Quantitative structure–toxicity relationship models for predication of toxicity of ionic liquids toward leukemia rat cell line IPC-81 based on index of ideality of correlation

References

• Abramenko N, Kustov L, Metelytsia L, Kovalishyn V, Tetko I, Peijnenburg W. 2020. A review of recent advances towards the development of QSAR models for toxicity assessment of ionic liquids. J Hazard Mater. 384:121429.
   PubMed Web of Science ®Google Scholar
• Achary P, Toropova A, Toropov A. 2019. Combinations of graph invariants and attributes of simplified molecular input-line entry system (SMILES) to build up models for sweetness. Food Res Int. 122:40–46.
   PubMed Web of Science ®Google Scholar
• Ahmadi S. 2012. A QSPR study of association constants of macrocycles toward sodium cation. Macroheterocycles. 5(1):23–31.
   Web of Science ®Google Scholar
• Ahmadi S. 2020. Mathematical modeling of cytotoxicity of metal oxide nanoparticles using the index of ideality correlation criteria. Chemosphere. 242:125192.
   PubMed Web of Science ®Google Scholar
• Ahmadi S, Aghabeygi S, Farahmandjou M, Azimi N. 2021. The predictive model for band gap prediction of metal oxide nanoparticles based on quasi-SMILES. Struct Chem. 32(5):1893–1813.
   Web of Science ®Google Scholar
• Ahmadi S, Akbari A. 2018. Prediction of the adsorption coefficients of some aromatic compounds on multi-wall carbon nanotubes by the Monte Carlo method. SAR QSAR Environ Res. 29(11):895–909.
   PubMed Web of Science ®Google Scholar
• Ahmadi S, Ghanbari H, Lotfi S, Azimi N. 2021. Predictive QSAR modeling for the antioxidant activity of natural compounds derivatives based on Monte Carlo method. Mol Divers. 25(1):87–11.
   PubMed Web of Science ®Google Scholar
• Ahmadi S, Toropova AP, Toropov AA. 2020. Correlation intensity index: mathematical modeling of cytotoxicity of metal oxide nanoparticles. Nanotoxicology. 14(8):1118–1126.
   PubMed Web of Science ®Google Scholar
• Bagri K, Kumar A, Nimbhal M, Kumar P. 2020. Index of ideality of correlation and correlation contradiction index: a confluent perusal on acetylcholinesterase inhibitors. Mol Simul. 46(10):777–786.
   Web of Science ®Google Scholar
• Bubalo MC, Radošević K, Redovniković IR, Halambek J, Srček VG. 2014. A brief overview of the potential environmental hazards of ionic liquids. Ecotoxicol Environ Saf. 99:1–12.
   PubMed Web of Science ®Google Scholar
• Bubalo MC, Radošević K, Srček VG, Das RN, Popelier P, Roy K. 2015. Cytotoxicity towards CCO cells of imidazolium ionic liquids with functionalized side chains: preliminary QSTR modeling using regression and classification based approaches. Ecotoxicol Environ Saf. 112:22–28.
   PubMed Web of Science ®Google Scholar
• Cao L, Zhu P, Zhao Y, Zhao J. 2018. Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids. J Hazard Mater. 352:17–26.
   PubMed Web of Science ®Google Scholar
• Chirico N, Gramatica P. 2011. Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient. J Chem Inf Model. 51(9):2320–2335.
   PubMed Web of Science ®Google Scholar
• Cho CW, Pham TPT, Zhao Y, Stolte S, Yun YS. 2021. Review of the toxic effects of ionic liquids. Sci Total Environ. 786:147309.
   PubMed Web of Science ®Google Scholar
• Cho CW, Ranke J, Arning J, Thöming J, Preiss U, Jungnickel C, Diedenhofen M, Krossing I, Stolte S. 2013. In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions. SAR QSAR Environ Res. 24(10):863–882.
   PubMed Web of Science ®Google Scholar
• Cho CW, Stolte S, Yun YS. 2016. Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors. Sci Rep. 6(1):33403–33409.
   PubMedGoogle Scholar
• Farahani SR, Sohrabi MR, Ghasemi JB. 2018. A detailed structural study of cytotoxicity effect of ionic liquids on the leukemia rat cell line IPC-81 by three dimensional quantitative structure toxicity relationship. Ecotoxicol Environ Saf. 158:256–265.
