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System-level multi-target drug discovery from natural products with applications to cardiovascular diseases

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Abstract

The term systems pharmacology describes a field of study that uses computational and experimental approaches to broaden the view of drug actions rooted in molecular interactions and advance the process of drug discovery. The aim of this work is to stick out the role that the systems pharmacology plays across the multi-target drug discovery from natural products for cardiovascular diseases (CVDs). Firstly, based on network pharmacology methods, we reconstructed the drug–target and target–target networks to determine the putative protein target set of multi-target drugs for CVDs treatment. Secondly, we reintegrated a compound dataset of natural products and then obtained a multi-target compounds subset by virtual-screening process. Thirdly, a drug-likeness evaluation was applied to find the ADME-favorable compounds in this subset. Finally, we conducted in vitro experiments to evaluate the reliability of the selected chemicals and targets. We found that four of the five randomly selected natural molecules can effectively act on the target set for CVDs, indicating the reasonability of our systems-based method. This strategy may serve as a new model for multi-target drug discovery of complex diseases.

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References

  1. Boran AD, Iyengar R (2010) Systems approaches to polypharmacology and drug discovery. Curr Opin Drug Disc 13:297–309. doi:10.1371/journal.pone.0040262

    CAS  Google Scholar 

  2. Csermely P, Agoston V, Pongor S (2005) The efficiency of multi-target drugs: the network approach might help drug design. Trends Pharmacol Sci 26:178–182. doi:10.1016/j.tips.2005.02.007

    Article  CAS  PubMed  Google Scholar 

  3. Wist AD, Berger SI, Iyengar R (2009) Systems pharmacology and genome medicine: a future perspective. Genome Med 1:11. doi:10.1186/gm11

    Article  PubMed Central  PubMed  Google Scholar 

  4. Morrow JK, Tian L, Zhang S (2010) Molecular networks in drug discovery. Crit Rev Biomed Eng 38:143–156. doi:10.1615/CritRevBiomedEng.v38.i2.30

    Article  PubMed Central  PubMed  Google Scholar 

  5. Kell D (2006) Systems biology, metabolic modelling and metabolomics in drug discovery and development. Drug Discov Today 11:1085–1092. doi:10.1016/j.drudis.2006.10.004

    Article  CAS  PubMed  Google Scholar 

  6. Cascante M, Boros LG, Comin-Anduix B, de Atauri P, Centelles JJ, Lee PW-N (2002) Metabolic control analysis in drug discovery and disease. Nat Biotechnol 20:243–249. doi:10.1038/nbt0302-243

    Article  CAS  PubMed  Google Scholar 

  7. Murthy D, Attri KS, Gokhale RS (2013) Network, nodes and nexus: systems approach to multitarget therapeutics. Curr Opin Biotech 24:1129–1136. doi:10.1016/j.copbio

    Article  CAS  PubMed  Google Scholar 

  8. Huang C, Zheng C, Li Y, Wang Y, Lu A, Yang L (2013) Systems pharmacology in drug discovery and therapeutic insight for herbal medicines. Brief Bioinform (in press). doi:10.1093/bib/bbt035

  9. Liu H, Wang J, Zhou W, Wang Y, Yang L (2013) Systems approaches and polypharmacology for drug discovery from herbal medicines: an example using licorice. J Ethnopharmacol 146:773–793. doi:10.1016/j.jep.2013.02.004

    Article  CAS  PubMed  Google Scholar 

  10. Wang X, Xu X, Li Y, Li X, Tao W, Li B, Wang Y, Yang L (2013) Systems pharmacology uncovers Janus functions of botanical drugs: activation of host defense system and inhibition of influenza virus replication. Integr Biol 5:351–371. doi:10.1039/c2ib20204b

    Article  CAS  Google Scholar 

  11. Li B, Xu X, Wang X, Yu H, Li X, Tao W, Wang Y, Yang L (2012) A systems biology approach to understanding the mechanisms of action of Chinese herbs for treatment of cardiovascular disease. Int J Mol Sci 13:13501–13520. doi:10.3390/ijms131013501

