Systems toxicology: Systematic approach to predict toxicity

Current Pharmaceutical Design

Volumn 22, Issue 46, 2016, Pages 6911-6917

  Kiani, Narsis A ^a   Shang, Ming Mei ^a   Tegnér, Jesper ^a  

^a KAROLINSKA UNIVERSITY HOSPITAL   (Sweden)

Author keywords

Drug adverse effects; Network analysis; Predictive modeling; System pharmacology

Indexed keywords

BIOLOGICAL PHENOMENA AND FUNCTIONS CONCERNING THE ENTIRE ORGANISM; COMPUTER MODEL; DRUG EFFICACY; DRUG SAFETY; EXPERT SYSTEM; HUMAN; MACHINE LEARNING; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; TOXICOLOGY; ADVERSE DRUG REACTION; BIOLOGY; COMPUTER SIMULATION; DRUG DEVELOPMENT;

DRUG;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DRUG DISCOVERY; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HUMANS; PHARMACEUTICAL PREPARATIONS;

EID: 85012054785     PISSN: 13816128     EISSN: 18734286     Source Type: Journal    
DOI: 10.2174/1381612822666161003115629     Document Type: Review

References (60)

1. Liebler DC, Guengerich FP. Elucidating mechanisms of druginduced toxicity. Nat Rev Drug Discov 2005; 4(5): 410-20
2. Brandt KD, Mazzuca SA. Lessons learned from nine clinical trials of disease-modifying osteoarthritis drugs. USA: Wiley Company 2005; pp. 3349-59
3. Allain H, Bentué-Ferrer D, Akwa Y. Disease-modifying drugs and Parkinson’s disease. Prog Neurobiol 2008; 84: 25-39
4. Salomone S, Caraci F, Leggio GM, Fedotova J, Drago F. New pharmacological strategies for treatment of Alzheimer’s disease: Focus on disease modifying drugs. Br J Clin Pharmacol 2012; 73(4): 504-17
5. Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 2008; 4(11): 682-90
6. Roncaglioni A, Toropov AA, Toropova AP, Benfenati E. 1-s2.0S1471489213000799-main. Curr Opin Pharmacol 2013; 13(5): 802-6
7. Madden CC. In Silico Toxicology — An Introduction. In: Cronin M, Madden J, Eds. In silico toxicology: principles and application. Cambridge: Royal Society of Chemistry 2010; pp. 1-10
8. Pfannkuch F, Suter-Dick L, Brandenburg A. Predictive toxicology : from vision to reality. USA: Wiley-VCH Verlag 2014
9. DS TOPKAT: A Step Beyond SAR Predictive Toxicology in Discovery Studio. Available from: (http://accelrys.com/)
10. Sanderson DM, Earnshaw CG. Computer-prediction of possible toxic action from chemical-structure the derek system. Hum Exp Toxicol 1991; 10(4): 261-73
11. Bhogal N, Grindon C, Combes R, Balls M. Toxicity testing: Creating a revolution based on new technologies. Trends Biotechnol 2005; 23: 299-307
12. US EPA, OCSPP O. A Computer System to Evaluate the Carcinogenic Potential of Chemicals. Available from: (https://www.epa.gov/tsca-screening-tools)
13. Lewis DF, Ioannides C, Parke DV. A prospective toxicity evaluation (COMPACT) on 40 chemicals currently being tested by the National Toxicology Program. Mutagenesis 1990; 5(5): 433-5
14. Li AP. Accurate prediction of human drug toxicity: A major challenge in drug development. Chem-Biol Interact 2004; 150: 3-7
15. Ekins S. Systems-ADME/Tox: Resources and network approaches. J Pharmacol Toxicol Methods 2006; 53: 38-66
16. Ekins S, Nikolsky Y, Nikolskaya T. Techniques: Application of systems biology to absorption, distribution, metabolism, excretion and toxicity. Trends Pharmacol Sci 2005; 26: 202-9
17. Plant NJ, Vinken M, Kolodkin A, Boogerd FC. A. E, Borisy AA. An introduction to systems toxicology. Toxicol Res Royal Soc Chem 2015; 4(1): 9-22
18. Waters M, Fostel J. Toxicogenomics and systems toxicology: aims and prospects. Nat Rev Genet 2004; 5(12): 936-48
