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Diem-Tran PT, Ho TT, Tuan NV, Bao LQ, Phuong HT, Chau TTG, Minh HTB, Nguyen CT, Smanova Z, Casanola-Martin GM, Rasulev B, Pham-The H, Cuong LCV. Stability Constant and Potentiometric Sensitivity of Heavy Metal-Organic Fluorescent Compound Complexes: QSPR Models for Prediction and Design of Novel Coumarin-like Ligands. TOXICS 2023; 11:595. [PMID: 37505560 PMCID: PMC10383909 DOI: 10.3390/toxics11070595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/02/2023] [Accepted: 07/04/2023] [Indexed: 07/29/2023]
Abstract
Industrial wastewater often consists of toxic chemicals and pollutants, which are extremely harmful to the environment. Heavy metals are toxic chemicals and considered one of the major hazards to the aquatic ecosystem. Analytical techniques, such as potentiometric methods, are some of the methods to detect heavy metals in wastewaters. In this work, the quantitative structure-property relationship (QSPR) was applied using a range of machine learning techniques to predict the stability constant (logβML) and potentiometric sensitivity (PSML) of 200 ligands in complexes with the heavy metal ions Cu2+, Cd2+, and Pb2+. In result, the logβML models developed for four ions showed good performance with square correlation coefficients (R2) ranging from 0.80 to 1.00 for the training and 0.72 to 0.85 for the test sets. Likewise, the PSML displayed acceptable performance with an R2 of 0.87 to 1.00 for the training and 0.73 to 0.95 for the test sets. By screening a virtual database of coumarin-like structures, several new ligands bearing the coumarin moiety were identified. Three of them, namely NEW02, NEW03, and NEW07, showed very good sensitivity and stability in the metal complexes. Subsequent quantum-chemical calculations, as well as physicochemical/toxicological profiling were performed to investigate their metal-binding ability and developability of the designed sensors. Finally, synthesis schemes are proposed to obtain these three ligands with major efficiency from simple resources. The three coumarins designed clearly demonstrated capability to be suitable as good florescent chemosensors towards heavy metals. Overall, the computational methods applied in this study showed a very good performance as useful tools for designing novel fluorescent probes and assessing their sensing abilities.
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Affiliation(s)
- Phan Thi Diem-Tran
- Mientrung Institute for Scientific Research, Vietnam National Museum of Nature, Vietnam Academy of Science and Technology, Hue 53000, Vietnam
| | - Tue-Tam Ho
- Faculty of Pharmaceutical Chemistry and Technology, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Nguyen-Van Tuan
- Faculty of Pharmaceutical Chemistry and Technology, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Le-Quang Bao
- Faculty of Pharmaceutical Chemistry and Technology, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Ha Tran Phuong
- Mientrung Institute for Scientific Research, Vietnam National Museum of Nature, Vietnam Academy of Science and Technology, Hue 53000, Vietnam
| | - Trinh Thi Giao Chau
- Mientrung Institute for Scientific Research, Vietnam National Museum of Nature, Vietnam Academy of Science and Technology, Hue 53000, Vietnam
| | - Hoang Thi Binh Minh
- Mientrung Institute for Scientific Research, Vietnam National Museum of Nature, Vietnam Academy of Science and Technology, Hue 53000, Vietnam
| | - Cong-Truong Nguyen
- Faculty of Pharmaceutical Chemistry and Technology, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Zulayho Smanova
- Department of Chemistry, National University of Uzbekistan after Mirzo Ulugbek, Tashkent 100012, Uzbekistan
| | | | - Bakhtiyor Rasulev
- Department of Chemistry, National University of Uzbekistan after Mirzo Ulugbek, Tashkent 100012, Uzbekistan
- Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND 58102, USA
| | - Hai Pham-The
- Faculty of Pharmaceutical Chemistry and Technology, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi 10000, Vietnam
| | - Le Canh Viet Cuong
- Mientrung Institute for Scientific Research, Vietnam National Museum of Nature, Vietnam Academy of Science and Technology, Hue 53000, Vietnam
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Prediction of critical properties of sulfur-containing compounds: New QSPR models. J Mol Graph Model 2020; 101:107700. [PMID: 32927270 DOI: 10.1016/j.jmgm.2020.107700] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 06/22/2020] [Accepted: 07/10/2020] [Indexed: 01/22/2023]
Abstract
In this study, new models have been proposed for the prediction of different critical properties (critical temperature (TC), critical pressure (PC), critical volume (VC), and acentric factor (ω)) of the sulfur-containing compounds based on quantitative structure-property relationship (QSPR). An extensive data set containing experimental data of over 130 different sulfur-containing compounds was employed. Enhanced Replacement Method (ERM) was applied for subset variable selection. Based on ERM selected descriptors, two different models, including linear model and genetic programming (GP) based non-linear model have been proposed for each critical property. The predicted values of each target were in good agreement with the experimental data. For GP-based models, the values of the coefficient of determination (R2) were 0.936, 0.976, 0.990, and 0.917 for TC, PC, VC, and ω, respectively. After revisiting the available QSPR models, it was found that the domain of applicability of new models has been expanded.
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Martynko E, Solov'ev V, Varnek A, Legin A, Kirsanov D. QSPR Modeling of Potentiometric Mg
2+
/Ca
2+
Selectivity for PVC‐plasticized Sensor Membranes. ELECTROANAL 2020. [DOI: 10.1002/elan.201900648] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Ekaterina Martynko
- Institute of ChemistrySaint-Petersburg State University, Peterhof Universitetsky Prospect, 26 Saint-Petersburg 198504 Russia
| | - Vitaly Solov'ev
- A.N. Frumkin Institute of Physical Chemistry and ElectrochemistryRussian Academy of Sciences Leninskiy Prosp., 31 119071 Moscow Russia
| | - Alexandre Varnek
- Laboratoire de Chémoinformatique, UMR 7140 CNRSUniversité de Strasbourg 4, rue Blaise Pascal 67000 Strasbourg France
| | - Andrey Legin
- Institute of ChemistrySaint-Petersburg State University, Peterhof Universitetsky Prospect, 26 Saint-Petersburg 198504 Russia
| | - Dmitry Kirsanov
- Institute of ChemistrySaint-Petersburg State University, Peterhof Universitetsky Prospect, 26 Saint-Petersburg 198504 Russia
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Solov'ev V, Tsivadze A, Marcou G, Varnek A. Classification of Metal Binders by Naïve Bayes Classifier on the Base of Molecular Fragment Descriptors and Ensemble Modeling. Mol Inform 2019; 38:e1900002. [DOI: 10.1002/minf.201900002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 03/15/2019] [Indexed: 12/31/2022]
Affiliation(s)
- Vitaly Solov'ev
- A.N. Frumkin Institute of Physical Chemistry and ElectrochemistryRussian Academy of Sciences, Leninskiy prosp., 31 119071 Moscow Russia
| | - Aslan Tsivadze
- A.N. Frumkin Institute of Physical Chemistry and ElectrochemistryRussian Academy of Sciences, Leninskiy prosp., 31 119071 Moscow Russia
| | - Gilles Marcou
- Laboratoire de Chémoinformatique, UMR 7140 CNRSUniversité de Strasbourg 1, rue Blaise Pascal 67000 Strasbourg France
| | - Alexandre Varnek
- Laboratoire de Chémoinformatique, UMR 7140 CNRSUniversité de Strasbourg 1, rue Blaise Pascal 67000 Strasbourg France
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