Document Type : Full research article
Authors
Department of Chemistry, Payame Noor University, 19395-4697 Tehran, Iran
Abstract
A quantitative Structure-Activity Relationship (QSAR) model was applied to the prediction of the antimicrobial activity of 22 derivatives 2, 4, 6-s-triazine as anti-malarial agents. The antimicrobial activity of 22 2, 4, 6-s-triazine derivatives were modeled with the descriptors of quantum-chemical calculations with density functional theory (DFT) method at B3LYP/6‒31G level and topological descriptors. This study was conducted using the multiple linear regressions (MLR), the partial least square analysis (PLS) and the principal component regression (PCR) method. Results displayed that the MLR method predicted of antimicrobial activity good enough. The best model, with six descriptors was selected. Also it indicates very good consistency towards data variations for the validation methods. The predicted values of antimicrobial activity are in suitable agreement with the experimental results. The obtained results suggested that the PLS method could be more helpful to predict the antimicrobial activity of 2, 4, 6-s-triazine derivatives. This study to be usable to predict the activity of other derivatives in the same groups.
Keywords
- Blasco, D. Leroy, D.A. Fidock, Antimalarial drug resistance: linking Plasmodium falciparum parasite biology to the clinic, Nat. Med. 23 (8) (2017) 917–928.
- J. Modest, Chemical and biological studies on 1, 2-dihydro-s-triazines. II. Three-component synthesis, J. Org. Chem. 21 (1956) 1–13.
- Klenke, M.P. Barrett,R. Brun, I.H. Gilbert, Antiplasmodial activity of a Series of 1, 3, 5-triazine-substituted polyamines, J. Antimicrob Chemother. 52 (2003) 290–293.
- Garwal, K. Srivastava, S.K. Puri, P.M.S. Chauhan, Synthesis of 2, 4, 6-trisubstituted triazine as antimalarial agents, Bioorg. Med. Chem. Lett. 15 (2005) 531–533.
- N. Yakhontov, G.M. Vakhatova, Search for medicinal preparations in the series of 1, 3, 5-triazines, Pharm. Chem. J. 15 (1981) 546–561.
- M.S. Chauhan, Currents and potential flaricides, Drugs Future. 25 (2000) 481–488.
- M.S. Chauhan, S.K. Srivastava, Present trends and future strategy in chemotherapy of malaria, Curr. Med. Chem. 8(2001) 1535–1542.
- L. Blakley, S.J. Benkovic, Dihydrofolate reductase in folates and pteridines. Chemistry and biochemistry of folates: dihydrofolate reductase, vol 1. Wiley, New York (1984) 191–251.
- Yousefnejad, M. Mahboubifar, R. Eskandari, Quantitative structure-activity relationship to predict the anti-malarial activity in a set of new imidazolopiperazines based on artifcial neural networks, Malaria J. 18 (310) (2019) 1-17.
- Hadni, M. Elhallaoui, 2D and 3D-QSAR, molecular docking and ADMET properties in silico studies of azaaurones as antimalarial agents, New J. Chem. 44 (2020) 6553–6565.
- H. Masand , A.A. Toropov, A.P. Toropova, D.T. Mahajan, QSAR models for anti-malarial activity of 4-aminoquinolines, Curr. Comput. Aided Drug Des. 10 (1) (2014) 75-82.
- Sanchait, H. Iftikar, K.H. Kalyan, S. Pubalee, C.D. Ramesh, Quantitative Structure-Activity Relationships of the Antimalarial Agent Artemisinin and Some of its Derivatives – A DFT Approach, Comb. Chem. High T. Scr. 16 (8) (2013) 590-602.
- T.V. Nguyen, T. V. Dat, S. Mizukami, D. L. H. Nguyen, F. Mosaddeque, S. N. Kim, D. H. B. Nguyen, O. T. Đinh, T. L.Vo, G. L.T. Nguyen, C. Q. Duong, S. Mizuta, D. N. H. Tam, M. P. Truong, N. T. Huy, K. Hirayama, 2D-quantitative structure–activity relationships model using PLS method for anti-malarial activities of anti-haemozoin compounds, Malaria J.20 (64) (2021)1-12.
- Pathak, H. Ojha, A.K. Tiwari, D. Sharma, M.Saini, R. Kakkar, Design, synthesis and biological evaluation of antimalarial activity of new derivatives of 2,4,6-s-triazine, Chem. Cen. J. 11 (2017) 132-143.
- J. Frisch, et al. Gaussian 09, Revision B,01, Gaussian, Inc, Pittsburgh, PA. 2009.
- G.Parr, R.G.Pearson, Absolute hardness: companion parameter to absolute electronegativity, J. Am. Chem. Soc. 105(1983) 7512-7516.
- Lee, W.Yang, R.G. Parr, Development of the Colle-Salvetti correlation energy formula into a functional of the electron density, Phys. Rev. B 37 (1988) 785-789.
- Mauri, V. Consonni, M. Pavan, R. Todeschini, Dragon software: an easy approach to molecular descriptor calculations, MATCH Commun. Math. Comput. Chem. 56 (2006) 237–248.
- Todeschini, V. Consonni, Handbook of Molecular Descriptors, Wiley-VCH, Weinheim (2000) pp. 667-690.
- Consonni, D. Ballabioand, R. Todeschini, Comments on the definition of the Q2 parameter for QSAR validation, J. Chem. Inf. Model 49 (2009) 1669-1678.
- Consonni, D. Ballabioand,R. Todeschini, Evaluation of model predictive ability by external validation techniques, J. Chemometrics 24 (2010)194-201.
- Y. Lee, C.Y. Chen, Toxicity and quantitative structure–activity relationships of benzoic acids to Pseudokirchneriella subcapitata, J. Hazard. Mater. 165 (2009) 156-161.
- Jing, Z. Zhou, J. Zhuo, Quantitative structure-activity relationship (QSAR) study of toxicity of quaternary ammonium compounds on Chlorella pyrenoidosa and Scenedesmus quadricauda, Chemosphere 86 (2012) 76-82.
- Wold S, M. Sjostrom, L. Eriksson, PLS-regression: a basic tool of chemometrics. Chemomet Intell Lab. 58 (2001) 109–130.
- Saghaie, H. Sakhi, H. Sabzyan, M.Shahlaei, D. Shamshirian, Stepwise MLR and PCR QSAR study of the pharmaceutical activities of antimalarial 3-hydroxypyridinone agents using B3LYP/6-311++G** descriptors. Med. Chem. Res. 22 (2013) 1679–1688.
)