19. Valerio LG. In silico toxicology for the pharmaceutical sciences. Toxicol Appl Pharmacol 2009; 241: 356-70
20. Enoch SJ, Cronin MTD, Schultz TW, Madden JC. An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis. Chemosphere 2008; 71(7): 1225-32
21. Piparo E LO, Worth A. Review of QSAR Models and Software Tools for predicting Developmental and Reproductive Toxicity. EUR 24522. JRC Scientific and Technical Reports 2010; Available at: http://publications.jrc.ec.europeau/repository/handle/JRC59820
22. Ren S. Ecotoxicity prediction using mechanismand nonmechanism-based QSARs: A preliminary study. Chemosphere 2003; 53(9): 1053-65
23. Vedani A, Dobler M, Hu Z, Smieko M. OpenVirtualToxLab-A platform for generating and exchanging in silico toxicity data. Toxicol Lett 2015; 232(2): 519-32
24. Sushko I, Salmina E, Potemkin VA, Poda G, Tetko I V. ToxAlerts: A web server of structural alerts for toxic chemicals and compounds with potential adverse reactions. J Chem Inf Mode 2012; 52(8): 2310-6
25. Dearden C.J. In silico prediction of drug toxicity. J Comput aided Mol Des 2003; 17(5): 119-27
26. Maltarollo VG, Gertrudes JC, Oliveira PR, Honorio KM. Applying machine learning techniques for ADME-Tox prediction: a review. Expert Opin Drug Metab Toxicol 2015; 11(2): 259-71
27. Ghanooni M, Mattison DR, Zhang YP, Macina OT, Rosenkranz HS, Klopman G. Structural determinants associated with risk of human developmental toxicity. Am J Obs 1997; 176: 799-805
28. Cruz-Monteagudo M, Cordeiro MNDS, Borges F. Computational chemistry approach for the early detection of drug-induced idiosyncratic liver toxicity. J Comput Chem 2008; 29(4): 533-49
29. Arena VC, Sussman NB, Mazumdar S, Yu S, Macina OT. The utility of structure-activity relationship (SAR) models for prediction and covariate selection in developmental toxicity: comparative analysis of logistic regression and decision tree models. SAR QSAR Environ Res 2004; 15(1): 1-18
30. Chavan S, Friedman R, Nicholls IA. Acute toxicity-supported chronic toxicity prediction: a k-nearest neighbor coupled readacross strategy. Int J Mol Sci 2015; 16(5): 11659-77
31. Labute MX, Zhang X, Lenderman J, Bennion BJ, Wong SE, Lightstone FC. Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines. PLoS One 2014; 9(9): e106298
32. Sturla SJ, Boobis AR, Fitzgerald RE, et al. Systems toxicology: From basic research to risk assessment. Chem Res Toxicol 2014; 27(3): 314-29
33. Handy RD. Systems toxicology: using the systems biology approach to assess chemical pollutants in the environment. Adv Exp Biol 2008; 2: 249-81
34. Pouliot Y, Chiang AP, Butte AJ. Predicting adverse drug reactions using publicly available PubChem BioAssay data. Clin Pharmacol Ther 2011; 90(1): 90-9
35. Iskar M, Zeller G, Zhao XM, van Noort V, Bork P. Drug discovery in the age of systems biology: The rise of computational approaches for data integration. Curr Opin Biotechnol 2012; 23: 609-16
36. Bai JPF, Abernethy DR. Systems pharmacology to predict drug toxicity: integration across levels of biological organization. Annu Rev Pharmacol Toxicol 2013; 53(1): 451-73
37. Rahmani H, Weiss G, Méndez-Lucio O, Bender A. ARWAR: A network approach for predicting Adverse Drug Reactions. Comput Biol Med 2016; 68: 101-8
38. Lounkine E, Keiser MJ, Whitebread S, et al. Large-scale prediction and testing of drug activity on side-effect targets. Nature 2012; 486(7403): 361-7
39. Xie LL, Li J, Xie LL, Bourne PE. Drug discovery using chemical systems biology: Identification of the protein-ligand binding network to explain the side effects of CETP inhibitors. PLoS Comput Biol 2009; 5(5): e1000387
40. Wallach I, Jaitly N, Lilien R. A structure-based approach for mapping adverse drug reactions to the perturbation of underlying biological pathways. PLoS One 2010; 5(8): e12063
41. Scheiber J, Chen B, Milik M, et al. Gaining insight into off-target mediated effects of drug candidates with a comprehensive systems chemical biology analysis. J Chem Inf Model 2009; 49(2): 308-17
42. Atias N, Sharan R. An algorithmic framework for predicting side effects of drugs. J Comput Biol 2011; 18(3): 207-18
43. Cami A, Arnold A, Manzi S, Reis B. Predicting adverse drug events using pharmacological network models. Sci Transl Med 2011; 3(114): 114-27
44. Mizutani S, Pauwels E, Stoven V, Goto S, Yamanishi Y. Relating drug-protein interaction network with drug side effects. Bioinformatics 2012; 28(18): 522-8
45. Gottlieb A, Altman RB. Integrating systems biology sources illuminates drug action. Clin Pharmacol Ther 2014; 95(2): 1-7
46. Fan S, Geng Q, Pan Z, et al. Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach. BMC Syst Biol 2012; 6(38): 152
47. Azuaje FJ, Zhang L, Devaux Y, Wagner DR. Drug-target network in myocardial infarction reveals multiple side effects of unrelated drugs. Sci Rep 2011; 1: 1-10
48. Brouwers L, Iskar M, Zeller G, van Noort V, Bork P. Network neighbors of drug targets contribute to drug side-effect similarity. PLoS One 2011; 6(7): e22187
49. Huang L-C, Wu X, Chen JY. Predicting adverse side effects of drugs. BMC Genomics 2011; 12(Suppl 5): S11
50. Huang J, Niu C, Green CD, Yang L, Mei H, Han JDJ. Systematic prediction of pharmacodynamic drug-drug interactions through protein-protein-interaction network. PLoS Comput Biol 2013; 9(3): e1002998
51. Cobanoglu MC, Liu C, Hu F, Oltvai ZN, Bahar I. Predicting drugtarget interactions using probabilistic matrix factorization. J Chem Inf Model 2013; 53(12): 3399-409
52. Garcia-Serna R, Vidal D, Remez N, Mestres J. Large-scale predictive drug safety: from structural alerts to biological mechanisms. Chem Res Toxicol 2015; 28(10): 1875-87
53. Remez N, Garcia-Serna R, Vidal D, Mestres J. The in vitro pharmacological profile of drugs as a proxy indicator of potential in vivo organ toxicities. Chem Res Toxicol 2016; 29(4): 637-48
54. Kuhn M, Al Banchaabouchi M, Campillos M, et al. Systematic identification of proteins that elicit drug side effects. Mol Syst Biol 2014; 9(1): 663
55. Pauwels E, Stoven V, Yamanishi Y. Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinformatics 2011; 12(1): 169
56. Ivanov SM, Lagunin AA, Poroikov V V. In silico assessment of adverse drug reactions and associated mechanisms. Drug Discov Today 2015; 1: 1-14
57. Boland MR, Jacunski A, Lorberbaum T, Romano JD, Moskovitch R, Tatonetti NP. Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms. Wiley Interdiscip Rev Syst Biol Med 2015; 104-22
58. Wang T, Wu MB, Zhang RH, et al. Advances in Computational Structure-Based Drug Design and Application in Drug Discovery. Curr Top Med Chem 2016; 16(9): 901-16
59. Tegnér JN, Compte A, Auffray C, et al. Computational disease modeling fact or fiction? BMC Syst Biol. BioMed Central 2009; 3(1): 56
60. mez-Cabrero D, Compte A, Tegner J. Workflow for generating competing hypothesis from models with parameter uncertainty. Interf Focus 2011; 1(3): 438-49