Artículo

Fioressi, S.E.; Bacelo, D.E.; Rojas, C.; Aranda, J.F.; Duchowicz, P.R."Conformation-independent quantitative structure-property relationships study on water solubility of pesticides" (2019) Ecotoxicology and Environmental Safety. 171:47-53
El editor solo permite la decarga de la versión post-print. Si usted posee dicha versión, enviela a
Consulte el artículo en la página del editor
Consulte la política de Acceso Abierto del editor

Abstract:

Water solubility is a key physicochemical parameter in pesticide control and regulation, although sometimes its experimental determination is not an easy task. In this study, we present Quantitative Structure-Property Relationships (QSPRs) for predicting the water solubility at 20 °C of 1211 approved heterogeneous pesticide compounds, collected from the online Pesticides Properties Data Base (PPDB). Validated and generally applicable Multivariable Linear Regression (MLR) models were established, including molecular descriptors carrying constitutional and topological aspects of the analyzed compounds. The most representative descriptors were selected from the exploration of a large number of about 18,000 structural variables. A hybrid approach that involves a molecular descriptor, a fingerprint, and a flexible descriptor showed the best predictive performance. © 2018 Elsevier Inc.

Registro:

Documento: Artículo
Título:Conformation-independent quantitative structure-property relationships study on water solubility of pesticides
Autor:Fioressi, S.E.; Bacelo, D.E.; Rojas, C.; Aranda, J.F.; Duchowicz, P.R.
Filiación:Departamento de Química, Facultad de Ciencias Exactas y Naturales, Universidad de Belgrano, Villanueva 1324, Buenos Aires, CP 1426, Argentina
Facultad de Ciencia y Tecnología, Universidad del Azuay, Av. 24 de Mayo 7-77 y Hernán Malo, Cuenca, Ecuador
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), CONICET, UNLP, Diag. 113 y 64, C.C. 16, Sucursal 4, La Plata, 1900, Argentina
Palabras clave:CORAL software; Molecular descriptors; Pesticides; Quantitative structure-property relationships; Water solubility; pesticide; pesticide; water; molecular analysis; pesticide residue; physicochemical property; quantitative analysis; regression analysis; software; solubility; Article; chemical structure; conformation; multiple linear regression analysis; quantitative structure property relation; solubility; chemistry; quantitative structure activity relation; solubility; statistical model; Linear Models; Molecular Conformation; Pesticides; Quantitative Structure-Activity Relationship; Solubility; Water
Año:2019
Volumen:171
Página de inicio:47
Página de fin:53
DOI: http://dx.doi.org/10.1016/j.ecoenv.2018.12.056
Handle:http://hdl.handle.net/20.500.12110/paper_01476513_v171_n_p47_Fioressi
Título revista:Ecotoxicology and Environmental Safety
Título revista abreviado:Ecotoxicol. Environ. Saf.
ISSN:01476513
CODEN:EESAD
CAS:water, 7732-18-5; Pesticides; Water
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01476513_v171_n_p47_Fioressi

Referencias:

