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Devillers J, Larghi A, Sartor V, Setier-Rio ML, Lagneau C, Devillers H. Nonlinear SAR Modelling of Mosquito Repellents for Skin Application. TOXICS 2023; 11:837. [PMID: 37888688 PMCID: PMC10610853 DOI: 10.3390/toxics11100837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/28/2023]
Abstract
Finding new marketable mosquito repellents is a complex and time-consuming process that can be optimized via modelling. In this context, a SAR (Structure-Activity Relationship) model was designed from a set of 2171 molecules whose actual repellent activity against Aedes aegypti was available. Information-rich descriptors were used as input neurons of a three-layer perceptron (TLP) to compute the models. The most interesting classification model was a 20/6/2 TLP showing 94% and 89% accuracy on the training set and test set, respectively. A total of 57 other artificial neural network models based on the same architecture were also computed. This allowed us to consider all chemicals both as training and test set members in order to better interpret the results obtained with the selected model. Most of the wrong predictions were explainable. The 20/6/2 TLP model was then used for predicting the potential repellent activity of new molecules. Among them, two were successfully evaluated in vivo.
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Affiliation(s)
| | - Adeline Larghi
- EID Méditerranée, Direction Technique, 34184 Montpellier, France
| | - Valérie Sartor
- Laboratoire des IMRCP, Université de Toulouse, CNRS UMR 5623, Université Toulouse III-Paul Sabatier, 31062 Toulouse, France
| | | | | | - Hugo Devillers
- SPO, University Montpellier, INRAE, Institut Agro, 34000 Montpellier, France
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Mamy L, Patureau D, Barriuso E, Bedos C, Bessac F, Louchart X, Martin-laurent F, Miege C, Benoit P. Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review. CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2015; 45:1277-1377. [PMID: 25866458 PMCID: PMC4376206 DOI: 10.1080/10643389.2014.955627] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done. The considered processes were water dissolution, dissociation, volatilization, retention on soils and sediments (mainly adsorption and desorption), degradation (biotic and abiotic), and absorption by plants. A total of 790 equations involving 686 structural molecular descriptors are reported to estimate 90 environmental parameters related to these processes. A significant number of equations was found for dissociation process (pKa), water dissolution or hydrophobic behavior (especially through the KOW parameter), adsorption to soils and biodegradation. A lack of QSAR was observed to estimate desorption or potential of transfer to water. Among the 686 molecular descriptors, five were found to be dominant in the 790 collected equations and the most generic ones: four quantum-chemical descriptors, the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest unoccupied molecular orbital (ELUMO), polarizability (α) and dipole moment (μ), and one constitutional descriptor, the molecular weight. Keeping in mind that the combination of descriptors belonging to different categories (constitutional, topological, quantum-chemical) led to improve QSAR performances, these descriptors should be considered for the development of new QSAR, for further predictions of environmental parameters. This review also allows finding of the relevant QSAR equations to predict the fate of a wide diversity of compounds in the environment.
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Affiliation(s)
- Laure Mamy
- INRA-AgroParisTech, UMR 1402 ECOSYS (Ecologie Fonctionnelle et Ecotoxicologie des Agroécosystèmes), Versailles, France
| | - Dominique Patureau
- INRA, UR 0050 LBE (Laboratoire de Biotechnologie de l’Environnement), Narbonne, France
| | - Enrique Barriuso
- INRA-AgroParisTech, UMR 1402 ECOSYS (Ecologie Fonctionnelle et Ecotoxicologie des Aroécosystèmes), Thiverval-Grignon, France
| | - Carole Bedos
- INRA-AgroParisTech, UMR 1402 ECOSYS (Ecologie Fonctionnelle et Ecotoxicologie des Aroécosystèmes), Thiverval-Grignon, France
| | - Fabienne Bessac
- Université de Toulouse – INPT, Ecole d’Ingénieurs de Purpan – UPS, IRSAMCLaboratoire de Chimie et Physique Quantiques – CNRS, UMR 5626, Toulouse, France
| | - Xavier Louchart
- INRA, UMR 1221 LISAH (Laboratoire d’étude des Interactions Sol - Agrosystème – Hydrosystème), Montpellier, France
| | | | | | - Pierre Benoit
- INRA-AgroParisTech, UMR 1402 ECOSYS (Ecologie Fonctionnelle et Ecotoxicologie des Aroécosystèmes), Thiverval-Grignon, France
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Geidl S, Svobodová Vařeková R, Bendová V, Petrusek L, Ionescu CM, Jurka Z, Abagyan R, Koča J. How Does the Methodology of 3D Structure Preparation Influence the Quality of pKa Prediction? J Chem Inf Model 2015; 55:1088-97. [PMID: 26010215 DOI: 10.1021/ci500758w] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The acid dissociation constant is an important molecular property, and it can be successfully predicted by Quantitative Structure-Property Relationship (QSPR) models, even for in silico designed molecules. We analyzed how the methodology of in silico 3D structure preparation influences the quality of QSPR models. Specifically, we evaluated and compared QSPR models based on six different 3D structure sources (DTP NCI, Pubchem, Balloon, Frog2, OpenBabel, and RDKit) combined with four different types of optimization. These analyses were performed for three classes of molecules (phenols, carboxylic acids, anilines), and the QSPR model descriptors were quantum mechanical (QM) and empirical partial atomic charges. Specifically, we developed 516 QSPR models and afterward systematically analyzed the influence of the 3D structure source and other factors on their quality. Our results confirmed that QSPR models based on partial atomic charges are able to predict pKa with high accuracy. We also confirmed that ab initio and semiempirical QM charges provide very accurate QSPR models and using empirical charges based on electronegativity equalization is also acceptable, as well as advantageous, because their calculation is very fast. On the other hand, Gasteiger-Marsili empirical charges are not applicable for pKa prediction. We later found that QSPR models for some classes of molecules (carboxylic acids) are less accurate. In this context, we compared the influence of different 3D structure sources. We found that an appropriate selection of 3D structure source and optimization method is essential for the successful QSPR modeling of pKa. Specifically, the 3D structures from the DTP NCI and Pubchem databases performed the best, as they provided very accurate QSPR models for all the tested molecular classes and charge calculation approaches, and they do not require optimization. Also, Frog2 performed very well. Other 3D structure sources can also be used but are not so robust, and an unfortunate combination of molecular class and charge calculation approach can produce weak QSPR models. Additionally, these 3D structures generally need optimization in order to produce good quality QSPR models.