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Wang X, Xu X, Tao W, Li Y, Wang Y, Yang L (2012) A systems biology approach to uncovering pharmacological synergy in herbal medicines with applications to cardiovascular disease. Evid-Based Compl Alt (in press). doi:10.1155/2012/519031

  13. Tao W, Xu X, Wang X, Li B, Wang Y, Li Y, Yang L (2012) Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease. J Ethnopharmacol 145:1–10. doi:10.1016/j.jep.2012.09.051

    Article  PubMed  Google Scholar 

  14. Zhou W, Wang Y (2014) A network-based analysis of the types of coronary artery disease from traditional Chinese medicine perspective: Potential for therapeutics and drug discovery. J Ethnopharmacol 151:66–77. doi:10.1016/j.jep.2013.11.007

    Article  PubMed  Google Scholar 

  15. Singh N, Guha R, Giulianotti MA, Pinilla C, Houghten RA, Medina-Franco JL (2009) Chemoinformatic analysis of combinatorial libraries, drugs, natural products, and molecular libraries small molecule repository. J Chem Inf Model 49:1010–1024. doi:10.1021/ci800426u

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. Austin CP, Brady LS, Insel TR, Collins FS (2004) NIH molecular libraries initiative. Science 306:1138–1139. doi:10.1126/science.1105511

    Article  CAS  PubMed  Google Scholar 

  17. Irwin JJ, Shoichet BK (2005) ZINC-a free database of commercially available compounds for virtual screening. J Chem Inf Model 45:177–182. doi:10.1021/ci049714+

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Ertl P, Roggo S, Schuffenhauer A (2008) Natural product-likeness score and its application for prioritization of compound libraries. J Chem Inf Model 48:68–74. doi:10.1021/ci700286x

    Article  CAS  PubMed  Google Scholar 

  19. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT (2000) Gene Ontology: tool for the unification of biology. Nat Genet 25:25–29. doi:10.1038/75556

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  20. Smoot ME, Ono K, Ruscheinski J, Wang P-L, Ideker T (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27:431–432. doi:10.1093/bioinformatics/btq675

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  21. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748. doi:10.1006/jmbi.1996.0897

    Article  CAS  PubMed  Google Scholar 

  22. Xu X, Zhang W, Huang C, Li Y, Yu H, Wang Y, Duan J, Ling Y (2012) A novel chemometric method for the prediction of human oral bioavailability. Int J Mol Sci 13:6964–6982. doi:10.3390/ijms13066964

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Yamanishi Y, Kotera M, Kanehisa M, Goto S (2010) Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework. Bioinformatics 26:i246–i254. doi:10.1093/bioinformatics/btq176

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  24. Korcsmáros T, Szalay MS, Böde C, Kovács IA, Csermely P (2007) How to design multi-target drugs: target search options in cellular networks. Expert Opin Drug Discov 2:1–10

    Article  Google Scholar 

  25. Barabási A-L, Gulbahce N, Loscalzo J (2011) Network medicine: a network-based approach to human disease. Nat Rev Genet 12:56–68. doi:10.1038/nrg2918

    Article  PubMed Central  PubMed  Google Scholar 

  26. Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, Fridman W-H, Pagès F, Trajanoski Z, Galon J (2009) ClueGO: a cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25:1091–1093. doi:10.1093/bioinformatics/btp101

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  27. Gao F, de Beer VJ, Hoekstra M, Xiao C, Duncker DJ, Merkus D (2010) Both \({\upbeta }\)1-and \({\upbeta }\)2-adrenoceptors contribute to feedforward coronary resistance vessel dilation during exercise. Am J Physiol Heart C 298:H921–H929. doi: 10.1152/ajpheart.00135.2009

    Article  CAS  Google Scholar 

  28. Yoshioka T, Fujii E, Endo M, Wada K, Tokunaga Y, Shiba N, Hohsho H, Shibuya H, Muraki T (1998) Antiinflammatory potency of dehydrocurdione, a zedoary-derived sesquiterpene. Inflamm Res 47:476–481. doi:10.1007/s000110050361

