of a teixobactin analogue reveals key interactions of the teixobactin pharmacophore. Chem Commun. 2017;53(18):2772–5.CrossRef Yang H, et al. X-ray crystallographic structure of a teixobactin analogue reveals key interactions of the teixobactin pharmacophore. Chem Commun. 2017;53(18):2772–5.CrossRef
43.
go back to reference Chen YC, et al. Prediction of protein pairs sharing common active ligands using protein sequence, structure, and ligand similarity. J Chem Inf Model. 2016;56(9):1734–45.CrossRefPubMed Chen YC, et al. Prediction of protein pairs sharing common active ligands using protein sequence, structure, and ligand similarity. J Chem Inf Model. 2016;56(9):1734–45.CrossRefPubMed
46.
go back to reference Hart TN, Ness SR, Read RJ. Critical evaluation of the research docking program for the CASP2 challenge. Proteins. 1997;29(Suppl 1):205–9.CrossRef Hart TN, Ness SR, Read RJ. Critical evaluation of the research docking program for the CASP2 challenge. Proteins. 1997;29(Suppl 1):205–9.CrossRef
47.
go back to reference Sullivan DC, Martin EJ. Exploiting structure-activity relationships in docking. J Chem Inf Model. 2008;48(4):817–30.CrossRefPubMed Sullivan DC, Martin EJ. Exploiting structure-activity relationships in docking. J Chem Inf Model. 2008;48(4):817–30.CrossRefPubMed
48.
go back to reference Zsoldos Z, et al. eHiTS: a new fast, exhaustive flexible ligand docking system. J Mol Graph Model. 2007;26(1):198–212.CrossRefPubMed Zsoldos Z, et al. eHiTS: a new fast, exhaustive flexible ligand docking system. J Mol Graph Model. 2007;26(1):198–212.CrossRefPubMed
49.
go back to reference Rarey M, et al. A fast flexible docking method using an incremental construction algorithm. J Mol Biol. 1996;261(3):470–89.CrossRefPubMed Rarey M, et al. A fast flexible docking method using an incremental construction algorithm. J Mol Biol. 1996;261(3):470–89.CrossRefPubMed
50.
go back to reference Friesner RA, et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem. 2004;47(7):1739–49.CrossRefPubMed Friesner RA, et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem. 2004;47(7):1739–49.CrossRefPubMed
51.
go back to reference Jones G, et al. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997;267(3):727–48.CrossRefPubMed Jones G, et al. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997;267(3):727–48.CrossRefPubMed
52.
53.
go back to reference Pierce BG, et al. ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics. 2014;30(12):1771–3.CrossRefPubMedPubMedCentral Pierce BG, et al. ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics. 2014;30(12):1771–3.CrossRefPubMedPubMedCentral
54.
go back to reference Arockia Babu M, et al. Development of 3D-QSAR models for 5-lipoxygenase antagonists: chalcones. Bioorg Med Chem. 2002;10(12):4035–41.CrossRefPubMed Arockia Babu M, et al. Development of 3D-QSAR models for 5-lipoxygenase antagonists: chalcones. Bioorg Med Chem. 2002;10(12):4035–41.CrossRefPubMed
55.
go back to reference Liu GY, et al. 3D-QSAR studies of insecticidal anthranilic diamides as ryanodine receptor activators using CoMFA, CoMSIA and DISCOtech. Chemosphere. 2010;78(3):300–6.CrossRefPubMed Liu GY, et al. 3D-QSAR studies of insecticidal anthranilic diamides as ryanodine receptor activators using CoMFA, CoMSIA and DISCOtech. Chemosphere. 2010;78(3):300–6.CrossRefPubMed
57.
go back to reference Patel Y, et al. A comparison of the pharmacophore identification programs: catalyst, DISCO and GASP. J Comput Aided Mol Des. 2002;16(8–9):653–81.CrossRefPubMed Patel Y, et al. A comparison of the pharmacophore identification programs: catalyst, DISCO and GASP. J Comput Aided Mol Des. 2002;16(8–9):653–81.CrossRefPubMed
59.
go back to reference Engels MF, et al. CerBeruS: a system supporting the sequential screening process. J Chem Inf Comput Sci. 2000;40(2):241–5.CrossRefPubMed Engels MF, et al. CerBeruS: a system supporting the sequential screening process. J Chem Inf Comput Sci. 2000;40(2):241–5.CrossRefPubMed
60.
go back to reference Lemmen C, Lengauer T, Klebe G. FLEXS: a method for fast flexible ligand superposition. J Med Chem. 1998;41(23):4502–20.CrossRefPubMed Lemmen C, Lengauer T, Klebe G. FLEXS: a method for fast flexible ligand superposition. J Med Chem. 1998;41(23):4502–20.CrossRefPubMed
61.