   PubMed Web of Science ®Google Scholar
• Fatemi MH, Izadiyan P. 2011a. Cytotoxicity estimation of ionic liquids based on their effective structural features. Chemosphere. 84(5):553–563.
   PubMed Web of Science ®Google Scholar
• Fatemi MH, Izadiyan P. 2011b. In silico cytotoxicity estimation of ionic liquids based on their two-and three-dimensional structural descriptors. Monatsh Chem. 142(11):1111–1119.
   Web of Science ®Google Scholar
• Flieger J, Flieger M. 2020. Ionic liquids toxicity—benefits and threats. Int J Mol Sci. 21(17):6267.
   Web of Science ®Google Scholar
• Frade RF, Matias A, Branco LC, Afonso CA, Duarte CM. 2007. Effect of ionic liquids on human colon carcinoma HT-29 and CaCo-2 cell lines. Green Chem. 9(8):873–877.
   Web of Science ®Google Scholar
• García-Lorenzo A, Tojo E, Tojo J, Teijeira M, Rodríguez-Berrocal FJ, González MP, Martínez-Zorzano VS. 2008. Cytotoxicity of selected imidazolium-derived ionic liquids in the human Caco-2 cell line. Sub-structural toxicological interpretation through a QSAR study. Green Chem. 10(5):508–516.
   Web of Science ®Google Scholar
• Ghaedi A. 2015. Predicting the cytotoxicity of ionic liquids using QSAR model based on SMILES optimal descriptors. J Mol Liq. 208:269–279.
   Web of Science ®Google Scholar
• Ghiasi T, Ahmadi S, Ahmadi E, Talei Bavil Olyai M, Khodadadi Z. 2021. The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors. SAR QSAR Environ Res. 32(6):495–520.
   PubMed Web of Science ®Google Scholar
• Gupta S, Basant N, Singh KP. 2015. Nonlinear QSAR modeling for predicting cytotoxicity of ionic liquids in leukemia rat cell line: an aid to green chemicals designing. Environ Sci Pollut Res Int. 22(16):12699–12710.
   PubMed Web of Science ®Google Scholar
• Jastorff B, Mölter K, Behrend P, Bottin-Weber U, Filser J, Heimers A, Ondruschka B, Ranke J, Schaefer M, Schröder H, et al. 2005. Progress in evaluation of risk potential of ionic liquids—basis for an eco-design of sustainable products. Green Chem. 7(5):362–372.
   Web of Science ®Google Scholar
• Javidfar M, Ahmadi S. 2020. QSAR modelling of larvicidal phytocompounds against Aedes aegypti using index of ideality of correlation. SAR QSAR Environ Res. 31(10):717–739.
   PubMed Web of Science ®Google Scholar
• Kumar A, Kumar P. 2020a. Quantitative structure toxicity analysis of ionic liquids toward acetylcholinesterase enzyme using novel QSTR models with index of ideality of correlation and correlation contradiction index. J Mol Liq. 318:114055.
   Web of Science ®Google Scholar
• Kumar A, Kumar P. 2021a. Cytotoxicity of quantum dots: use of quasiSMILES in development of reliable models with index of ideality of correlation and the consensus modelling. J Hazard Mater. 402:123777.
   PubMed Web of Science ®Google Scholar
• Kumar P, Kumar A. 2020b. CORAL: QSAR models of CB1 cannabinoid receptor inhibitors based on local and global SMILES attributes with the index of ideality of correlation and the correlation contradiction index. Chemometr Intelligent Lab Syst. 200:103982.
   Web of Science ®Google Scholar
• Kumar P, Kumar A. 2021b. Correlation intensity index (CII) as a benchmark of predictive potential: construction of quantitative structure activity relationship models for anti-influenza single-stranded DNA aptamers using Monte Carlo optimization. J Mol Struct. 1246:131205.
   Web of Science ®Google Scholar
• Kumar P, Kumar A, Sindhu J. 2019. In silico design of diacylglycerol acyltransferase-1 (DGAT1) inhibitors based on SMILES descriptors using Monte-Carlo method. SAR QSAR Environ Res. 30(8):525–541.