  • (2017), Agency, USEP Finalization of Guidance on Incorporation of Water Treatment Effects on Pesticide Removal and Transformations in Drinking Water Exposure Assessments; Ali, J., Camilleri, P., Brown, M.B., Hutt, A.J., Kirton, S.B., In silico prediction of aqueous solubility using simple QSPR models: the importance of phenol and phenol-like moieties (2012) J. Chem. Inf. Model., 52, pp. 2950-2957
  • Ali, J., Camilleri, P., Brown, M.B., Hutt, A.J., Kirton, S.B., Revisiting the general solubility equation: in silico prediction of aqueous solubility incorporating the effect of topographical polar surface area (2012) J. Chem. Inf. Model., 52, pp. 420-428
  • Bhhatarai, B., Gramatica, P., Prediction of aqueous solubility, vapor pressure and critical micelle concentration for aquatic partitioning of perfluorinated chemicals (2010) Environ. Sci. Technol., 45, pp. 8120-8128
  • Cappelli, C.I., Manganelli, S., Lombardo, A., Gissi, A., Benfenati, E., Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds (2013) Sci. Total Environ., 463, pp. 781-789
  • Clarke, E.D., Delaney, J.S., Physical and molecular properties of agrochemicals: an analysis of screen inputs, hits, leads, and products (2003) CHIMIA Int. J. Chem., 57, pp. 731-734
  • Cronin, M.T.D., Livingstone, D.J., Predicting Chemical Toxicity and Fate (2004), CRC press Boca Raton; Das, R.N., Roy, K., QSPR with extended topochemical atom (ETA) indices. 4. Modeling aqueous solubility of drug like molecules and agrochemicals following OECD guidelines (2013) Struct. Chem., 24, pp. 303-331
  • Delaney, J.S., ESOL: estimating aqueous solubility directly from molecular structure (2004) J. Chem. Inf. Comput. Sci., 44, pp. 1000-1005
  • Duchowicz, P.R., Castro, E.A., Fernández, F.M., Alternative algorithm for the search of an optimal set of descriptors in QSAR-QSPR studies (2006) MATCH Commun. Math. Comput. Chem., 55, pp. 179-192
  • Duchowicz, P.R., Comelli, N.C., Ortiz, E.V., Castro, E.A., QSAR study for carcinogenicity in a large set of organic compounds (2012) Curr. Drug Saf., 7, pp. 282-288
  • Duchowicz, P.R., Fioressi, S.E., Bacelo, D.E., Saavedra, L.M., Toropova, A.P., Toropov, A.A., QSPR studies on refractive indices of structurally heterogeneous polymers (2015) Chemom. Intell. Lab. Syst., 140, pp. 86-91
  • Duchowicz, P.R., Fioressi, S.E., Castro, E., Wróbel, K., Ibezim, N.E., Bacelo, D.E., Conformation‐Independent QSAR Study on Human Epidermal Growth Factor Receptor‐2 (HER2) Inhibitors (2017) ChemistrySelect, 2, pp. 3725-3731
  • Eriksson, L., Jaworska, J., Worth, A.P., Cronin, M.T., McDowell, R.M., Gramatica, P., Methods for reliability and uncertainty assessment and for applicability evaluations of classification-and regression-based QSARs (2003) Environ. Health Perspect., 111, p. 1361
  • Gadaleta, D., Mangiatordi, G.F., Catto, M., Carotti, A., Nicolotti, O., Applicability domain for QSAR models: where theory meets reality (2016) Int. J. Quant. Struct.-Prop. Relatsh., 1, pp. 45-63
  • Golbraikh, A., Tropsha, A., Beware of q2! (2002) J. Mol. Graph Model, 20, pp. 269-276
  • Gramatica, P., Principles of QSAR models validation: internal and external (2007) QSAR Comb. Sci., 26, pp. 694-701
  • Hamadache, M., Amrane, A., Benkortbi, O., Hanini, S., Khaouane, L., Moussa, C.S., Environmental Toxicity of Pesticides, and its Modeling by Qsar Approaches, Advances in QSAR Modeling (2017), pp. 471-501. , Springer Cham; Hamilton, D., Ambrus, A., Dieterle, R., Felsot, A., Harris, C., Holland, P., Katayama, A., Unsworth, J., Regulatory limits for pesticide residues in water (IUPAC Technical Report) (2003) Pure Appl. Chem., 75, pp. 1123-1155
  • Hong, H., Xie, Q., Ge, W., Qian, F., Fang, H., Shi, L., Su, Z., Tong, W., Mold2, molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics (2008) J. Chem. Inf. Model., 48, pp. 1337-1344
  • Kim, M., Li, L.Y., Grace, J.R., Predictability of physicochemical properties of polychlorinated dibenzo-p-dioxins (PCDDs) based on single-molecular descriptor models (2016) Environ. Pollut., 213, pp. 99-111
  • Lewis, K., Green, A., Tzilivakis, J., Warner, D., The pesticide properties database (ppdb) developed by the agriculture & environment research unit (AERU) (2018) Univ. Herts., pp. 2006-2018
  • Mas, S., de Juan, A., Tauler, R., Olivieri, A.C., Escandar, G.M., Application of chemometric methods to environmental analysis of organic pollutants: a review (2010) Talanta, 80, pp. 1052-1067
  • (2007), OECD Guidance Document On The Validation of (Quantitative) Structure-Activity Relationship [(Q)Sar] Models, Environment Health and Safety Publications Series on Testing and Assesment No. 69; Ran, Y., He, Y., Yang, G., Johnson, J.L., Yalkowsky, S.H., Estimation of aqueous solubility of organic compounds by using the general solubility equation (2002) Chemosphere, 48, pp. 487-509
  • Rojas, C., Duchowicz, P.R., Tripaldi, P., Diez, R.P., QSPR analysis for the retention index of flavors and fragrances on a OV-101 column (2015) Chemom. Intell. Lab. Syst., 140, pp. 126-132
  • Roy, K., On some aspects of validation of predictive quantitative structure–activity relationship models (2007) Expert Opin. Drug Discov., 2, pp. 1567-1577
  • Talevi, A., Bellera, C.L., Di Ianni, M., Duchowicz, P.R., Bruno-Blanch, L.E., Castro, E.A., An integrated drug development approach applying topological descriptors (2012) Curr. Comput. Aided Drug Des., 8, pp. 172-181
  • Tebes-Stevens, C., Patel, J.M., Koopmans, M., Olmstead, J., Hilal, S.H., Pope, N., Weber, E.J., Wolfe, K., Demonstration of a consensus approach for the calculation of physicochemical properties required for environmental fate assessments (2018) Chemosphere, 194, pp. 94-106
  • Toropov, A.A., Toropova, A.P., Benfenati, E., Gini, G., Leszczynska, D., Leszczynski, J., CORAL: QSPR model of water solubility based on local and global SMILES attributes (2013) Chemosphere, 90, pp. 877-880
  • Toropov, A.A., Toropova, A.P., Benfenati, E., Nicolotti, O., Carotti, A., Nesmerak, K., Veselinović, A.M., Bacelo, D., QSPR/QSAR analyses by means of the CORAL software: results, challenges, perspectives, pharmaceutical sciences: breakthroughs in research and practice (2017) IGI Glob., pp. 929-955
  • Toropova, A., Toropov, A., Martyanov, S., Benfenati, E., Gini, G., Leszczynska, D., Leszczynski, J., CORAL: QSAR modeling of toxicity of organic chemicals towards Daphnia magna (2012) Chemom. Intell. Lab. Syst., 110, pp. 177-181
  • Verma, R.P., Hansch, C., An approach toward the problem of outliers in QSAR (2005) Bioorg. Med. Chem., 13, pp. 4597-4621
  • Villaverde, J.J., Sevilla-Morán, B., López-Goti, C., Alonso-Prados, J.L., Sandín-España, P., Computational methodologies for the risk assessment of pesticides in the European Union (2017) J. Agric. Food Chem., 65, pp. 2017-2018
  • Villaverde, J.J., Sevilla-Morán, B., López-Goti, C., Alonso-Prados, J.L., Sandín-España, P., Considerations of nano-QSAR/QSPR models for nanopesticide risk assessment within the European legislative framework (2018) Sci. Total Environ., 634, pp. 1530-1539
  • Wilczyńska-Piliszek, A.J., Piliszek, S., Falandysz, J., QSAR and ANN for the estimation of water solubility of 209 polychlorinated trans-azobenzenes (2012) J. Environ. Sci. Health, Part A, 47, pp. 155-166
  • Wishart, D.S., Feunang, Y.D., Marcu, A., Guo, A.C., Liang, K., Vázquez-Fresno, R., Sajed, T., Karu, N., HMDB 4.0: the human metabolome database for 2018 (2017) Nucleic Acids Res., 46, pp. D608-D617
  • Wold, S., Eriksson, L., Clementi, S., Statistical validation of QSAR results (1995) Chemom. Methods Mol. Des., pp. 309-338
  • Yap, C.W., PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints (2011) J. Comput. Chem., 32, pp. 1466-1474
  • Zeng, X.-L., Wang, H.-J., Wang, Y., QSPR models of n-octanol/water partition coefficients and aqueous solubility of halogenated methyl-phenyl ethers by DFT method (2012) Chemosphere, 86, pp. 619-625

