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Euldji I, Benmouloud W, Paduszyński K, Si-Moussa C, Benkortbi O. Hybrid Improved Grey Wolf Support Vector Regression Algorithm for Modeling Solubilities of APIs in Pure Ionic Liquids: σ-Profile Descriptors. J Chem Inf Model 2024; 64:1361-1376. [PMID: 38314703 DOI: 10.1021/acs.jcim.3c01876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
The objective of this study was to model the solubility of active pharmaceutical ingredients (APIs) in different ionic liquids (ILs) based on the σ-moments of cations, anions, and APIs that were used as molecular descriptors calculated using the σ-profiles of three categories of descriptors based on conductor-like screening model for real solvents. The database of 83 API-ILs systems composed of 14 APIs, 12 cations, and 7 anions (25 ILs combinations) was collected as 850 data points at different temperature ranges. A hybrid Improved Grey Wolf Support vector regression, abbreviated as I-GWO-SVR(r), algorithm was selected as the learning method. Based on a comprehensive comparison with 11 different models, various statistical factors, and graphical analyses, including an external validation test, analysis of variance (ANOVA), and sensitivity analysis, the capability and validity of the proposed approach have been assessed and verified. The overall study confirmed that the proposed new model provided the best results in terms of predicting the solubility of APIs in ILs.
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Affiliation(s)
- Imane Euldji
- Faculty of Technology, Department of Process and Environmental Engineering, Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Yahia Fares, Medea 26000, Algeria
| | - Widad Benmouloud
- Faculty of Technology, Department of Process and Environmental Engineering, Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Yahia Fares, Medea 26000, Algeria
| | - Kamil Paduszyński
- Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw, Poland
| | - Chérif Si-Moussa
- Faculty of Technology, Department of Process and Environmental Engineering, Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Yahia Fares, Medea 26000, Algeria
| | - Othmane Benkortbi
- Faculty of Technology, Department of Process and Environmental Engineering, Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Yahia Fares, Medea 26000, Algeria
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2
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Liu X, Wang X, Yu M, Jia Q, Yan F, Wang Q. QSPR Model to Predict the Speed of Sound of Ionic Liquids as a Function of Variable Temperature and Pressure. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.3c00570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
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3
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Wu JQ, Gong XQ, Wang Q, Yan F, Li JJ. A QSPR study for predicting θ(LCST) and θ(UCST) in binary polymer solutions. Chem Eng Sci 2023. [DOI: 10.1016/j.ces.2022.118326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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4
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Jia Q, Wang J, Yan F, Wang Q. A QSTR model for toxicity prediction of pesticides towards Daphnia magna. CHEMOSPHERE 2022; 291:132980. [PMID: 34813852 DOI: 10.1016/j.chemosphere.2021.132980] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 11/15/2021] [Accepted: 11/17/2021] [Indexed: 06/13/2023]
Abstract
Because of the large amount of pesticides discharged into rivers, adverse effects could be induced to aquatic organisms. Daphnia magna is often used as an indicator organism to evaluate the toxicity of pesticides. In this study, a quantitative structure-toxicity relationship (QSTR) model was established based on norm descriptors for predicting the acute toxicity of pesticides to Daphnia magna. The model results showed the good predictability (Rtraining2 = 0.8045, Rtesting2 = 0.8224). The validation results of internal validation, external validation, Y-randomization test and application domain analysis demonstrated the model's stability, reliability and robustness. Therefore, the above results indicate that norm descriptors might be universal for describing the relationship between the toxicity and structures of pesticides compounds. Moreover, some pesticides' toxicities without experimental data were also predicted by this model.
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Affiliation(s)
- Qingzhu Jia
- School of Marine and Environmental Science, Tianjin Marine Environmental Protection and Restoration Technology Engineering Center, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Junli Wang
- School of Marine and Environmental Science, Tianjin Marine Environmental Protection and Restoration Technology Engineering Center, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Fangyou Yan
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China.
| | - Qiang Wang
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
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5
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Shi Y, Li JJ, Wang Q, Jia Q, Yan F, Luo ZH, Zhou YN. Computer-aided estimation of kinetic rate constant for degradation of volatile organic compounds by hydroxyl radical: An improved model using quantum chemical and norm descriptors. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2021.117244] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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6
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Shi Y, Wang J, Wang Q, Jia Q, Yan F, Luo ZH, Zhou YN. Supervised Machine Learning Algorithms for Predicting Rate Constants of Ozone Reaction with Micropollutants. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.1c04697] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Yajuan Shi
- Department of Chemical Engineering, School of Chemistry and Chemical Engineering, State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China
| | - Jiang Wang
- Department of Chemical Engineering, School of Chemistry and Chemical Engineering, State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China
| | - Qiang Wang
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, Tianjin, 300457, P. R. China
| | - Qingzhu Jia
- School of Marine and Environmental Science, Tianjin University of Science and Technology, Tianjin, 300457, P. R. China
| | - Fangyou Yan
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, Tianjin, 300457, P. R. China
| | - Zheng-Hong Luo
- Department of Chemical Engineering, School of Chemistry and Chemical Engineering, State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China
| | - Yin-Ning Zhou
- Department of Chemical Engineering, School of Chemistry and Chemical Engineering, State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China
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7
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Wen H, Su Y, Wang Z, Jin S, Ren J, Shen W, Eden M. A systematic modeling methodology of deep neural network‐based structure‐property relationship for rapid and reliable prediction on flashpoints. AIChE J 2021. [DOI: 10.1002/aic.17402] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Huaqiang Wen
- School of Chemistry and Chemical Engineering Chongqing University Chongqing China
| | - Yang Su
- School of Intelligent Technology and Engineering Chongqing University of Science and Technology Chongqing China
| | - Zihao Wang
- Process Systems Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany
| | - Saimeng Jin
- School of Chemistry and Chemical Engineering Chongqing University Chongqing China
| | - Jingzheng Ren
- Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong
| | - Weifeng Shen
- School of Chemistry and Chemical Engineering Chongqing University Chongqing China
| | - Mario Eden
- Department of Chemical Engineering Auburn University Auburn AL USA
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Paduszyński K. Extensive Databases and Group Contribution QSPRs of Ionic Liquid Properties. 3: Surface Tension. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c00783] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Kamil Paduszyński
- Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw, Poland
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9
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Toropova AP, Toropov AA, Benfenati E. The self-organizing vector of atom-pairs proportions: use to develop models for melting points. Struct Chem 2021. [DOI: 10.1007/s11224-021-01778-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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10
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Zhang S, Jia Q, Yan F, Xia S, Wang Q. Evaluating the properties of ionic liquid at variable temperatures and pressures by quantitative structure–property relationship (QSPR). Chem Eng Sci 2021. [DOI: 10.1016/j.ces.2020.116326] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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11
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Koi ZK, Yahya WZN, Kurnia KA. Prediction of ionic conductivity of imidazolium-based ionic liquids at different temperatures using multiple linear regression and support vector machine algorithms. NEW J CHEM 2021. [DOI: 10.1039/d1nj01831k] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The conductivity of various imidazolium-based ILs has been predicted via QSPR approach using MLR and SVM regression coupled with stepwise model-building. This will aid the screening of suitable ILs with desired conductivity for specific applications.
