DFT-QSAR models to predict biological activities of carbamates, s-alkylcarbamathioates, ureas and chloroacetamides derivatives

Azeddine Adad, Majdouline Larif, Rachid Hmammouchi, Abdelhafid Idrissi Taghki, Mohammed Bouachrine, Tahar Lakhlifi


3D-QSAR study is applied to a set of 76 molecules based on 4 sets of compounds. This study was conducted using the principal component analysis (PCA) method, the past least square regression method (PLS) and the artificial neural network (ANN). The predicted values of activities are in good agreement with the experimental results. The past least square regression method (PLS) techniques, considering the relevant, showed a correlation coefficient (R2) values more than 0,70 which is a good result. As a result of quantitative structure-activity relationships, we found that the model proposed in this study is constituted of major descriptors used to describe these molecules. The obtained results suggested that the proposed combination of several calculated parameters could be useful to predict the biological activity of carbamates, s-alkylcarbamathioates, ureas, chloroacetamides derivatives.


Vimal Ramani, 2011. Effect of pesticides on phosphate solubilization by Bacillus sphaericus and Pseudomonas cepacia. Volume 99, Issue 3, 232–236.

Michele Del Carlo, Marcello Mascini, Alessia Pepe, Gianofranco Diletti, Dario Compagnone, 2004. Screening of food samples for carbamate and organophosphate pesticides using an electrochemical bioassay. Food Chemistry, 88 (4), 651-656.

Brandy, White, J. and Jams Harmon, H., 2005. Optical solid-state detection of organophosphates using organophosphorus hydrolase. Biosensors and Bioelectronics., 20 (10), 1977-1983.

Paulino, M. G., Sakuragui, M. M., Fernandes, M.N., 2012. Effects of atrazine on the gill cells and ionic balance in a neotropical ï¬sh, Prochilodus lineatus. Chemosphere, 86; 1–7.

McKinney, J. D., Richard, A., Waller, C., Newman, M. C., Gerberik, F., 2000. The practice of structure activity relationships (SAR) in toxicology., Toxicol. Sci., 56, 8.

Roy, K., Ghosh, G., 2009. QSTR with extended topochemical atom (ETA) indices. 12. QSAR for the toxicity of diverse aromatic compounds to Tetrahymena pyriformis using chemometric tools., Chemosphere, 77, 999-1009.

Hansch, C., Muir, R. M., Fujita, T., Maloney, P. P, Geiger, F., Streich, M., 1963. J. Am. Chem. Soc., 85, 2817-2825.

Bodor, N., 1988. Current Medicinal Chemistry, 5, 353-380. From book: Biochemistry of Redox Reactions, by Bernard Testa, editor: London [u, a], Acad. Press, 1995.

Sabljic, A., Güsten, H., Verhaar, H., Hermens, J., 1995. QSAR modelling of soil sorption. Improvements and systematics of logKoc vs. logP correlations. Chemosphere, 31, 4489–4514.

Sabljic, A., 2001. QSAR models for estimating properties of persistent organic pollutants required in evaluation of their environmental fate and risk. Chemosphere, 43, 363–375.

Yang Wen, Li M., Su Wie, C., Qin, Ling Fu, Jia He, Yuan, H. Zhao, 2012. Linear and non-linear relationships between soil sorption and hydrophobicity: Model, validation and influencing factors. Chemosphere, 86, 634–640.

Benigni, R.; Zito, R., 2004. The second national toxicology program comparative exercise on the prediction of rodent carcinogenicity: deï¬nitive results. Mutat. Res., 566, 49–63.

Zakarya, D., Larfaoui, E. M., Boulaamail, A., Tollabi, M. and Lakhlifi, T., 1998. QSARs for a series of inhibitory anilids. Chemosphere, Vol. 36, N° 13, 2809-2818.

Elhallaoui, M., Elasri, M., Ouazzani, F., Mechaqrane, A. and Lakhlifi,T., 2003. Quantitative Structure-Activity Relationships of Noncompetitive Antagonists of the NMDA Recetor: A Study of a series of MK801 Derivative Molecules Using Statistical Methods and Neural Network. Int. J. Mol. Sci, 4, 249-262.

Papa, E., Battaini, F., Gramatica, P., 2005. Ranking of aquatic toxicity of esters modelled by QSAR. Chemosphere, 58, 559-570.

Zhang, L., Hao, G. F., Tan, Y., Xi, Z., Huang, M. Z., Yang, G. F., 2009. Bioactive conformation analysis of cyclic imides as protoporphyrinogen oxidase inhibitor by combining DFT calculations, QSAR and molecular dynamic simulations. Bioorganic & Medicinal Chemistry, 17, 4935-4942.