    Article  CAS  PubMed  Google Scholar 

  29. Pan M-H, Huang T-M, Lin J-K (1999) Biotransformation of curcumin through reduction and glucuronidation in mice. Drug Metab Dispos 27:486–494

    CAS  PubMed  Google Scholar 

  30. Kurahashi K, Fujiwara M (1976) Adrenergic neuron blocking action of dehydrocorydaline isolated from Corydalis bulbosa. Can J Physiol Pharm 54:287–293. doi:10.1139/y76-042

    Article  CAS  Google Scholar 

  31. Xu Z, Chen X, Fu S, Bao J, Dang Y, Huang M, Chen L, Wang Y (2012) Dehydrocorydaline inhibits breast cancer cells proliferation by inducing apoptosis in MCF-7 cells. Am J Chin Med 40:177–185. doi:10.1142/S0192415X12500140

    Article  CAS  PubMed  Google Scholar 

  32. Pujol A, Mosca R, Farrés J, Aloy P (2010) Unveiling the role of network and systems biology in drug discovery. Trends Pharmacol Sci 31:115–123. doi:10.1016/j.tips.2009.11.006

    Article  CAS  PubMed  Google Scholar 

  33. Masferrer JL, Zweifel BS, Manning PT, Hauser SD, Leahy KM, Smith WG, Isakson PC, Seibert K (1994) Selective inhibition of inducible cyclooxygenase 2 in vivo is antiinflammatory and nonulcerogenic. Proc Natl Acad Sci USA 91:3228–3232. doi:10.1073/pnas.91.8.3228

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  34. Li N, Liu JY, Qiu H, Harris TR, Sirish P, Hammock BD, Chiamvimonvat N (2011) Use of metabolomic profiling in the study of arachidonic acid metabolism in cardiovascular disease. Congest Heart Fail 17:42–46. doi:10.1111/j.1751-7133.2010.00209.x

    Article  PubMed Central  PubMed  Google Scholar 

  35. Wang Y, Liu Z, Li C, Li D, Ouyang Y, Yu J, Guo S, He F, Wang W (2012) Drug target prediction based on the herbs components: the study on the multitargets pharmacological mechanism of qishenkeli acting on the coronary heart disease. Evid Based Complement Altern (in press). doi:10.1155/2012/698531

  36. Ho CY, Seidman CE (2006) A contemporary approach to hypertrophic cardiomyopathy. Circulation 113:e858–e862. doi:10.1161/circulationaha.105.591982

    Article  PubMed  Google Scholar 

  37. Griendling KK, Murphy T, Alexander RW (1993) Molecular biology of the renin-angiotensin system. Circulation 87:1816–1828. doi:10.1161/01.CIR.87.6.1816

    Article  CAS  PubMed  Google Scholar 

  38. Li X, Xu X, Wang J, Yu H, Wang X, Yang H, Xu H, Tang S, Li Y, Yang L (2012) A system-level investigation into the mechanisms of chinese traditional medicine: compound danshen formula for cardiovascular disease treatment. PLoS One 7:e43918. doi:10.1371/journal.pone.0043918

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  39. Ma XH, Shi Z, Tan C, Jiang Y, Go ML, Low BC, Chen YZ (2010) In-silico approaches to multi-target drug discovery. Pharm Res 27:739–749. doi:10.1007/s11095-010-0065-2

    Article  CAS  PubMed  Google Scholar 

  40. Cheng TO (2007) Cardiovascular effects of Danshen. Int J Cardiol 121:9–22. doi:10.1016/j.ijcard.2007.01.004

    Article  PubMed  Google Scholar 

  41. Konik E, Kurtz E, Sam F, Sawyer D (2012) Coronary artery spasm, hypertension, hypokalemia and licorice. J Clin Case Rep 2:143. doi:10.4172/2165-7920.1000143

