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Ecotoxicological QSARs pp 513–544Cite as

Ecotoxicological QSAR Modeling of Organophosphorus and Neonicotinoid Pesticides

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

Abstract

Organophosphorus and neonicotinoid pesticides are important agrochemicals used worldwide. The beginning of the quantitative structure-activity/toxicity relationship (QSAR/QSTR) field, after the 1960s, is related to the study of the organophosphorus pesticide activity. QSARs have been recognized as an important research direction in the field of medicinal, analytical chemistry, toxicology, pharmaceutical, and environmental chemistry. The main aim of QSAR/QSTR models is to find reliable relationships between the biological activity/toxicity and the experimental or theoretical compound molecular descriptors, to design new structures with improved target properties and safety profile. In this chapter, successful QSAR models are presented for the ecotoxicological data of organophosphorus and neonicotinoid pesticides. In particular, QSAR models for organophosphorus aquatic and terrestrial organism ecotoxicity; for the neonicotinoid toxicity against the honeybees, Musca domestica L., American cockroach, and aphids (Aphis craccivora and Myzus persicae); and for the inhibition ability of acetylcholinesterase and other enzymes by organophosphorus pesticides are presented. The literature data indicate a large variety of QSAR approaches employed in these published studies. In case of organophosphorus pesticides, many available ecotoxicity data for human beings and animals were employed in the computational studies. For the neonicotinoid pesticides a limited number of QSAR models were reported, especially due to the lack of the degradability and aquatic organism toxicity data. The ligand-based combined with structure-based approaches remain a powerful tool in the design of new environment-friendly and less toxic organophosphorus and neonicotinoid pesticides.

Authors “Alina Bora, Luminita Crisan and Ana Borota” are contributed equally to this work.

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References

  1. Hansch C, Maloney PP, Fujita T, Muir RM (1962) Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 194:178–180

    Article  CAS  Google Scholar 

  2. Hansch C, Fujita T (1964) p-σ-π analysis. A method for the correlation of biological activity and chemical structure. J Am Chem Soc 86:1616–1626

    Article  CAS  Google Scholar 

  3. Pope CN (1999) Organophosphorus pesticides: do they all have the same mechanism of toxicity? J Toxicol Environ Health B Crit Rev 2:161–181

    Article  CAS  PubMed  Google Scholar 

  4. Gavrilescu M (2005) Fate of pesticides in the environment and its bioremediation. Eng Life Sci 5:497–526

    Article  CAS  Google Scholar 

  5. Coppage DL, Bradeich E (1976) River pollution by anti-cholinesterase agent. Water Res 10:19–24

    Article  CAS  Google Scholar 

  6. Kumar SK (2000) Biological basis of assessment of ecotoxicology of pesticides on soil organisms. Dissertation master’s thesis, Centre for Environment Jawaharlal Nehru Technological University, Hyderabad

    Google Scholar 

  7. Vermeire T, McPhail R, Waters M (2003) Integrated human and ecological risk assessment: a case study of organophosphorous pesticides in the environment. Hum Ecol Risk Assess 9:343–357

    Article  CAS  Google Scholar 

  8. Morifusa E (1979) Organophosphorus pesticides: organic and biological chemistry. CRC Press, Boca Raton

    Google Scholar 

  9. Marrs TC (1993) Organophosphate poisoning. Pharmacol Ther 58:51–66

    Article  CAS  PubMed  Google Scholar 

  10. Gupta RC (2006) Classification and uses of organophosphates and carbamates. In: Gupta RC (ed) Toxicology of organophosphate & carbamate compounds. Elsevier, Amsterdam

    Google Scholar 

  11. Bajgar J (2004) Organophosphates/nerve agent poisoning: mechanism of action, diagnosis, prophylaxis, and treatment. Adv Clin Chem 38:151–216

    Article  CAS  PubMed  Google Scholar 

  12. Elersek T, Filipic M (2011) Organophosphorous pesticides - mechanisms of their toxicity. In: Stoytcheva M (ed) Pesticides – the impacts of pesticides exposure. IntechOpen, London

    Google Scholar 

  13. Boublik Y, Saint-Aguet P, Lougarre A et al (2002) Acetylcholinesterase engineering for detection of insecticide residues. Protein Eng Des Sel 15:43–50