Jing, G., Zhou, Z., Zhuo, J., 2012. Quantitative structure-activity relationship (QSAR) study of toxicity of quaternary ammonium compounds on Chlorella pyrenoidosa and Scenedesmus quadricauda. Chemosphere, 86, 76-82.

Larif, M., Adad, A., Hmammouchi, R., Taghki, A. I., Soulaymani, A., Elmidaoui, A., Bouachrine, M. and Lakhlifi, T., 2013. Biological activities of triazine derivatives. Combining DFT and QSAR results, article in press in Arabian Journal of Chemistry. http://dx.doi.org/10.1016/j.arabjc.2012.12.033

Supratik K., Kunal R., 2012. First report on development of quantitative interspecies structure–carcinogenicity relationship models and exploring discriminatory features for rodent carcinogenicity of diverse organic chemicals using OECD guidelines. Chemosphere in press.

Laarej, K., Bouachrine, M., Radi, S., Kertit, S. and Hammouti, B., 2010. Quantum Chemical Studies on the Inhibiting Effect of Bipyrazoles on Steel Corrosion in HCl. E-Journal of Chemistry, 7(2), 419-424.

Zarrok, H., Oudda, H., Zarrouk, A., Salghi, R., Hammouti, B., Bouachrine, M., 2011. Weight Loss Measurement and Theoretical Study of New Pyridazine Compound as Corrosion Inhibitor for C38 Steel in Hydrochloric Acid Solution. Der Pharma Chemica, 3 (6): 576-590.

Chimizou, R., Iwamura, H., Fujita, T., 1988. Agric Food Chem. 36, 1276.

Larfaoui, E. M., 1997. Impact des pesticides sur l'environnement: Étude de la toxicité et mode d'action de diverses familles d'herbicides par les méthodes statistiques et les réseaux de neurones. Thesis, University Moulay Ismail, Faculty of Science, Meknes, Morocco.

Hogarh, J. N., Seike, N., Kobara, Y., Habib, A., Namd, J. J., Lee, J. S. Qilu Li, Liu, X., Jun Li, Zhang, G., Masunaga, S., 2012. Passive air monitoring of PCBs and PCNs across East Asia: A comprehensive congener evaluation for source characterization. Chemosphere, 86: 718–726.

Taurino, A.M., Dello, D., Monaco, S. Capone, M. Epifani, R. Rella, P. Siciliano, L. Ferrara, G. Maglione, A. Basso, D. Balzarano., 2003. Analysis of dry salami by means of an electronic nose and correlation with microbiological methods. Sensors and Actuators B 95, 123–131

Demuth, H., Hugan, M., Beal M., 2011. Neural Network Toolbox. For use with MATHLAB, User Guid's, Version 9.

Zakarya, D., Larfaoui, E. M., Boulaamail, A. and Lakhlifi, T., 1996. Analysis of structure-toxicity relationships for a series of amide herbicides using statistical methods and neural network. SAR and QSAR in Environmental Research, 5, 269-279.

Zakarya, D., Boulaamail, A., Larfaoui, E. M. and Lakhlifi, T., 1997. QSARs for DDT-Type analogs using statistical methods and neural network. SAR and QSAR in Environmental Research, 6, 183-203.

Zupan, J., Gasteiger, J., 1999. Neural Networks for Chemistry and Drug Design: An Introduction, second ed., VCH, Weinheim.

Turkan N., 1993. Génie, gènes et neurones, Revue de l’Université de Moncton, 26 (1), 205-221.

Lee, P. Y., Chen C. Y. J., 2009. Hazard. Mater., 165, 156-161.

Adamo, C.; Barone, V., 2000. A TDDFT study of the electronic spectrum of s-tetrazine in the gas-phase and in aqueous solution. Chem. Phys. Lett., 330, 152–160.

Parac, M., Grimme, S., 2003. All calculations were done by GAUSSIAN 03 W software., J. Phys. Chem., A 106, 6844–6850.

Gaussian 03, Revision B.01, M. J. Frisch, and al., Gaussian, Inc., Pittsburgh, PA, 2003.

Becke, A. D., 1993. A new mixing of Hartree–Fock and local densityâ€functional theories. J. Chem. Phys., 98, 1372.

Lee, C., Yang, W., Parr, R. G., 1988. Development of the Colle-Salvetti conelation energy formula into a functional of the electron density., Phys. Rev., B. 37, 785-789.

STATITCF Software, 1987. Technical Institute of cereals and fodder, Paris, France.

Jonathan, N. H., Nobuyasu, S., Yuso, K., Ahsan, H., Jae-Jak, N., Jong-Sik, L. Q. L., Xiang, L., Jun, L., Gan, Z., Shigeki, M., 2012. Passive air monitoring of PCBs and PCNs across East Asia: A comprehensive congener evaluation for source characterization. Chemosphere, 86, 718–726.

Full Text: PDF


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.