  42. Lü D-Y, Cao Y, Li L, Zhu Z-Y, Dong X, Zhang H, Chai Y-F, Lou Z-Y (2011) Comparative analysis of essential oils found in Rhizomes Curcumae and Radix Curcumae by gas chromatography-mass spectrometry. J Pharm Anal 1:203–207. doi:10.1016/j.jpha.2011.05.001

  43. Fan HY, Fu FH, Yang MY, Xu H, Zhang AH, Liu K (2010) Antiplatelet and antithrombotic activities of salvianolic acid A. Thromb Res 126:e17–e22. doi:10.1016/j.thromres.2010.04.006

    Article  CAS  PubMed  Google Scholar 

  44. Kim YH, Shin EK, Kim DH, Lee HH, Park JHY, Kim J-K (2010) Antiangiogenic effect of licochalcone A. Biochem Pharmacol 80:1152–1159. doi:10.1016/j.bcp.2010.07.006

    Article  CAS  PubMed  Google Scholar 

  45. Kim M, Kim Y (2010) Hypocholesterolemic effects of curcumin via up-regulation of cholesterol 7a-hydroxylase in rats fed a high fat diet. Nutr Res Pract 4:191–195. doi:10.4162/nrp.2010.4.3.191

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  46. Xie L, Evangelidis T, Xie L, Bourne PE (2011) Drug discovery using chemical systems biology: weak inhibition of multiple kinases may contribute to the anti-cancer effect of nelfinavir. PLoS Comput Biol 7:e1002037. doi:10.1371/journal.pcbi.1002037

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  47. Wang J-G, Staessen JA (2000) Genetic polymorphisms in the renin-angiotensin system: relevance for susceptibility to cardiovascular disease. Eur J Pharmacol 410:289–302. doi:10.1016/S0014-2999(00)00822-0

    Article  CAS  PubMed  Google Scholar 

  48. Bai JP, Abernethy DR (2013) Systems pharmacology to predict drug toxicity: integration across levels of biological organization. Annu Rev Pharmacol 53:451–473. doi:10.1146/annurev-pharmtox-011112-140248

    Article  CAS  Google Scholar 

  49. Serena DT, Gianni C, Valentina C, Mauro G, Tiziana C, Chiara S, Simone N, Barbara M, Giuseppina B, Virgilio M (2013) Cytocompatibility evaluation of glycol-chitosan coated boron nitride nanotubes in human endothelial cells. Colloids Surf B Biointerfaces 111:142–149. doi:10.1016/j.colsurfb.2013.05.031

    Article  Google Scholar 

  50. Xiong X, Yang X, Liu Y, Zhang Y, Wang P, Wang J (2013) Chinese herbal formulas for treating hypertension in traditional Chinese medicine: perspective of modern science. Hypertens Res 36:570–579. doi:10.1038/hr.2013.18

    Article  PubMed Central  PubMed  Google Scholar 

  51. Webb NJ, Bottomley MJ, Watson CJ, Brenchley PE (1998) Vascular endothelial growth factor (VEGF) is released from platelets during blood clotting: implications for measurement of circulating VEGF levels in clinical disease. Clin Sci 94:395–404. doi:10.1042/cs0940395

    CAS  PubMed  Google Scholar 

  52. Thomas T, Advani A (2006) Inflammation in cardiovascular disease and regulation of the actin cytoskeleton in inflammatory cells: the actin cytoskeleton as a target. Cardiovasc Hematol Agents Med Chem 4:165–182. doi:10.2174/187152506776369926

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

We would like to express our sincere gratitude to Editor in Chief Guillermo A. Morales for assistance with the English correction of the manuscript. This work was supported by Grants from Northwest A & F University, National Natural Science Foundation of China (31170796 and 81373892). And it also was supported in part by China Academy of Chinese Medical Sciences (ZZ0608).

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Correspondence to Yonghua Wang.

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Chunli Zheng and Jinan Wang have contributed equally to this study.

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Zheng, C., Wang, J., Liu, J. et al. System-level multi-target drug discovery from natural products with applications to cardiovascular diseases. Mol Divers 18, 621–635 (2014). https://doi.org/10.1007/s11030-014-9521-y

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