Skip to main content
SpringerLink
Log in

Ecotoxicological QSARs of Mixtures

  • Protocol
  • First Online:
Ecotoxicological QSARs

Part of the book series: Methods in Pharmacology and Toxicology ((MIPT))

Abstract

In this era of advanced industrialization, all the living beings and environment are exposed to multicomponent mixtures of different classes of chemicals such as organics, pesticides, heavy metals, and pharmaceuticals which may cause direct or indirect hazards to humans, wildlife, aquatic systems, and ecosystems. The regulatory authorities have mostly relied on the single chemical risk assessment, instead of considering the impact of complex chemical mixtures. It is also well known that toxicity data for the individual components is available for a fraction of all existing chemicals in environment. The condition is much worse as there is minimal toxicity data for complex multicomponent chemical mixtures, and the nature of toxicity of a mixture (synergism and/or antagonism) will be entirely different from the toxicity of the single chemicals. A number of regulatory authorities have proposed several methodologies and guidance for the evaluation of hazardous effects of multicomponent chemical mixtures. However, a standard, significant, and reliable approach for evaluation of toxicity of chemical mixtures and their management across diverse monitoring sectors is lacking. In the present chapter, we have illustrated the basic concepts of mixture toxicity assessment, such as concentration addition, independent action, and interaction (synergism and/or antagonism), as well as focused on the computational approaches, such as quantitative structure-activity relationship (QSAR), which is already proven as an efficient alternative method for toxicity prediction of chemicals by regulatory authorities for decision making. Subsequently, we have also provided a brief detail on several ongoing research projects in the European Union (EU), funded by the current European Research and Innovation Programme Horizon 2020 or the Seventh Framework Programme for mixture toxicity prediction. The present chapter also explains the importance of evaluation of chemical mixture toxicity and essential steps in basic QSAR modelling in the context of mixtures. Additionally, we have reported the successful application of QSAR in the prediction of mixture toxicity of different classes of chemicals such as pharmaceuticals, pesticides, metals, and organic industrial chemicals.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Evans RM, Martin OV, Faust M, Kortenkamp A (2016) Should the scope of human mixture risk assessment span legislative/regulatory silos for chemicals? Sci Total Environ 543:757–764

    Article  CAS  PubMed  Google Scholar 

  2. Commission, EE (2012) Communication from the Commission to the Council the combination effects of chemicals. Chem Mix Com 10

    Google Scholar 

  3. EPA, U (2007) Concepts, methods, and data sources for cumulative health risk assessment of multiple chemicals, exposures and effects: a resource document (final report). US Environmental Protection Agency, Washington, D.C.; EPA/600/R-06: 2007

    Google Scholar 

  4. Pohl HR, Mumtaz M, McClure PR, Colman J, Zaccaria K, Melia J, Ingerman L (2018) Framework for assessing health impacts of multiple chemicals and other stressors. CDC stack public health publication, Atlanta, USA

    Google Scholar 

  5. Meek M, Boobis AR, Crofton KM, Heinemeyer G, Van Raaij M, Vickers C (2011) Risk assessment of combined exposure to multiple chemicals: a WHO/IPCS framework. Regul Toxicol Pharmacol 60:S1–S14

    CAS  Google Scholar 

  6. EFSA, EFSA (2008) Opinion of the Scientific Panel on Plant Protection products and their Residues to evaluate the suitability of existing methodologies and, if appropriate, the identification of new approaches to assess cumulative and synergistic risks from pesticides to human health with a view to set MRLs for those pesticides in the frame of Regulation (EC) 396/2005. EFSA J 6:705

    Article  Google Scholar 

  7. Scher S (2012) Opinion on the toxicity and assessment of chemical mixtures. Scientific Committees on Health and Environmental Risks (SCHER), Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR) European Commission, Brussels

    Google Scholar 

  8. Bopp SK, Barouki R, Brack W, Dalla Costa S, Dorne J-LC, Drakvik PE, Faust M, Karjalainen TK, Kephalopoulos S, van Klaveren J (2018) Current EU research activities on combined exposure to multiple chemicals. Environ Int 120:544–562

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. EDC-MixRisk (2019) https://edcmixrisk.ki.se/