Citas:

---------- APA ----------
Fioressi, S.E., Bacelo, D.E., Rojas, C., Aranda, J.F. & Duchowicz, P.R. (2019) . Conformation-independent quantitative structure-property relationships study on water solubility of pesticides. Ecotoxicology and Environmental Safety, 171, 47-53.
http://dx.doi.org/10.1016/j.ecoenv.2018.12.056
---------- CHICAGO ----------
Fioressi, S.E., Bacelo, D.E., Rojas, C., Aranda, J.F., Duchowicz, P.R. "Conformation-independent quantitative structure-property relationships study on water solubility of pesticides" . Ecotoxicology and Environmental Safety 171 (2019) : 47-53.
http://dx.doi.org/10.1016/j.ecoenv.2018.12.056
---------- MLA ----------
Fioressi, S.E., Bacelo, D.E., Rojas, C., Aranda, J.F., Duchowicz, P.R. "Conformation-independent quantitative structure-property relationships study on water solubility of pesticides" . Ecotoxicology and Environmental Safety, vol. 171, 2019, pp. 47-53.
http://dx.doi.org/10.1016/j.ecoenv.2018.12.056
---------- VANCOUVER ----------
Fioressi, S.E., Bacelo, D.E., Rojas, C., Aranda, J.F., Duchowicz, P.R. Conformation-independent quantitative structure-property relationships study on water solubility of pesticides. Ecotoxicol. Environ. Saf. 2019;171:47-53.
http://dx.doi.org/10.1016/j.ecoenv.2018.12.056