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Affiliation(s)
- Zi Kang Koi
- Department of Chemical Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak Darul Ridzuan, Malaysia
| | - Wan Zaireen Nisa Yahya
- Department of Chemical Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak Darul Ridzuan, Malaysia
- Center of Research in Ionic Liquids, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak Darul Ridzuan, Malaysia
| | - Kiki Adi Kurnia
- Department of Chemical Engineering, Faculty of Industrial Technology, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung 40132, Indonesia
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Lan T, Yan X, Yan F, Xia S, Jia Q, Wang Q. Norm index in QSTR work for predicting toxicity of ionic liquids on Vibrio fischeri. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2020; 205:111187. [PMID: 32853869 DOI: 10.1016/j.ecoenv.2020.111187] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 07/26/2020] [Accepted: 08/14/2020] [Indexed: 06/11/2023]
Abstract
Ionic liquids have been becoming new 'green solvent' because of the low saturation vapor pressure, less volatilization and more recycling utilization. Since most ILs are soluble in water, it should be indispensable to evaluate the ecotoxicology effect of ILs on aquatic environment before using them widely. Based on the concept of norm index, a set of norm descriptors were proposed for anions, cations and ILs. The whole IL structure optimization method has been used to build a predictive norm index-based quantitative structure-toxicity relationship model for the toxicity of ILs on Vibrio fischeri. Statistical results indicated that norm descriptors were reliable and robust in expressing the relationship between structural information and toxicity of ILs. Meanwhile, a series of ILs without experimental values were predicted based on this stable QSTR model. The results indicated that for imidazole-based ILs, an increase in the length of substituent in the branch could enhance the toxicity of ILs on Vibrio fischeri, and the branch contains hydroxyl group, double bond or triple bonds might reduce the toxicity of ILs. Results obtained in this present work would be valuable for the molecular design and the toxicity evaluation toward aquatic organism of ILs.
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Affiliation(s)
- Tian Lan
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Xue Yan
- School of Marine and Environmental Science, Tianjin Marine Environmental Protection and Restoration Technology Engineering Center, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Fangyou Yan
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China.
| | - Shuqian Xia
- Key Laboratory for Green Chemical Technology of the State Education Ministry, School of Chemical Engineering and Technology, Tianjin University, 300072, Tianjin, China.
| | - Qingzhu Jia
- School of Marine and Environmental Science, Tianjin Marine Environmental Protection and Restoration Technology Engineering Center, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Qiang Wang
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
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13
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Liu T, Yan F, Jia Q, Wang Q. Norm index-based QSAR models for acute toxicity of organic compounds toward zebrafish embryo. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2020; 203:110946. [PMID: 32888619 DOI: 10.1016/j.ecoenv.2020.110946] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/11/2020] [Accepted: 06/23/2020] [Indexed: 06/11/2023]
Abstract
Zebrafish embryos are highly sensitive to toxicant exposure and have been used to evaluate the potential eco-toxicity caused by organic pollutants in the aquatic environment. This study was to develop four quantitative structure-activity relationship (QSAR) models based on norm descriptors for acute toxicity of different exposure times toward zebrafish embryo of organic compounds with various structures. Norm descriptors were obtained by calculating the norm index of the atomic distribution matrix, which was composed of atomic spatial distribution and atomic properties. These norm index-based QSAR models presented satisfactory results with R2 of 0.8549, 0.9162, 0.8335 and 0.8119 for 48, 96, 120 and 132 h, respectively. Validation results including cross validation, external validation, Y-randomized test and applicability domain analysis indicated that the proposed models were stable, robust and reliable. Accordingly, these norm descriptors might be effective in predicting the acute toxicity of various organics to zebrafish embryos, which might be useful for evaluating the potential hazards of organic pollutants to aquatic environment.
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Affiliation(s)
- Ting Liu
- School of Marine and Environmental Science, Tianjin Marine Environmental Protection and Restoration Technology Engineering Center, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Fangyou Yan
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
| | - Qingzhu Jia
- School of Marine and Environmental Science, Tianjin Marine Environmental Protection and Restoration Technology Engineering Center, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China.
| | - Qiang Wang
- School of Chemical Engineering and Material Science, Tianjin University of Science and Technology, 13St. 29, TEDA, 300457, Tianjin, PR China
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