  10. HBM4EU (2019) https://www.hbm4eu.eu/

  11. SOLUTIONS (2019) https://www.solutions-project.eu/project/

  12. EuroMix (2019) https://www.euromixproject.eu/

  13. EUToxRisk (2019) http://www.eu-toxrisk.eu/

  14. Yang R, Thomas RS, Gustafson DL, Campain J, Benjamin SA, Verhaar H, Mumtaz MM (1998) Approaches to developing alternative and predictive toxicology based on PBPK/PD and QSAR modeling. Environ Health Perspect 106:1385–1393

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Martens M, Mosselmans G, Fumero S, Jacobs G, Lafontaine A (1984) Some thoughts on a possible regulatory approach at EEC level on the classification and labeling of dangerous preparations. Regul Toxicol Pharmacol 4:145–156

    Article  CAS  PubMed  Google Scholar 

  16. Logan DT, Wilson HT (1995) An ecological risk assessment method for species exposed to contaminant mixtures. Environ Toxicol Chem An Inter J 14:351–359

    Article  CAS  Google Scholar 

  17. europea, UeC (1996) Technical guidance document in support of commission directive 93/67/EEC on risk assessment for new notified substances and commission regulation (EC) N. 1488/94 on risk assessment for existing substances. Office for official publications of the European communities: 1996. European Commission, Brussels

    Google Scholar 

  18. OPP, EPA (2000) Proposed guidance on cumulative risk assessment of pesticide chemicals that have a common mechanism of Toxicity, US EPA, Washington DC

    Google Scholar 

  19. Greco WR, Bravo G, Parsons JC (1995) The search for synergy: a critical review from a response surface perspective. Pharmacol Rev 47:331–385

    CAS  PubMed  Google Scholar 

  20. Altenburger R, Boedeker W, Faust M, Grimme LH (1993) Aquatic toxicology, analysis of combination effects. In: Handbook of hazardous materials. Academic Press, San Diego, pp 15–27

    Chapter  Google Scholar 

  21. Kortenkamp A, Altenburger R (1998) Synergisms with mixtures of xenoestrogens: a reevaluation using the method of isoboles. Sci Total Environ 221:59–73

    Article  CAS  PubMed  Google Scholar 

  22. Bödeker W, Altenburger R, Faust M, Grimme L (1990) Methods for the assessment of mixtures of plant protection substances (pesticides): mathematical analysis of combination effects in phytopharmacology and ecotoxicology. Nachr bl Dtsch Pflanzenschutzd 42:70–78

    Google Scholar 

  23. Schmähl D (1980) Combination effects in chemical carcinogenesis. In: Further studies in the assessment of toxic actions. Springer, Berlin, pp 29–40

    Chapter  Google Scholar 

  24. Monosson E (2004) Chemical mixtures: considering the evolution of toxicology and chemical assessment. Environ Health Perspect 113:383–390

    Article  PubMed Central  CAS  Google Scholar 

  25. Teuschler LK, Hertzberg RC (1995) Current and future risk assessment guidelines, policy, and methods development for chemical mixtures. Toxicology 105:137–144

    Article  CAS  PubMed  Google Scholar 

  26. Altenburger R, Backhaus T, Boedeker W, Faust M, Scholze M, Grimme LH (2000) Predictability of the toxicity of multiple chemical mixtures to Vibrio fischeri: mixtures composed of similarly acting chemicals. Environ Toxicol Chem An Inter J 19:2341–2347

    Article  CAS  Google Scholar 

  27. Hayes AW (2007) Principles and methods of toxicology. Crc Press

    Google Scholar 

  28. Kar S, Leszczynski J (2019) Exploration of computational approaches to predict the toxicity of chemical mixtures. Toxics 7:15

    Article  CAS  PubMed Central  Google Scholar 

  29. Borzelleca JF (2001) The art, the science, and the seduction of toxicology: an evolutionary development. Principles and methods of toxicology

    Google Scholar 

  30. Brack W, Ait-Aissa S, Burgess RM, Busch W, Creusot N, Di Paolo C, Escher BI, Hewitt LM, Hilscherova K, Hollender J (2016) Effect-directed analysis supporting monitoring of aquatic environments—an in-depth overview. Sci Total Environ 544:1073–1118