    Article  CAS  Google Scholar 

  14. Curtil C, Masson P (1993) Aging of cholinesterase after inhibition by organophosphates. Ann Pharm Fr 51:63–77

    CAS  PubMed  Google Scholar 

  15. Aldridge WN, Reiner E (1972) Acylated amino acids in inhibited B-esterases. In: Neuberger A, Tatum EL (eds) Enzyme inhibitors as substrates. North-Holland Publishing Company, Amsterdam

    Google Scholar 

  16. IUPAC. Compendium of Chemical Terminology, 2nd ed. (the “Gold Book”). Compiled by A. D. McNaught and A. Wilkinson. Blackwell Scientific Publications, Oxford (1997). XML on-line corrected version: http://goldbook.iupac.org (2006) created by Nic M, Jirat J, Kosata B; updates compiled by A. Jenkins. ISBN 0-9678550-9-8. https://doi.org/10.1351/goldbook. Last update: 2014-02-24; version: 2.3.3. https://doi.org/10.1351/goldbook.AT06800

  17. Nauen R, Denholm I (2005) Resistance of insect pests to neonicotinoid insecticides: current status and future prospects. Arch Insect Biochem Physiol 58:200–215

    Article  CAS  PubMed  Google Scholar 

  18. Jeschke P, Nauen R, Schindler M, Elbert A (2011) Overview of the status and global strategy for neonicotinoids. J Agric Food Chem 59:2897–2908

    Article  CAS  PubMed  Google Scholar 

  19. Casida JE, Durkin KA (2013) Neuroactive insecticides: targets, selectivity, resistance, and secondary effects. Annu Rev Entomol 58:99–117

    Article  CAS  PubMed  Google Scholar 

  20. Bonmatin JM, Giorio C, Girolami V et al (2015) Environmental fate and exposure; neonicotinoids and fipronil. Environ Sci Pollut Res 22:35–67

    Article  CAS  Google Scholar 

  21. Shao X, Liu Z, Xu X, Li Z, Qian X (2013) Overall status of neonicotinoid insecticides in China: production, application and innovation. J Pestic Sci 38:1–9

    Article  CAS  Google Scholar 

  22. Jeschke P, Nauen R (2008) Neonicotinoids – from zero to hero insecticide chemistry. Pest Manag Sci 64:1084–1098

    Article  CAS  PubMed  Google Scholar 

  23. Casida JE (2018) Neonicotinoids and other insect nicotinic receptor competitive modulators: progress and prospects. Annu Rev Entomol 63:125–144

    Article  CAS  PubMed  Google Scholar 

  24. Elbert A, Haas M, Springer B et al (2008) Applied aspects of neonicotinoid uses in crop protection. Pest Manag Sci 64:1099–1105

    Article  CAS  PubMed  Google Scholar 

  25. Matsuda K, Kanaoka S, Akamatsu M, Sattelle DB (2009) Diverse actions and target-site selectivity of neonicotinoids: structural insights. Mol Pharmacol 76:1–10

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Nauen R, Bretschneider T (2002) New modes of action of insecticides. Pest Outlook 13:241–245

    Article  CAS  Google Scholar 

  27. Casida JE, Quistad GB (2004) Why insecticides are more toxic to insects than people: the unique toxicology of insects. J Pestic Sci 29:81–86

    Article  CAS  Google Scholar 

  28. Liu GY, Ju XL, Cheng J (2010) Selectivity of imidacloprid for fruit fly versus rat nicotinic acetylcholine receptors by molecular modeling. J Mol Model 16:993–1002

    Article  CAS  PubMed  Google Scholar 

  29. Simon-Delso N, Amaral-Rogers V, Belzunces LP et al (2015) Systemic insecticides (neonicotinoids and fipronil): trends, uses, mode of action and metabolites. Environ Sci Pollut Res Int 22:5–34

    Article  CAS  PubMed  Google Scholar 

  30. Li C, Xu X-Y, Li J-Y et al (2011) Synthesis and chiral purification of 14C-labeled novel neonicotinoids, paichongding. J Label Comp Radiopharm 54:775–779

    Article  CAS  Google Scholar 

  31. Shao X, Swenson TL, Casida JE (2013) Cycloxaprid insecticide: nicotinic acetylcholine receptor binding site and metabolism. Agric Food Chem 61:7883–7888

    Article  CAS  Google Scholar 

  32. Tomizawa M, Durkin KA, Ohno I et al (2011) N-haloacetylimino neonicotinoids: potency and molecular recognition at the insect nicotinic receptor. Bioorg Med Chem Lett 21:3583–3586