go back to reference Tervo AJ, et al. BRUTUS: optimization of a grid-based similarity function for rigid-body molecular superposition. 1. Alignment and virtual screening applications. J Med Chem. 2005;48(12):4076–86.CrossRefPubMed Tervo AJ, et al. BRUTUS: optimization of a grid-based similarity function for rigid-body molecular superposition. 1. Alignment and virtual screening applications. J Med Chem. 2005;48(12):4076–86.CrossRefPubMed
62.
go back to reference Yan X, et al. Enhancing molecular shape comparison by weighted Gaussian functions. J Chem Inf Model. 2013;53(8):1967–78.CrossRefPubMed Yan X, et al. Enhancing molecular shape comparison by weighted Gaussian functions. J Chem Inf Model. 2013;53(8):1967–78.CrossRefPubMed
63.
go back to reference Wermuth CG. Pharmacophores: historical perspective and viewpoint from a medicinal chemist. Methods Princ Med Chem. 2006;32:3. Wermuth CG. Pharmacophores: historical perspective and viewpoint from a medicinal chemist. Methods Princ Med Chem. 2006;32:3.
64.
go back to reference Zuo Z, MacMillan DW. Decarboxylative arylation of α-amino acids via photoredox catalysis: a one-step conversion of biomass to drug pharmacophore. J Am Chem Soc. 2014;136(14):5257–60.CrossRefPubMedPubMedCentral Zuo Z, MacMillan DW. Decarboxylative arylation of α-amino acids via photoredox catalysis: a one-step conversion of biomass to drug pharmacophore. J Am Chem Soc. 2014;136(14):5257–60.CrossRefPubMedPubMedCentral
65.
go back to reference Cereto-Massagué A, et al. Molecular fingerprint similarity search in virtual screening. Methods. 2015;71:58–63.CrossRefPubMed Cereto-Massagué A, et al. Molecular fingerprint similarity search in virtual screening. Methods. 2015;71:58–63.CrossRefPubMed
67.
go back to reference Consortium, U. UniProt: the universal protein knowledgebase. Nucleic Acids Res. 2017;45(D1):D158–69.CrossRef Consortium, U. UniProt: the universal protein knowledgebase. Nucleic Acids Res. 2017;45(D1):D158–69.CrossRef
68.
go back to reference Liu T, et al. BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 2007;35(Database issue):D198–201.CrossRefPubMed Liu T, et al. BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 2007;35(Database issue):D198–201.CrossRefPubMed
69.
go back to reference Chatr-aryamontri A, et al. The BioGRID interaction database: 2017 update. Nucleic Acids Res. 2017;45(D1):D369–79.CrossRefPubMed Chatr-aryamontri A, et al. The BioGRID interaction database: 2017 update. Nucleic Acids Res. 2017;45(D1):D369–79.CrossRefPubMed
70.
71.
go back to reference Wishart DS, et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 2006;34(suppl_1):D668–72.CrossRefPubMed Wishart DS, et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 2006;34(suppl_1):D668–72.CrossRefPubMed
72.
73.
go back to reference Keshava Prasad TS, et al. Human protein reference database-2009 update. Nucleic Acids Res. 2009;37(Database issue):D767–72.CrossRefPubMed Keshava Prasad TS, et al. Human protein reference database-2009 update. Nucleic Acids Res. 2009;37(Database issue):D767–72.CrossRefPubMed
74.
go back to reference Orchard S, et al. The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 2014;42(D1):D358–63.CrossRefPubMed Orchard S, et al. The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. 2014;42(D1):D358–63.CrossRefPubMed
75.
go back to reference Kanehisa M, et al. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353–61.CrossRefPubMed Kanehisa M, et al. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353–61.CrossRefPubMed
76.
go back to reference Deng L, et al. MTA1 modulated by miR-30e contributes to epithelial-to-mesenchymal transition in hepatocellular carcinoma through an ErbB2-dependent pathway. Oncogene. 2017;36(28):3976–85.CrossRefPubMed Deng L, et al. MTA1 modulated by miR-30e contributes to epithelial-to-mesenchymal transition in hepatocellular carcinoma through an ErbB2-dependent pathway. Oncogene. 2017;36(28):3976–85.CrossRefPubMed
77.
go back to reference Licata L, et al. MINT, the molecular interaction database: 2012 update. Nucleic Acids Res. 2012;40(1):D857–61.CrossRefPubMed Licata L, et al. MINT, the molecular interaction database: 2012 update. Nucleic Acids Res. 2012;40(1):D857–61.CrossRefPubMed
79.
go back to reference Gao Z, et al. PDTD: a web-accessible protein database for drug target identification. BMC Bioinform. 2008;9:104.CrossRef Gao Z, et al. PDTD: a web-accessible protein database for drug target identification. BMC Bioinform. 2008;9:104.CrossRef
80.
go back to reference Goodsell DS. The protein data bank, in atomic evidence. Berlin: Springer; 2016. p. 1–4. Goodsell DS. The protein data bank, in atomic evidence. Berlin: Springer; 2016. p. 1–4.