    Article  CAS  PubMed  Google Scholar 

  31. Groten JP, Feron VJ, Sühnel J (2001) Toxicology of simple and complex mixtures. Trends Pharmacol Sci 22:316–322

    Article  CAS  PubMed  Google Scholar 

  32. Scher S (2011) SCCS toxicity and assessment of chemical mixtures (pp 1–50), European commission, Brussels

    Google Scholar 

  33. Kortenkamp A, Backhaus T, Faust M (2007) State of the art report on mixture toxicity. Final Report to the European Commission under Contract Number 070307, The School of Pharmacy, University of London, London

    Google Scholar 

  34. Kienzler A, Berggren E, Bessems J, Bopp S, van der Linden, S, Worth A (2014) Assessment of mixtures-review of regulatory requirements and guidance. Joint Research Centre, Science and Policy Reports. European Commission, Luxembourg

    Google Scholar 

  35. Loewe S, Muischnek H (1926) Über kombinationswirkungen. Naunyn Schmiedeberg’s Arch Pharmacol 114:313–326

    Article  CAS  Google Scholar 

  36. Loewe S (1953) The problem of synergism and antagonism of combined drugs. Arzneim Forsch 3:285–290

    CAS  Google Scholar 

  37. Berenbaum MC (1985) The expected effect of a combination of agents: the general solution. J Theor Biol 114:413–431

    Article  CAS  PubMed  Google Scholar 

  38. Backhaus T, Sumpter J, Blanck H (2008) On the ecotoxicology of pharmaceutical mixtures. In: Pharmaceuticals in the environment. Springer, Berlin, Heidelberg, pp 257–276

    Chapter  Google Scholar 

  39. Cedergreen N (2014) Quantifying synergy: a systematic review of mixture toxicity studies within environmental toxicology. PLoS One 9:e96580

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Rodea-Palomares I, González-Pleiter M, Martín-Betancor K, Rosal R, Fernández-Piñas F (2015) Additivity and interactions in ecotoxicity of pollutant mixtures: some patterns, conclusions, and open questions. Toxics 3:342–369

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bliss C (1939) The toxicity of poisons applied jointly 1. Annu Appl Biol 26:585–615

    Article  CAS  Google Scholar 

  42. Faust M, Altenburger R, Backhaus T, Blanck H, Boedeker W, Gramatica P, Hamer V, Scholze M, Vighi M, Grimme L (2003) Joint algal toxicity of 16 dissimilarly acting chemicals is predictable by the concept of independent action. Aquat Toxicol 63:43–63

    Article  CAS  PubMed  Google Scholar 

  43. Backhaus T, Altenburger R, Boedeker W, Faust M, Scholze M, Grimme LH (2000) Predictability of the toxicity of a multiple mixture of dissimilarly acting chemicals to Vibrio fischeri. Environ Toxico Chem An Inter J 19:2348–2356

    Article  CAS  Google Scholar 

  44. De Zwart D, Posthuma L (2005) Complex mixture toxicity for single and multiple species: proposed methodologies. Environ Toxic Chem An Inter J 24:2665–2676

    Article  Google Scholar 

  45. Suter G (2009) Extrapolation practice for ecotoxicological effect characterization of chemicals. Integr Environ Assess Manag 5:358

    Article  Google Scholar 

  46. Posthuma L, Vijver M (2007) Exposure and ecological effects of toxic mixtures at field-relevant concentrations. Model validation and integration of the SSEO programme RIVM report, 860706002/2007

    Google Scholar 

  47. Ragas AM, Teuschler LK, Posthuma L, Cowan CE (2011) Human and ecological risk assessment of chemical mixtures. In: Mixture toxicity: linking approaches from ecological and human toxicology. CRC-Press, New York, pp 157–212

    Google Scholar 

  48. Jonker M, van Gestel CA, Kammenga JE, Laskowski R, Svendsen C (2016) Mixture toxicity: linking approaches from ecological and human toxicology. CRC press, New York

    Google Scholar 

  49. Backhaus T, Faust M (2012) Predictive environmental risk assessment of chemical mixtures: a conceptual framework. Environ Sci Technol 46:2564–2573