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Affiliation(s)
- Stanislav Geidl
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
| | - Radka Svobodová Vařeková
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
| | - Veronika Bendová
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
| | - Lukáš Petrusek
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
| | - Crina-Maria Ionescu
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
| | - Zdeněk Jurka
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
| | - Ruben Abagyan
- ‡Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, 9500 Gilman Drive, MC 0657, San Diego, California 92161, United States
| | - Jaroslav Koča
- †National Centre for Biomolecular Research, Faculty of Science, and CEITEC - Central European Institute of Technology, Masaryk University Brno, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic
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Gong W, Liu X, Gao D, Yu Y, Fu W, Cheng D, Cui B, Bai J. The kinetics and QSAR of abiotic reduction of mononitro aromatic compounds catalyzed by activated carbon. CHEMOSPHERE 2015; 119:835-840. [PMID: 25222622 DOI: 10.1016/j.chemosphere.2014.08.043] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2014] [Revised: 08/10/2014] [Accepted: 08/13/2014] [Indexed: 06/03/2023]
Abstract
The kinetics of abiotic reduction of mono-nitro aromatic compounds (mono-NACs) catalyzed by activated carbon (AC) in an anaerobic system were examined. There were 6 types of substituent groups on nitrobenzene, including methyl, chlorine, amino, carboxyl, hydroxyl and cyanogen groups, at the ortho, meta or para positions. Our results showed that reduction followed pseudo-first order reaction kinetics, and that the rate constant (logkSA) varied widely, ranging between -4.77 and -2.82, depending upon the type and position of the substituent. A quantitative structure-activity relationship (QSAR) model using 15 theoretical molecular descriptors and partial-least-squares (PLS) regression was developed for the reduction rates of mono-NACs catalyzed by AC. The cross-validated regression coefficient (Qcum(2), 0.861) and correlation coefficient (R(2), 0.898) indicated significantly high robustness of the model. The VIP (variable importance in the projection) values of energy of the lowest unoccupied molecular orbital (ELUMO) and the maximum net atomic charge on the aromatic carbon bound to the nitro group (QC(-)) were 1.15 and 1.01, respectively. These values indicated that the molecular orbital energies and the atomic net charges might play important roles in the reduction of mono-NACs catalyzed by AC in anaerobic systems.
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Affiliation(s)
- Wenwen Gong
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Xinhui Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China.
| | - Ding Gao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Yanjun Yu
- School of Chemistry, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Wenjun Fu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Dengmiao Cheng
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Baoshan Cui
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Junhong Bai
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
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Masand VH, Mahajan DT, Hadda TB, Jawarkar RD, Chavan H, Bandgar BP, Chauhan H. Molecular docking and quantitative structure–activity relationship (QSAR) analyses of indolylarylsulfones as HIV-1 non-nucleoside reverse transcriptase inhibitors. Med Chem Res 2013. [DOI: 10.1007/s00044-013-0647-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Wang L, Liu XH, Wu D, Xu MZ, Sun T, Cui BS, Yang ZF. Modelling the depuration rates of polychlorinated biphenyls in Oncorhynchus mykiss with quantum chemical descriptors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2009; 20:91-101. [PMID: 19343585 DOI: 10.1080/10629360902726031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Using quantum chemical descriptors and partial least squares regression, a quantitative structure-activity relationship (QSAR) model is developed for the depuration rate constants (log k(d)) of 62 polychlorinated biphenyls (PCBs) in juvenile rainbow trout (Oncorhynchus mykiss). The values of the cross-validated regression coefficient (Qcum(2)) and standard deviation (SD) are 0.655 and 0.05, respectively. The high cross-validated coefficient and low standard deviation indicate that the QSAR model is well predictive. In the QSAR model, the following six descriptors are highly significant: QH(+) (the most positive charge of a hydrogen atom), HOF (standard heat of formation), CCR (core-core repulsion), EE (electronic energy), alpha(2) (squared average molecular polarisability), and S (molecular surface area). The significant descriptors show that the depuration of PCBs in rainbow trout may be mainly attributed to the biota-water partitioning process, and the reactive activity of PCB molecules may play a subordinate role.
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Affiliation(s)
- L Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, People's Republic of China
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