    Article  CAS  PubMed  Google Scholar 

  33. Zhang WW, Yang XB, Chen WD et al (2010) Design, multicomponent synthesis, and bioactivities of novel neonicotinoid analogues with 1,4-dihydropyridine scaffold. J Agric Food Chem 58:2741–2745

    Article  CAS  PubMed  Google Scholar 

  34. Verhaar HJM, Eriksson L, Sjostrom M et al (1994) Modelling the toxicity of organophosphates: a comparison of the multiple linear regression and PLS regression methods. Quant Struct-Act Relat 13:133–143

    CAS  Google Scholar 

  35. Schuurmann G (1990) QSAR analysis of the acute fish toxicity of organic phosphorothionates using theoretically derived molecular descriptors. Environ Toxicol Chem 9:417–428

    Article  Google Scholar 

  36. Perrin DD, Dempsey B, Serjeant EP (1981) pK, prediction for organic acids and bases. Chapman and Hall, New York

    Book  Google Scholar 

  37. Leo A (1986) CLOGP-3.42 MedChem Software, Medicinal Chemistry Project, Pomona College, Claremont

    Google Scholar 

  38. Opperhuizen A, Volde EW, Gobas FAPC et al (1985) Relationship between bioconcentration in fish and steric factors of hydrophobic chemicals. Chemosphere 14:1871–1896

    Article  CAS  Google Scholar 

  39. Drew MGB, Lumley JA, Price NR (1999) Predicting ecotoxicology of organophosphorous insecticides: successful parameter selection with the genetic function algorithm. Quant Struct-Act Relat 18:573–583

    Article  CAS  Google Scholar 

  40. Cerius2 (1997) Molecular Simulations Inc., San Diego. http://www-jmg.ch.cam.ac.uk/cil/SGTL/cerius2.html. Accesed 12 Mar 2019

  41. Tsar V2.4, Oxford Molecular Ltd., Magdalen Centre, Oxford Science Park, Standford-on-Thames, Oxford

    Google Scholar 

  42. Frisch MJ, Trucks GW, Schlegel HB et al (1995) Gaussian 94, revision E.1, Gaussian, Inc., Pittsburgh

    Google Scholar 

  43. Yan D, Jiang X, Yu G et al (2006) Quantitative structure-toxicity relationships of organophosphorous pesticides to fish (Cyprinus carpio). Chemosphere 63:744–750

    Article  CAS  PubMed  Google Scholar 

  44. Li F (1991) The metabolism and toxicity of the agrochemical. Chemical Industry Press, Beijing

    Google Scholar 

  45. Mazzatorta P, Benfenati E, Lorenzini P, Vighi M (2004) QSAR in ecotoxicity: An overview of modern classification Techniques. J Chem Inf Comput Sci 44:105–112

    Article  CAS  PubMed  Google Scholar 

  46. Guo JX, Wu JJ, Wright JB, Lushington GH (2006) Mechanistic insight into acetylcholinesterase inhibition and acute toxicity of organophosphorus compounds: a molecular modeling study. Chem Res Toxicol 19:209–216

    Article  CAS  PubMed  Google Scholar 

  47. Garcia-Domenech R, Alarcon-Elbal P, Bolas G et al (2007) Prediction of acute toxicity of organophosphorus pesticides using topological indices. SAR QSAR Environ Res 18:745–755

    Article  CAS  PubMed  Google Scholar 

  48. Can A (2014) Quantitative structure-toxicity relationship (QSTR) studies on the organophosphate insecticides. Toxicol Lett 230:434–443

    Article  CAS  PubMed  Google Scholar 

  49. Zhao J, Yu S (2013) Quantitative structure-activity relationship of organophosphate compounds based on molecular interaction fields descriptors. Environ Toxicol Pharmacol 35:228–234

    Article  CAS  PubMed  Google Scholar 

  50. Niraj RR, Saini V, Kumar A (2015) QSAR analyses of organophosphates for insecticidal activity and its in-silico validation using molecular docking study. Environ Toxicol Pharmacol 40:886–894

    Article  CAS  PubMed  Google Scholar 

  51. Vighi M, Garlanda MM, Calamari D (1991) QSARs for toxicity of organophosphorous pesticides to Daphnia and honeybees. Sci Total Environ 109–110:605–622

    Article  Google Scholar 

  52. Tanji K, Sullivan J (1995) QSAR analysis of the chemical hydrolysis of organophosphorus pesticides in natural waters. Technical completion report, project number W-843. https://escholarship.org/content/qt44p7338k/qt44p7338k.pdf. Accesed 23 Jan 2019