    Article  CAS  PubMed  Google Scholar 

  50. Howard GJ, Webster TF (2009) Generalized concentration addition: a method for examining mixtures containing partial agonists. J Theor Biol 259:469–477

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hadrup N, Taxvig C, Pedersen M, Nellemann C, Hass U, Vinggaard AM (2013) Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro. PLoS One 8:e70490

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. EC (2009) EC, State of the art report on mixture toxicity. European Union

    Google Scholar 

  53. Faust M, Altenburger R, Boedeker W, Grimme L (1994) Algal toxicity of binary combinations of pesticides. Bull Environ Contam Toxicol 53:134–141

    Article  CAS  PubMed  Google Scholar 

  54. Backhaus T, Faust M, Scholze M, Gramatica P, Vighi M, Grimme LH (2004) Joint algal toxicity of phenylurea herbicides is equally predictable by concentration addition and independent action. Environ Toxic Chem An Inter J 23:258–264

    Article  CAS  Google Scholar 

  55. Cedergreen N, Christensen AM, Kamper A, Kudsk P, Mathiassen SK, Streibig JC, Sørensen H (2008) A review of independent action compared to concentration addition as reference models for mixtures of compounds with different molecular target sites. Environ Toxic Chem An Inter J 27:1621–1632

    Article  CAS  Google Scholar 

  56. Belden JB, Gilliom RJ, Lydy MJ (2007) How well can we predict the toxicity of pesticide mixtures to aquatic life? Integr Environ Assess Manag 3:364–372

    Article  CAS  PubMed  Google Scholar 

  57. Norwood W, Borgmann U, Dixon D, Wallace A (2003) Effects of metal mixtures on aquatic biota: a review of observations and methods. Hum Ecol Risk Assess 9:795–811

    Article  CAS  Google Scholar 

  58. Kümmerer K (2008) Pharmaceuticals in the environment: sources, fate, effects and risks. Springer Science & Business Media, Berlin

    Book  Google Scholar 

  59. Warne MSJ (2003) In A review of the ecotoxicity of mixtures, approaches to, and recommendations for, their management. Proceedings of the fifth national workshop on the assessment of site contamination, National Environmental Protection Council Service Corporation, Adelaide, pp 253–276

    Google Scholar 

  60. Faust M, Altenburger R, Backhaus T, Blanck H, Boedeker W, Gramatica P, Hamer V, Scholze M, Vighi M, Grimme L (2001) Predicting the joint algal toxicity of multi-component s-triazine mixtures at low-effect concentrations of individual toxicants. Aquat Toxicol 56:13–32

    Article  CAS  PubMed  Google Scholar 

  61. Parvez S, Venkataraman C, Mukherji S (2009) Nature and prevalence of non-additive toxic effects in industrially relevant mixtures of organic chemicals. Chemosphere 75:1429–1439

    Article  CAS  PubMed  Google Scholar 

  62. Solomon KR, Brock TC, De Zwart D, Dyer SD, Posthuma L, Richards S, Sanderson H, Sibley P, van den Brink PJ (2008) Extrapolation practice for ecotoxicological effect characterization of chemicals. CRC Press, New York

    Google Scholar 

  63. Posthuma L, Suter GW II, Traas TP (2001) Species sensitivity distributions in ecotoxicology. CRC Press, New York

    Google Scholar 

  64. Baas J, Jager T, Kooijman B (2010) A review of DEB theory in assessing toxic effects of mixtures. Sci Total Environ 408:3740–3745

    Article  CAS  PubMed  Google Scholar 

  65. Dyer S, Warne MSJ, Meyer JS, Leslie HA, Escher BI (2011) Tissue residue approach for chemical mixtures. Integr Environ Assess Manag 7:99–115

    Article  CAS  PubMed  Google Scholar 

  66. Raies AB, Bajic VB (2016) In silico toxicology: computational methods for the prediction of chemical toxicity. Wiley Interdiscip Rev Comput Mol Sci 6:147–172

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Muratov EN, Varlamova EV, Artemenko AG, Polishchuk PG, Kuz'min VE (2012) Existing and developing approaches for QSAR analysis of mixtures. Mol Inform 31:202–221