81.
go back to reference Croft D, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2014;42(Database issue):D472.CrossRefPubMed Croft D, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2014;42(Database issue):D472.CrossRefPubMed
83.
84.
go back to reference Zhu F, et al. Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res. 2011;40(D1):D1128–36.CrossRefPubMedPubMedCentral Zhu F, et al. Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res. 2011;40(D1):D1128–36.CrossRefPubMedPubMedCentral
85.
go back to reference Li S. Mapping ancient remedies: applying a network approach to traditional Chinese medicine. Science. 2015;350(6262):S72–4. Li S. Mapping ancient remedies: applying a network approach to traditional Chinese medicine. Science. 2015;350(6262):S72–4.
87.
go back to reference Du J, et al. KEGG-PATH: Kyoto encyclopedia of genes and genomes-based pathway analysis using a path analysis model. Mol BioSyst. 2014;10(9):2441–7.CrossRefPubMed Du J, et al. KEGG-PATH: Kyoto encyclopedia of genes and genomes-based pathway analysis using a path analysis model. Mol BioSyst. 2014;10(9):2441–7.CrossRefPubMed
88.
go back to reference Ekins S, et al. Algorithms for network analysis in systems-ADME/Tox using the MetaCore and MetaDrug platforms. Xenobiotica. 2006;36(10–11):877–901.CrossRefPubMed Ekins S, et al. Algorithms for network analysis in systems-ADME/Tox using the MetaCore and MetaDrug platforms. Xenobiotica. 2006;36(10–11):877–901.CrossRefPubMed
89.
go back to reference Kurata H, et al. Extended CADLIVE: a novel graphical notation for design of biochemical network maps and computational pathway analysis. Nucleic Acids Res. 2007;35(20):e134–e134.CrossRefPubMedPubMedCentral Kurata H, et al. Extended CADLIVE: a novel graphical notation for design of biochemical network maps and computational pathway analysis. Nucleic Acids Res. 2007;35(20):e134–e134.CrossRefPubMedPubMedCentral
90.
91.
92.
go back to reference De Nooy W, Mrvar A, Batagelj V. Exploratory social network analysis with Pajek, vol. 27. Cambridge: Cambridge University Press; 2011.CrossRef De Nooy W, Mrvar A, Batagelj V. Exploratory social network analysis with Pajek, vol. 27. Cambridge: Cambridge University Press; 2011.CrossRef
93.
go back to reference Junker BH, Klukas C, Schreiber F. VANTED: a system for advanced data analysis and visualization in the context of biological networks. BMC Bioinform. 2006;7(1):109.CrossRef Junker BH, Klukas C, Schreiber F. VANTED: a system for advanced data analysis and visualization in the context of biological networks. BMC Bioinform. 2006;7(1):109.CrossRef
95.
go back to reference Schwarz R, et al. Integrated network reconstruction, visualization and analysis using YANAsquare. BMC Bioinform. 2007;8(1):313.CrossRef Schwarz R, et al. Integrated network reconstruction, visualization and analysis using YANAsquare. BMC Bioinform. 2007;8(1):313.CrossRef
96.
go back to reference Wan W, et al. Metabolomics reveals that vine tea (Ampelopsis grossedentata) prevents high-fat-diet-induced metabolism disorder by improving glucose homeostasis in rats. PLoS ONE. 2017;12(8):e0182830.CrossRefPubMedPubMedCentral Wan W, et al. Metabolomics reveals that vine tea (Ampelopsis grossedentata) prevents high-fat-diet-induced metabolism disorder by improving glucose homeostasis in rats. PLoS ONE. 2017;12(8):e0182830.CrossRefPubMedPubMedCentral
Metadata
Title
In silico approach in reveal traditional medicine plants pharmacological material basis
Authors
Fan Yi
Li Li
Li-jia Xu
Hong Meng
Yin-mao Dong
Hai-bo Liu
Pei-gen Xiao
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Chinese Medicine / Issue 1/2018
Electronic ISSN: 1749-8546
DOI
https://doi.org/10.1186/s13020-018-0190-0

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