  53. Lu GN, Dang Z, Tao XQ et al (2007) Quantitative Structure-Activity Relationships for enzymatic activity of chloroperoxidase on metabolizing organophosphorus pesticides. QSAR Comb Sci 26:182–188

    Article  CAS  Google Scholar 

  54. Bass C, Denholm I, Williamson MS, Nauen R (2015) The global status of insect resistance to neonicotinoid insecticides. Pestic Biochem Physiol 121:78–87

    Article  CAS  PubMed  Google Scholar 

  55. Tomizawa M, Casida JE (2003) Selective toxicity of neonicotinoids attributable to specificity of insect and mammalian nicotinic receptors. Annu Rev Entomol 48:339–364

    Article  CAS  PubMed  Google Scholar 

  56. Neonicotinoids: risks to bees confirmed (2018) European Food Safety Authority. https://www.efsa.europa.eu/en/press/news/180228, https://www.efsa.europa.eu/sites/default/files/news/180228-QA-Neonics.pdf. Accesed 15 Feb 2019

  57. Goulson D, Nicholls E, BotÚas C, Rotheray EL (2015) Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347(6229):1255957

    Article  PubMed  CAS  Google Scholar 

  58. Thompson H, Maus C (2007) The relevance of sub-lethal effects in honey bee testing for pesticide risk assessment. Pest Manag Sci 63:1058–1061

    Article  CAS  PubMed  Google Scholar 

  59. Basant N, Gupta S (2017) QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes. Environ Sci Pollut Res 24:14430–14444

    Article  CAS  Google Scholar 

  60. Hamadache M, Benkortbi O, Hanini S, Amrane A (2018) QSAR modeling in ecotoxicological risk assessment: application to the prediction of acute contact toxicity of pesticides on bees (Apis mellifera L). Environ Sci Pollut Res 25:896–907

    Article  CAS  Google Scholar 

  61. Wang X, Chu Z, Yang J, Li Y (2017) Pentachlorophenol molecule design with lower bioconcentration through 3D-QSAR associated with molecule docking. Environ Sci Pollut Res 24:25114–25125

    Article  CAS  Google Scholar 

  62. Hamadache M, Benkortbi O, Hanini S et al (2016) A quantitative structure-activity relationship for acute oral toxicity of pesticides on rats: validation, domain of application and prediction. J Hazard Mater 303:28–40

    Article  CAS  PubMed  Google Scholar 

  63. Cronin MTD, Walker JD, Jaworska JS et al (2003) Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances. Environ Health Perspect 111:1376–1390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Shao X, Li Z, Qian X, Xu X (2009) Design, synthesis, and insecticidal activities of novel analogues of neonicotinoids: replacement of nitromethylene with nitroconjugated system. J Agric Food Chem 57:951–957

    Article  CAS  PubMed  Google Scholar 

  65. Shao X, Fu H, Xu X et al (2010) Divalent and oxabridged neonicotinoids constructed by dialdehydes and nitromethylene analogues of imidacloprid: design, synthesis, crystal structure, and insecticidal activities. J Agric Food Chem 58:2696–2702

    Article  CAS  PubMed  Google Scholar 

  66. Xu R, Xia R, Luo M et al (2014) Design, synthesis, crystal structures, and insecticidal activities of eight-membered azabridge neonicotinoid analogues. J Agric Food Chem 62:381–390

    Article  CAS  PubMed  Google Scholar 

  67. Lei C, Geng L, Xu X, Shao X, Li Z (2018) Isoxazole-containing neonicotinoids: design, synthesis, and insecticidal evaluation. Bioorg Med Chem Lett 28:831–833

    Article  CAS  PubMed  Google Scholar 

  68. van der Sluijs JP, Simon-Delso N, Goulson D et al (2013) Neonicotinoids, bee disorders and the sustainability of pollinator services. Curr Opin Environ Sustain 5:293–305

    Article  Google Scholar 

  69. Goulson D (2013) An overview of the environmental risks posed by neonicotinoid insecticides. J Appl Ecol 50:977–987

    Article  Google Scholar 

  70. Devillers J, Pham-Delegue MH, Decourtye A et al (2003) Modeling the acute toxicity of pesticides to Apis mellifera. Bull Insectol 56:103–109

    Google Scholar 

  71. Toropov A, Benfenati E (2007) SMILES as an alternative to the graph in QSAR modeling of bee toxicity. Comput Biol Chem 31:57–60