    Article  CAS  PubMed  Google Scholar 

  68. Roy K, Kar S, Das RN (2015) A primer on QSAR/QSPR modeling: fundamental concepts. Springer, Cham

    Book  Google Scholar 

  69. Khan PM, Rasulev B, Roy K (2017) Chemometric modeling of refractive index of polymers using 2D descriptors: a QSPR approach. Comput Mater Sci 137:215–224

    Article  CAS  Google Scholar 

  70. Khan PM, Roy K, Benfenati E (2019) Chemometric modeling of Daphnia magna toxicity of agrochemicals. Chemosphere 224:470–479

    Article  CAS  PubMed  Google Scholar 

  71. Khan PM, Roy K (2018) QSPR modelling for prediction of glass transition temperature of diverse polymers. SAR QSAR Environ Res 29:935–956

    Article  CAS  PubMed  Google Scholar 

  72. Oecd (2007) Guidance document on the validation of (quantitative) structure activity relationship [(Q) SAR] models. Organisation for Economic Co-operation and Development Paris, France

    Google Scholar 

  73. Tropsha A (2012) Best practices for QSAR model development, validation, and exploitation. Mol Inform 29:476–488

    Article  CAS  Google Scholar 

  74. Roy K, Das RN, Ambure P, Aher RB (2016) Be aware of error measures. Further studies on validation of predictive QSAR models. Chemom Intell Lab Syst 152:18–33

    Article  CAS  Google Scholar 

  75. Roy K, Kar S, Das RN (2015) Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment. Academic press, London

    Google Scholar 

  76. Golbraikh A, Tropsha A (2002) Beware of q2! J Mol Graph Model 20:269–276

    Article  CAS  PubMed  Google Scholar 

  77. Yasri A, Hartsough D (2001) Toward an optimal procedure for variable selection and QSAR model building. J Chem Inf Comput Sci 41:1218–1227

    Article  CAS  PubMed  Google Scholar 

  78. Shahlaei M (2013) Descriptor selection methods in quantitative structure-activity relationship studies: a review study. Chem Rev 113:8093–8103

    Article  CAS  PubMed  Google Scholar 

  79. Cherkasov A, Muratov EN, Fourches D, Varnek A, Baskin II, Cronin M, Dearden J, Gramatica P, Martin YC, Todeschini R (2014) QSAR modeling: where have you been? Where are you going to? J Med Chem 57:4977–5010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Fourches D, Pu D, Tassa C, Weissleder R, Shaw SY, Mumper RJ, Tropsha A (2010) Quantitative nanostructure- activity relationship modeling. ACS Nano 4:5703–5712

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Yap CW (2011) PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints. J Comput Chem 32:1466–1474

    Article  CAS  PubMed  Google Scholar 

  82. Mauri A, Consonni V, Pavan M, Todeschini R (2006) Dragon software: an easy approach to molecular descriptor calculations. Match 56:237–248

    CAS  Google Scholar 

  83. Alvadesc (2019) https://www.alvascience.com/alvadesc/

  84. Khan PM, Rasulev B, Roy K (2018) QSPR modeling of the refractive index for diverse polymers using 2D descriptors. ACS Omega 3:13374–13386

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Rasulev B, Jabeen F, Stafslien S, Chisholm BJ, Bahr J, Ossowski M, Boudjouk P (2017) Polymer coating materials and their fouling release activity: a cheminformatics approach to predict properties. ACS Appl Mater Interfaces 9:1781–1792

    Article  CAS  PubMed  Google Scholar 

  86. Khan PM, Roy K (2018) Current approaches for choosing feature selection and learning algorithms in quantitative structure activity relationships (QSAR). Expert Opin Drug Discov 13:1075–1089

    Article  CAS  PubMed  Google Scholar 

  87. Roy K, Kar S (2016) In silico models for ecotoxicity of pharmaceuticals. In: In silico methods for predicting drug toxicity. Springer, NY, pp 237–304

    Google Scholar 

  88. Halling-Sørensen B, Nielsen SN, Lanzky PF, Ingerslev F, Lützhøft HCH, Jørgensen SE (1998) Occurrence, fate and effects of pharmaceutical substances in the environment-a review. Chemosphere 36:357–393