   PubMed Web of Science ®Google Scholar
• Kumar P, Kumar A, Sindhu J, Lal S. 2019. QSAR models for nitrogen containing monophosphonate and bisphosphonate derivatives as human farnesyl pyrophosphate synthase inhibitors based on Monte Carlo method. Drug Res (Stuttg). 69(3):159–167.
   PubMed Web of Science ®Google Scholar
• Lawrence I, Lin K. 1992. Assay validation using the concordance correlation coefficient. Biometrics. 48(2):599–604.
   Web of Science ®Google Scholar
• Lotfi S, Ahmadi S, Kumar P. 2021. A hybrid descriptor based QSPR model to predict the thermal decomposition temperature of imidazolium ionic liquids using Monte Carlo approach. J Mol Liq. 338:116465.
   Web of Science ®Google Scholar
• Lotfi S, Ahmadi S, Zohrabi P. 2020. QSAR modeling of toxicities of ionic liquids toward Staphylococcus aureus using SMILES and graph invariants. Struct Chem. 31(6):2257–2270.
   Web of Science ®Google Scholar
• Ma L, Lin Q, Song Y, Zhao B, Fan M. 2020. Toxic effect of three imidazole ionic liquids on two terrestrial plants. Open Life Sci. 15(1):466–475.
   PubMed Web of Science ®Google Scholar
• Matzke M, Stolte S, Thiele K, Juffernholz T, Arning J, Ranke J, Welz-Biermann U, Jastorff B. 2007. The influence of anion species on the toxicity of 1-alkyl-3-methylimidazolium ionic liquids observed in an (eco) toxicological test battery. Green Chem. 9(11):1198–1207.
   Web of Science ®Google Scholar
• Radošević K, Cvjetko M, Kopjar N, Novak R, Dumić J, Srček VG. 2013. In vitro cytotoxicity assessment of imidazolium ionic liquids: biological effects in fish Channel Catfish Ovary (CCO) cell line. Ecotoxicol Environ Saf. 92:112–118.
   PubMed Web of Science ®Google Scholar
• Ranke J, Mölter K, Stock F, Bottin-Weber U, Poczobutt J, Hoffmann J, Ondruschka B, Filser J, Jastorff B. 2004. Biological effects of imidazolium ionic liquids with varying chain lengths in acute Vibrio fischeri and WST-1 cell viability assays. Ecotoxicol Environ Saf. 58(3):396–404.
   PubMed Web of Science ®Google Scholar
• Ranke J, Müller A, Bottin-Weber U, Stock F, Stolte S, Arning J, Störmann R, Jastorff B. 2007. Lipophilicity parameters for ionic liquid cations and their correlation to in vitro cytotoxicity. Ecotoxicol Environ Saf. 67(3):430–438.
   PubMed Web of Science ®Google Scholar
• Ranke J, Stolte S, Störmann R, Arning J, Jastorff B. 2007. Design of sustainable chemical products-the example of ionic liquids. Chem Rev. 107(6):2183–2206.
   PubMed Web of Science ®Google Scholar
• Shayanfar A, Shayanfar S. 2014. Is regression through origin useful in external validation of QSAR models? Eur J Pharm Sci. 59:31–35.
   PubMed Web of Science ®Google Scholar
• Sivapragasam M, Moniruzzaman M, Goto M. 2020. An overview on the toxicological properties of ionic liquids toward microorganisms. Biotechnol J. 15(4):1900073.
   Web of Science ®Google Scholar
• Sosnowska A, Grzonkowska M, Puzyn T. 2017. Global versus local QSAR models for predicting ionic liquids toxicity against IPC-81 leukemia rat cell line: the predictive ability. J Mol Liq. 231:333–340.
   Web of Science ®Google Scholar
• Stolte S, Arning J, Bottin-Weber U, Matzke M, Stock F, Thiele K, Uerdingen M, Welz-Biermann U, Jastorff B, Ranke J. 2006. Anion effects on the cytotoxicity of ionic liquids. Green Chem. 8(7):621–629.
   Web of Science ®Google Scholar
• Stolte S, Matzke M, Arning J, Böschen A, Pitner W-R, Welz-Biermann U, Jastorff B, Ranke J. 2007. Effects of different head groups and functionalised side chains on the aquatic toxicity of ionic liquids. Green Chem. 9(11):1170–1179.