    Article  CAS  PubMed  Google Scholar 

  72. Singh KP, Gupta S, Basant N, Mohan D (2014) QSTR modeling for qualitative and quantitative toxicity predictions of diverse chemical pesticides in honey bee for regulatory purposes. Chem Res Toxicol 27:1504–1515

    Article  CAS  PubMed  Google Scholar 

  73. Zhao Y, Li Y (2018) Modified neonicotinoid insecticide with bi-directional selective toxicity and drug resistance. Ecotoxicol Environ Saf 164:467–473

    Article  CAS  PubMed  Google Scholar 

  74. Nishimura K, Kiriyama K, Kagabu S (2006) Quantitative structure-activity relationships of imidacloprid and its analogs with substituents at the C5 position on the pyridine ring in the neuroblocking activity. J Pestic Sci 31:110–115

    Article  CAS  Google Scholar 

  75. Sung N-D, Jang S-C, Choi K-S (2006) CoMFA and CoMSIA on the neuroblocking activity of 1-(6-chloro-3-pyridylmethyl)-2-nitroiminoimidazolidine analogues. Bull Kor Chem Soc 27:1741–1746

    Article  CAS  Google Scholar 

  76. Sung N-D, Jang S-C, Choi K-S (2008) Insecticidal and neuroblocking potencies of variants of the thiazolidine moiety of thiacloprid and quantitative relationship study for the key neonicotinoid pharmacophore. J Pestic Sci 33:58–66

    Google Scholar 

  77. Kagabu S, Ishihara R, Hieda Y, Nishimura K, Naruse Y (2007) Insecticidal and neuroblocking potencies of variants of the imidazolidine moiety of imidacloprid-related neonicotinoids and the relationship to partition coefficient and charge density on the pharmacophore. J Agric Food Chem 55:812–818

    Article  CAS  PubMed  Google Scholar 

  78. Okazawa A, Akamatsu M, Ohoka A et al (1998) Prediction of the binding mode of imidacloprid and related compounds to house fly head acetylcholine receptors using three-dimensional QSAR analysis. Pestic Sci 54:134–144

    Article  CAS  Google Scholar 

  79. Suzuki T, Avram S, Borota A, Funar-Timofei S (2014) QSAR modeling of N3-substituted imidacloprid insecticides used against the housefly musca domestica. J Toyo Univ Natural Sci 8:83–95. http://jairo.nii.ac.jp/0236/00004962/en

    Google Scholar 

  80. Nishiwaki H, Nagaoka H, Kuriyama M et al (2011) Affinity to the nicotinic acetylcholine receptor and insecticidal activity of chiral imidacloprid derivatives with a methylated imidazolidine ring. Biosci Biotechnol Biochem 75:780–782

    Article  CAS  PubMed  Google Scholar 

  81. Kiriyama K, Nishiwaki H, Nakagawa Y, Nishimura K (2003) Insecticidal activity and nicotinic acetylcholine receptor binding of dinotefuran and its analogues in the housefly, Musca domestica. Pest Manag Sci 59:1093–1100

    Article  CAS  PubMed  Google Scholar 

  82. Li J, Ju XL, Jiang FC (2008) Pharmacophore model for neonicotinoid insecticides. Chin Chem Lett 19:619–622

    Article  CAS  Google Scholar 

  83. Li Q, Kong X, Xiao Z et al (2012) Structural determinants of imidacloprid-based nicotinic acetylcholine receptor inhibitors identified using 3D-QSAR, docking, and molecular dynamics. J Mol Model 18:2279–2289

    Article  CAS  PubMed  Google Scholar 

  84. Nagaoka H, Nishiwaki H, Kubo T et al (2015) Docking model of the nicotinic acetylcholine receptor and nitromethylene neonicotinoid derivatives with a longer chiral substituent and their biological activities. Bioorg Med Chem 23:759–769

    Article  CAS  PubMed  Google Scholar 

  85. Nishiwaki H, Sato K, Nakagawa Y et al (2004) Metabolism of imidacloprid in houseflies. J Pestic Sci 29:110–116

    Article  CAS  Google Scholar 

  86. Nishiwaki H, Kuriyama M, Nagaoka H et al (2012) Synthesis of imidacloprid derivatives with a chiral alkylated imidazolidine ring and evaluation of their insecticidal activity and affinity to the nicotinic acetylcholine receptor. Bioorg Med Chem 20:6305–6312

    Article  CAS  PubMed  Google Scholar 

  87. Blackman RL, Eastop VF (2007) Taxonomic issues. In: van Emden HF, Harrington R (eds) Aphids as crop pests. CABI, Wallingford