    Article  PubMed  Google Scholar 

  89. Białk-Bielińska A, Caban M, Pieczyńska A, Stepnowski P, Stolte S (2017) Mixture toxicity of six sulfonamides and their two transformation products to green algae Scenedesmus vacuolatus and duckweed Lemna minor. Chemosphere 173:542–550

    Article  PubMed  CAS  Google Scholar 

  90. Zou X, Zhou X, Lin Z, Deng Z, Yin D (2013) A docking-based receptor library of antibiotics and its novel application in predicting chronic mixture toxicity for environmental risk assessment. Environ Monit Assess 185:4513–4527

    Article  CAS  PubMed  Google Scholar 

  91. Zou X, Lin Z, Deng Z, Yin D, Zhang Y (2012) The joint effects of sulfonamides and their potentiator on Photobacterium phosphoreum: differences between the acute and chronic mixture toxicity mechanisms. Chemosphere 86:30–35

    Article  CAS  PubMed  Google Scholar 

  92. Long X, Wang D, Lin Z, Qin M, Song C, Liu Y (2016) The mixture toxicity of environmental contaminants containing sulfonamides and other antibiotics in Escherichia coli: differences in both the special target proteins of individual chemicals and their effective combined concentration. Chemosphere 158:193–203

    Article  CAS  PubMed  Google Scholar 

  93. Wang D, Shi J, Xiong Y, Hu J, Lin Z, Qiu Y, Cheng J (2018) A QSAR-based mechanistic study on the combined toxicity of antibiotics and quorum sensing inhibitors against Escherichia coli. J Hazard Mater 341:438–447

    Article  PubMed  CAS  Google Scholar 

  94. Wang D, Wu X, Lin Z, Ding Y (2018) A comparative study on the binary and ternary mixture toxicity of antibiotics towards three bacteria based on QSAR investigation. Environ Res 162:127–134

    Article  CAS  PubMed  Google Scholar 

  95. Cleuvers M (2004) Mixture toxicity of the anti-inflammatory drugs diclofenac, ibuprofen, naproxen, and acetylsalicylic acid. Ecotoxicol Environ Saf 59:309–315

    Article  CAS  PubMed  Google Scholar 

  96. Verhaar HJM, Van Leeuwen CJ, Hermens JLM (1992) Classifying environmental pollutants. Chemosphere 25:471–491

    Article  CAS  Google Scholar 

  97. Van Leeuwen CJ, Van Der Zandt PTJ, Aldenberg T, Verhaar HJM, Hermens JLM (1992) Application of QSARs, extrapolation and equilibrium partitioning in aquatic effects assessment. I. Narcotic industrial pollutants. Environ Toxicol Chem 11:267–282

    Article  Google Scholar 

  98. Escher BI, Bramaz N, Richter M, Lienert J (2006) Comparative ecotoxicological hazard assessment of beta-blockers and their human metabolites using a mode-of-action-based test battery and a QSAR approach. Environ Sci Technol 40:7402–7408

    Article  CAS  PubMed  Google Scholar 

  99. Lienert J, Güdel K, Escher BI (2007) Screening method for ecotoxicological hazard assessment of 42 pharmaceuticals considering human metabolism and excretory routes. Environ Sci Technol 41:4471–4478

    Article  CAS  PubMed  Google Scholar 

  100. De García SAO, Pinto GP, García-Encina PA, Irusta-Mata R (2014) Ecotoxicity and environmental risk assessment of pharmaceuticals and personal care products in aquatic environments and wastewater treatment plants. Ecotoxicology 23:1517–1533

    Article  CAS  Google Scholar 

  101. Mahmoud WMM, Toolaram AP, Menz J, Leder C, Schneider M, Kümmerer K (2014) Identification of phototransformation products of thalidomide and mixture toxicity assessment: an experimental and quantitative structural activity relationships (QSAR) approach. Water Res 49:11–22

    Article  CAS  PubMed  Google Scholar 

  102. Villa S, Vighi M, Finizio A (2014) Experimental and predicted acute toxicity of antibacterial compounds and their mixtures using the luminescent bacterium Vibrio fischeri. Chemosphere 108:239–244