   Web of Science ®Google Scholar
• Tetko IV, Sushko I, Pandey AK, Zhu H, Tropsha A, Papa E, Oberg T, Todeschini R, Fourches D, Varnek A. 2008. Critical assessment of QSAR models of environmental toxicity against Tetrahymena pyriformis: focusing on applicability domain and overfitting by variable selection. J Chem Inf Model. 48(9):1733–1746.
   PubMed Web of Science ®Google Scholar
• Toropov AA, Toropova AP. 2018. Improved model for biodegradability of organic compounds: the correlation contributions of rings. Toxicity and biodegradation testing. Springer: Berlin, Germany; p. 147–183.
   Google Scholar
• Toropov AA, Toropova AP. 2019. The Correlation Contradictions Index (CCI): building up reliable models of mutagenic potential of silver nanoparticles under different conditions using quasi-SMILES. Sci Total Environ. 681:102–109.
   PubMed Web of Science ®Google Scholar
• Toropova AP, Toropov AA. 2014. CORAL software: prediction of carcinogenicity of drugs by means of the Monte Carlo method. Eur J Pharm Sci. 52:21–25.
   PubMed Web of Science ®Google Scholar
• Ventura SP, Marques CS, Rosatella AA, Afonso CA, Goncalves F, Coutinho JA. 2012. Toxicity assessment of various ionic liquid families towards Vibrio fischeri marine bacteria. Ecotoxicol Environ Saf. 76(2):162–168.
   PubMed Web of Science ®Google Scholar
• Veselinović JB, Đorđević V, Bogdanović M, Morić I, Veselinović AM. 2018. QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria. Struct Chem. 29(2):541–551.
   Web of Science ®Google Scholar
• Wang X, Ohlin CA, Lu Q, Fei Z, Hu J, Dyson PJ. 2007. Cytotoxicity of ionic liquids and precursor compounds towards human cell line HeLa. Green Chem. 9(11):1191–1197.
   Web of Science ®Google Scholar
• Wu T, Li W, Chen M, Zhou Y, Zhang Q. 2020. Estimation of ionic liquids toxicity against leukemia rat cell line IPC‐81 based on the empirical‐like models using intuitive and explainable fingerprint descriptors. Mol Inf. 39(10):2000102.
   Web of Science ®Google Scholar
• Yan F, Lan T, Yan X, Jia Q, Wang Q. 2019. Norm index-based QSTR model to predict the eco-toxicity of ionic liquids towards Leukemia rat cell line. Chemosphere. 234:116–122.
   PubMed Web of Science ®Google Scholar
• Yan F, Xia S, Wang Q, Ma P. 2012. Predicting the toxicity of ionic liquids in leukemia rat cell line by the quantitative structure–activity relationship method using topological indexes. Ind Eng Chem Res. 51(43):13897–13901.
   Web of Science ®Google Scholar
• Yu M, Wang SH, Luo YR, Han YW, Li XY, Zhang BJ, Wang JJ. 2009. Effects of the 1-alkyl-3-methylimidazolium bromide ionic liquids on the antioxidant defense system of Daphnia magna. Ecotoxicol Environ Saf. 72(6):1798–1804.
   PubMed Web of Science ®Google Scholar
• Zhao D, Liao Y, Zhang Z. 2007. Toxicity of ionic liquids. Clean Soil Air Water. 35(1):42–48.
   Web of Science ®Google Scholar
• Zhao Y, Zhao J, Huang Y, Zhou Q, Zhang X, Zhang S. 2014. Toxicity of ionic liquids: database and prediction via quantitative structure-activity relationship method. J Hazard Mater. 278:320–329.
   PubMed Web of Science ®Google Scholar
• Zhu S, Yu P, Lei M, Tong Y, Zheng L, Zhang R, Ji J, Chen Q, Wu Y. 2013. Investigation of the toxicity of the ionic liquid 1-butyl-3-methylimidazolium chloride to Saccharomyces cerevisiae AY93161 for lignocellulosic ethanol production. Polish J Chem Technol. 15(2):94–98.
   Web of Science ®Google Scholar