    Google Scholar 

  88. Tian Z, Shao X, Li Z et al (2007) Synthesis, insecticidal activity, and QSAR of novel nitromethylene neonicotinoids with tetrahydropyridine fixed cis configuration and exo-ring ether modification. J Agric Food Chem 55:2288–2292

    Article  CAS  PubMed  Google Scholar 

  89. Wang MJ, Zhao XB, Wu D et al (2014) Design, synthesis, crystal structure, insecticidal activity, molecular docking, and QSAR studies of novel N3substituted imidacloprid derivatives. J Agric Food Chem 62:5429–5442

    Article  CAS  PubMed  Google Scholar 

  90. Bora A, Avram S, Funar-Timofei S, Halip L (2018) Computational electronic profile of the insecticide imidacloprid and analogues. Rev Roum Chim 63:861–867

    Google Scholar 

  91. Xu R, Luo M, Xia R et al (2014) Seven-membered azabridged neonicotinoids: synthesis, crystal structure, insecticidal assay, and molecular docking studies. J Agric Food Chem 62:11070–11079

    Article  CAS  PubMed  Google Scholar 

  92. Yang L, Zhao Y-L, Li H-H et al (2014) Design, synthesis, crystal structure, bioactivity, and molecular docking studies of novel sulfonylamidine-derived neonicotinoid analogues. Med Chem Res 23:5043–5057

    Article  CAS  Google Scholar 

  93. Funar-Timofei S, Bora A (2017) QSAR study of neonicotinoid insecticidal activity against cowpea aphids by the MLR approach. In: Proceedings of the 21st international electronic conference on synthetic organic chemistry, 4727. https://doi.org/10.3390/ecsoc-21-04727

  94. Funar-Timofei S, Bora A (2019) Insecticidal activity evaluation of phenylazo and dihydropyrrole-fused neonicotinoids against cowpea aphids using the MLR approach. Proceedings 9:18. https://doi.org/10.3390/ecsoc-22-05664

    Article  Google Scholar 

  95. Bora A, Suzuki T, Funar-Timofei S (2019) Neonicotinoid insecticide design: molecular docking, multiple chemometric approaches, and toxicity relationship with Cowpea aphids. Environ Sci Pollut Res Int 26:14547–14561. https://doi.org/10.1007/s11356-019-04662-9

    Article  CAS  PubMed  Google Scholar 

  96. Hidaka K, Kimura T, Abdel-Rahman HM et al (2000) Small-sized human immunodeficiency virus type-1 protease inhibitors containing allophenylnorstatine to explore the S2’ pocket. Biochemistry 39:12534–12542

    Article  CAS  Google Scholar 

  97. Wissner A, Berger DM, Boschelli DH et al (2000) 4-Anilino-6,7-dialkoxyquinoline-3-carbonitrile inhibitors of epidermal growth factor receptor kinase and their bioisosteric relationship to the 4-anilino-6,7-dialkoxyquinazoline inhibitors. J Med Chem 43:3244–3256

    Article  CAS  PubMed  Google Scholar 

  98. Xia S, Cheng J, Feng Y et al (2014) Computational investigations about the effects of hetero-molecular aggregation on bioactivities: a case of neonicotinoids and water. Chin J Chem 32:324–334

    Article  CAS  Google Scholar 

  99. Zhu C, Li G, Xiao K et al (2019) Water bridges are essential to neonicotinoids: insights from synthesis, bioassay, and molecular modeling studies. Chin J Chem 30:255–258

    CAS  Google Scholar 

  100. Loso MR, Benko Z, Buysse A et al (2016) SAR studies directed toward the pyridine moiety of the sap-feeding insecticide sulfoxaflor (Isoclast™ active). Bioorg Med Chem 24:378–382

    Article  CAS  PubMed  Google Scholar 

  101. Crisan L, Borota A, Suzuki T, Funar-Timofei S (2019) An approach to identify new insecticides against Myzus Persicae. In silico study based on linear and non-linear regression techniques. Mol Inform. https://doi.org/10.1002/minf.201800119

    Article  CAS  Google Scholar 

  102. Namba T (1971) Cholinesterase inhibition by organophosphorus compounds and its clinical effects. Bull World Health Organ 44:289–307

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Koureas M, Tsakalof A, Tsatsakis A, Hadjichristodoulou C (2012) Systematic review of biomonitoring studies to determine the association between exposure to organophosphorus and pyrethroid insecticides and human health outcomes. Toxicol Lett 210:155–168

    Article  CAS  PubMed  Google Scholar 

  104. Colovic MB, Krstic DZ, Lazarevic-Pasti TD et al (2013) Acetylcholinesterase inhibitors: pharmacology and toxicology. Curr Neuropharmacol 11:315–335

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Mearns J, Dunn J, Lees-Haley PR (1994) Psychological effects of organophosphate pesticides: a review and call for research by psychologists. J Clin Psychol 50:286–294

    Article  CAS  PubMed  Google Scholar 

  106. Johnson MK (1969) A phosphorylation site in brain and the delayed neurotoxic effect of some organophosphorus compounds. Biochem J 111:487–495

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Johnson MK (1969) The delayed neurotoxic effect of some organophosphorus compounds. Identification of the phosphorylation site as an esterase. Biochem J 114:711–717

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Kobayashi S, Okubo R, Ugawa Y (2017) Delayed polyneuropathy induced by organophosphate poisoning. Intern Med 56:1903–1905

    Article  PubMed  PubMed Central  Google Scholar 

  109. Richardson RJ, Hein ND, Wijeyesakere SJ et al (2013) Neuropathy target esterase (NTE): overview and future. Chem Biol Interact 203:238–244

    Article  CAS  PubMed  Google Scholar 

  110. Stallone L, Beseler C (2002) Pesticide poisoning and depressive symptoms among farm residents. Ann Epidemiol 12:389–394

    Article  Google Scholar 

  111. Wang A, Cockburn M, Ly TT et al (2014) The association between ambient exposure to organophosphates and Parkinson’s disease risk. Occup Environ Med 71:275–281

    Article  PubMed  CAS  Google Scholar 

  112. Yan D, Zhang Y, Liu L, Yan H (2016) Pesticide exposure and risk of Alzheimer’s disease: a systematic review and meta-analysis. Sci Rep 6:32222

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Guyton KZ, Loomis D, Grosse Y et al (2015) Carcinogenicity of tetrachlorvinphos, parathion, malathion, diazinon, and glyphosate. Lancet Oncol 16:490–491

    Article  PubMed  Google Scholar 

  114. Lerro CC, Koutros S, Andreotti G et al (2015) Organophosphate insecticide use and cancer incidence among spouses of pesticide applicators in the agricultural health study. Occup Environ Med 72:736–744

    Article  PubMed  Google Scholar 

  115. Kitamura S, Sugihara K, Fujimoto N, Yamazaki T (2011) Organophosphates as endocrine disruptors. In: Satoh T, Gupta RC (eds) Anticholinesterase pesticides: metabolism, neurotoxicity, and epidemiology. Wiley, New York

    Google Scholar 

  116. Sutris JM, How V, Sumeri SA, Muhammad M et al (2016) Genotoxicity following organophosphate pesticides exposure among Orang Asli children living in an agricultural island in Kuala Langat, Selangor, Malaysia. Int J Occup Environ Med 7:42–51

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Hulse EJ, Davies JO, Simpson AJ et al (2014) Respiratory complications of organophosphorus nerve agent and insecticide poisoning. Implications for respiratory and critical care. Am J Respir Crit Care Med 190:1342–1354

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  118. Bouchard MF, Bellinger DC, Wright RO, Weisskopf MG (2010) Attention-deficit/hyperactivity disorder and urinary metabolites of organophosphate pesticides. Pediatrics 125:e1270–e1277

    Article  PubMed  Google Scholar 

  119. Mastrantonio G, Mack HG, Della Védova CO (2008) Interpretation of the mechanism of acetylcholinesterase inhibition ability by organophosphorus compounds through a new conformational descriptor. An experimental and theoretical study. J Mol Model 14:813–821

    Article  CAS  PubMed  Google Scholar 

  120. Yazal JE, Rao SN, Mehl A, Slikker W Jr (2001) Prediction of organophosphorus acetylcholinesterase inhibition using three-dimensional quantitative structure-activity relationship (3D-QSAR) methods. Toxicol Sci 63:223–232

    Article  PubMed  Google Scholar 

  121. Ruark CD, Hack CE, Robinson PJ et al (2013) Quantitative structure-activity relationships for organophosphates binding to acetylcholinesterase. Arch Toxicol 87:281–289

    Article  CAS  PubMed  Google Scholar 

  122. Veselinovic JB, Nikolic GM, Trutic NV et al (2015) Monte Carlo QSAR models for predicting organophosphate inhibition of acetylcholinesterase. SAR QSAR Environ Res 26:449–460

    Article  CAS  PubMed  Google Scholar 

  123. Schaffer NK, Lang RP, Simet L, Drisko RW (1958) Phosphopeptides from acid-hydrolyzed P32-labeled isopropyl methylphosphonofluoridate-inactivated trypsin. J Biol Chem 1:185–192

    Google Scholar 

  124. Somogyi L, Martin SP, Venkatesan T, Ulrich CD (2001) Recurrent acute pancreatitis: an algorithmic approach to identification and elimination of inciting factors. Gastroenterology 120:708–717

    Article  CAS  PubMed  Google Scholar 

  125. Ruark CD (2010) Quantitative structure-activity relationships for organophosphates binding to trypsin and chymotrypsin. Dissertation, Miami University

    Google Scholar 

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Acknowledgments

This work was financially supported by the Project No. 1.1/2018 of the “Coriolan Dragulescu” Institute of Chemistry of the Romanian Academy. Alina Bora, Luminita Crisan, and Ana Borota contributed equally to this work.

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    Authors and Affiliations

    1. “Coriolan Dragulescu” Institute of Chemistry, Timisoara, Romania

      Alina Bora, Luminita Crisan, Ana Borota, Simona Funar-Timofei & Gheorghe Ilia

    2. West University Timisoara, Faculty of Chemistry-Biology and Geography, Timisoara, Romania

      Gheorghe Ilia

    Authors
    1. Alina Bora
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    2. Luminita Crisan
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    3. Ana Borota
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    4. Simona Funar-Timofei
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    5. Gheorghe Ilia
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    Corresponding author

    Correspondence to Gheorghe Ilia .

    Editor information

    Editors and Affiliations

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

      Kunal Roy

    Glossary

    AChE

    Acetylcholinesterase

    ADME

    Absorption, distribution, metabolism, excretion

    Analogue

    A chemical compound that differs from another compound by one or more atoms. These compounds form a congeneric series of the compound, which have similar structures and similar physicochemical properties.

    ANN

    Artificial neural networks

    CART

    Classification and regression tree

    CoMFA

    Comparative molecular field analysis

    COMSIA

    Comparative molecular similarity index analysis

    Descriptor

    A numeric representation of molecules based on their chemical structures, e.g., steric descriptors, which are related to shape or molecular size, hydrophobic descriptors (usually quantified by logP—the partition coefficient between hydrophilic and hydrophobic phases), and electronic descriptors such as atomic charge, etc.

    EC50

    Half maximal effective concentration

    ED50

    Effective dose (for inducing paralysis or death in 50% of the tested population)

    F

    Fischer test

    IMI

    Imidacloprid

    In silico

    An expression, which denotes, “performed on the computer or via computer simulation.”

    K a

    The binding constant

    K i

    The inhibition constant or bimolecular rate constant

    K p

    The phosphorylation rate constant

    KNN

    K-nearest neighbors classification

    LC50

    The median lethal concentration (the concentration of a substance expected to induce death of 50% of the members of a tested population)

    LD50

    The median lethal dose (the single dose necessary to kill 50% of the members of a tested population)

    LDA

    Linear discriminant analysis

    logBCF

    Logarithm of the bioconcentration factor

    MLR

    Multiple linear regression

    NMC

    Nearest mean classifier

    nAChR

    Nicotinic acetylcholine receptor

    OP

    Organophosphorus

    p

    Significance level of regression

    PLS

    Partial least squares

    Q 2

    Cross-validation correlation coefficient

    QDA

    Quadratic discriminant analysis

    QSAR

    Quantitative structure-activity relationship

    QSTR

    Quantitative structure-toxicity relationship

    R 2

    The coefficient of correlation/determination

    R 2 adj

    The adjusted R2

    RDA

    Regularized discriminant analysis

    RMSE

    Root-mean-square error

    SEE

    Standard error of the estimate

    SIMCA

    Soft independent modeling of class analogy

    SVM

    Support vector machine

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    Bora, A., Crisan, L., Borota, A., Funar-Timofei, S., Ilia, G. (2020). Ecotoxicological QSAR Modeling of Organophosphorus and Neonicotinoid Pesticides. 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_21

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    • DOI: https://doi.org/10.1007/978-1-0716-0150-1_21

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    • Publisher Name: Humana, New York, NY

    • Print ISBN: 978-1-0716-0149-5

    • Online ISBN: 978-1-0716-0150-1

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