    Article  CAS  PubMed  Google Scholar 

  103. Hernández AF, Parrón T, Tsatsakis AM, Requena M, Alarcón R, Olga López O (2013) Toxic effects of pesticide mixtures at a molecular level: their relevance to human health. Toxicology 307:136–145

    Article  PubMed  CAS  Google Scholar 

  104. Tsatsakis AM, Zafiropoulos A, Tzatzarakis MN, Tzanakakis GN, Kafatos A (2009) Relation of PON1 and CYP1A1 genetic polymorphisms to clinical findings in a cross-sectional study of a Greek rural population professionally exposed to pesticides. Toxicol Lett 186:66–72

    Article  CAS  PubMed  Google Scholar 

  105. Zeliger H (2011) Human toxicology of chemical mixtures. William Andrew, NY

    Chapter  Google Scholar 

  106. Arnold SF, Klotz DM, Collins BM, Vonier PM, Guillette LJ, McLachlan JA (1996) Synergistic activation of estrogen receptor with combinations of environmental chemicals. Science 272:1489–1492

    Article  CAS  PubMed  Google Scholar 

  107. Liu S-S, Song X-Q, Liu H-L, Zhang Y-H, Zhang J (2009) Combined photobacterium toxicity of herbicide mixtures containing one insecticide. Chemosphere 75:381–388

    Article  CAS  PubMed  Google Scholar 

  108. Gutowski L, Baginska E, Olsson O, Leder C, Kümmerer K (2015) Assessing the environmental fate of S-metolachlor, its commercial product Mercantor Gold® and their photoproducts using a water-sediment test and in silico methods. Chemosphere 138:847–855

    Article  CAS  PubMed  Google Scholar 

  109. Jansen E, Michels M, Van Til M, Doelman P (1994) Effects of heavy metals in soil on microbial diversity and activity as shown by the sensitivity-resistance index, an ecologically relevant parameter. Biol Fertil Soils 17:177–184

    Article  Google Scholar 

  110. Nweke CO, Umeh SI, Ohale VK (2018) Toxicity of four metals and their mixtures to Pseudomonas fluorescens: an assessment using fixed ratio ray design. Ecotox Environ Contam Toxicol 13:1–14

    Google Scholar 

  111. Gikas P (2008) Single and combined effects of nickel (Ni (II)) and cobalt (Co (II)) ions on activated sludge and on other aerobic microorganisms: a review. J Hazard Mater 159:187–203

    Article  CAS  PubMed  Google Scholar 

  112. Su L-m, Xing Y, Mu C-f, Yan J-c, Zhao Y-h (2008) Evaluation and QSAR study of joint toxicity of substituted phenols and cadmium to Photobacterium phosphoreum. Chem Res Chinese U 24:281–284

    Article  CAS  Google Scholar 

  113. Su L, Zhang X, Yuan X, Zhao Y, Zhang D, Qin W (2012) Evaluation of joint toxicity of nitroaromatic compounds and copper to Photobacterium phosphoreum and QSAR analysis. J Hazard Mater 241:450–455

    Article  PubMed  CAS  Google Scholar 

  114. Aggerbeck M, Blanc EB (2018) Role of mixtures of organic pollutants in the development of metabolic disorders via the activation of xenosensors. Curr Opin Toxicol 8:57–65

    Article  Google Scholar 

  115. Lu GH, Wang C, Wang PF, Chen ZY (2009) Joint toxicity evaluation and QSAR modeling of aromatic amines and phenols to bacteria. Bull Environ Contam Toxicol 83:8–14

    Article  CAS  PubMed  Google Scholar 

  116. Zeng M, Lin Z, Yin D, Yin K (2008) QSAR for predicting joint toxicity of halogenated benzenes to Dicrateria zhanjiangensis. Bull Environ Contam Toxicol 81:525–530

    Article  CAS  PubMed  Google Scholar 

  117. Wang B, Yu G, Zhang Z, Hu H, Wang L (2006) Quantitative structure-activity relationship and prediction of mixture toxicity of alkanols. Chin Sci Bull 51:2717–2723

    Article  CAS  Google Scholar 

  118. Chen CY, Chen SL, Christensen ER (2005) Individual and combined toxicity of nitriles and aldehydes to Raphidocelis subcapitata. Environ Toxicol Chem 24:1067–1073

    Article  CAS  PubMed  Google Scholar 

  119. Lin Z, Niu X, Wu C, Yin K, Cai Z (2005) Prediction of the toxicological joint effects between cyanogenic toxicants and aldehydes to Photobacterium phosphoreum. QSAR Comb Sci 24:354–363

    Article  CAS  Google Scholar 

  120. Huang H, Wang X, Shao Y, Chen D, Dai X, Wang L (2003) QSAR for prediction of joint toxicity of substituted phenols to tadpoles (Rana japonica). Bull Environ Contam Toxicol 71:1124–1130

    CAS  PubMed  Google Scholar 

  121. Altenburger R, Schmitt H, Schüürmann G (2005) Algal toxicity of nitrobenzenes: combined effect analysis as a pharmacological probe for similar modes of interaction. Environ Toxic Chem An Inter J 24:324–333

    Article  CAS  Google Scholar 

  122. Pohl HR, Ruiz P, Scinicariello F, Mumtaz MM (2012) Joint toxicity of alkoxyethanol mixtures: contribution of in silico applications. Regul Toxicol Pharmacol 64:134–142

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Jin H, Wang C, Shi J, Chen L (2014) Evaluation on joint toxicity of chlorinated anilines and cadmium to Photobacterium phosphoreum and QSAR analysis. J Hazard Mater 279:156–162

    Article  CAS  PubMed  Google Scholar 

  124. Swartz RC, Schults DW, Ozretich RJ, Lamberson JO, Cole FA, Ferraro SP, Dewitt TH, Redmond MS (1995) ΣPAH: a model to predict the toxicity of polynuclear aromatic hydrocarbon mixtures in field-collected sediments. Environ Toxicol Chem 14:1977–1987

    Article  CAS  Google Scholar 

  125. Choi K, Sweet LI, Meier PG, Kim P-G (2004) Aquatic toxicity of four alkylphenols (3-tert-butylphenol, 2-isopropylphenol, 3-isopropylphenol, and 4-isopropylphenol) and their binary mixtures to microbes, invertebrates, and fish. Environ Toxicol 19:45–50

    Article  CAS  PubMed  Google Scholar 

  126. Wang T, Lin Z, Yin D, Tian D, Zhang Y, Kong D (2011) Hydrophobicity-dependent QSARs to predict the toxicity of perfluorinated carboxylic acids and their mixtures. Environ Toxicol Pharmacol 32:259–265

    Article  PubMed  CAS  Google Scholar 

  127. Hoover G, Kar S, Guffey S, Leszczynski J, Sepúlveda MS (2019) In vitro and in silico modeling of perfluoroalkyl substances mixture toxicity in an amphibian fibroblast cell line. Chemosphere 233:25–33

    Article  CAS  PubMed  Google Scholar 

  128. Kar S, Ghosh S, Leszczynski J (2018) Single or mixture halogenated chemicals? Risk assessment and developmental toxicity prediction on zebrafish embryos based on weighted descriptors approach. Chemosphere 210:588–596

    Article  CAS  PubMed  Google Scholar 

  129. Bucher JR, Lucier G (1998) Current approaches toward chemical mixture studies at the National Institute of Environmental Health Sciences and the US National Toxicology Program. Environ Health Perspect 106:1295–1298

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Pharmacoinformatics, National Institute of Pharmaceutical Educational and Research (NIPER), Kolkata, India

    Pathan Mohsin Khan

  2. Interdisciplinary Center for Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS, USA

    Supratik Kar

  3. Drug Theoretics and Cheminformatics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

    Kunal Roy

Authors
  1. Pathan Mohsin Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Supratik Kar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kunal Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kunal Roy .

Editor information

Editors and Affiliations

  1. Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

    Kunal Roy

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Khan, P.M., Kar, S., Roy, K. (2020). Ecotoxicological QSARs of Mixtures. In: Roy, K. (eds) Ecotoxicological QSARs. Methods in Pharmacology and Toxicology. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0150-1_19

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-0150-1_19

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0149-5

  • Online ISBN: 978-1-0716-0150-1

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation