QSAR models for describing the toxicological eﬀects of ILs against Staphylococcus aureus based on norm indexes

He, Wensi; Yan, Fangyou; Jia, Qi; Xia, Shuqian; Wang, Qiang

doi:10.1016/j.chemosphere.2017.12.091

Cited by 31 publications

(7 citation statements)

References 62 publications

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“…In order to study the interaction between cations and anions, our previous work regarded the interaction between cations and anions as a mathematical formula composed of ion descriptors. 37,47 Compared with the results in the above literatures, the accuracy of our previous works on the interaction between anions and cations have been significantly improved. Recently, Yan et al 25,48 proposed a new method to express the interaction between anions and cations by calculating descriptors from ILs molecule, which have been successfully applied for QSPR modelling for predicting the heat capacity and the eco-toxicity of ILs.…”

Section: Introductionmentioning

confidence: 83%

Evaluating the properties of ionic liquid at variable temperatures and pressures by QSPR

Zhang

Jia

Yan³

et al. 2020

Preprint

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ILs thermodynamic properties at variable temperature and pressure, such as density, viscosity and thermal conductivity, are necessarily basal parameters of chemical engineering process. In this paper, some norm descriptors-based QSPR models are established to predict the properties of ILs at variable temperature and pressure. The f-T-P models are developed with 9020 data points of 314 ILs for density, 7342 data points of 351 ILs for viscosity and 608 data points of 87 ILs for thermal conductivity. These models have satisfactory statistical results for the calculation of ILs properties. The validation analysis shows that these QSPR models have good stability and predictability. And the norm descriptors are universal for predicting the properties of ILs. Moreover, these QSPR models are applied to predict parameters of f-T-P models for 16329 ILs generated by combing the cations and anions in the dataset, which might be valuable and further used handily by other chemists.

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Section: Introductionmentioning

confidence: 83%

Evaluating the properties of ionic liquid at variable temperatures and pressures by QSPR

Zhang

Jia

Yan³

et al. 2020

Preprint

Self Cite

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“…Hodyna et al [31] developed classification and regression QSAR models with good accuracies, among them the classification method led to better results than the latter [31]. In 2018, He et al [30] presented a QSAR model to predict MIC and MBC values of ILs toward S. aureus. The model was established based on matrix norm indexes, and their system parameters were determined by a multivariate linear regression method.…”

Section: Qsar For the Response Of Bacteriamentioning

confidence: 99%

“…The model could predict the MIC and MBC in the standard error of 0.341 and 0.282 log units, respectively. Similarly, Yan et al [62] which He et al [30] applied, and presented QSAR models to predict MIC and MBC of ILs to C. albicans with the good-of-fitness (R 2 ) of 0.930 and 0.873, respectively. Among bacterial species, the luminescent bacterium V. fischeri was mostly used for toxicity tests of ILs because it is sensitive, simple, and fast.…”

Section: Qsar For the Response Of Bacteriamentioning

confidence: 99%

Quantitative Structure-Activity Relationships to Estimate Toxicity of Ionic Liquids (ILs)

Cho¹,

Stolte²,

Yun³

2019

Encyclopedia of Ionic Liquids

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“…Besides, the norm index descriptor was utilized to describe the interaction between cations and anions. 29,32,33 The QSPR modeling was carried out in this study for a total of 31 different imidazolium IL mixtures, and various rigorous model validation strategies were then performed to ensure the model performance. Through our work, it was expected to provide an efficient approach to evaluate the thermal stability of IL mixtures and provide some guidance for experimental design and mixing of ILs.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, in silico design and data analysis (ISIDA), which represents the molecular structure based on a finite number of topological fragments, , was employed to explore the relationship between target properties and ionic structures. Besides, the norm index descriptor was utilized to describe the interaction between cations and anions. ,, The QSPR modeling was carried out in this study for a total of 31 different imidazolium IL mixtures, and various rigorous model validation strategies were then performed to ensure the model performance. Through our work, it was expected to provide an efficient approach to evaluate the thermal stability of IL mixtures and provide some guidance for experimental design and mixing of ILs.…”

Section: Introductionmentioning

confidence: 99%

Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures

Pan

Meng

et al. 2021

ACS Omega

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Ionic liquids (ILs) have been regarded as "designer solvents" because of their satisfactory physicochemical properties. The 5% onset decomposition temperature (T d , 5%onset ) is one of the most conservative but reliable indicators for characterizing the possible fire hazard of engineered ILs. This study is devoted to develop a quantitative structure−property relationship model for predicting the T d , 5%onset of binary imidazolium IL mixtures. Both in silico design and data analysis descriptors and norm index were employed to encode the structural characteristics of binary IL mixtures. The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. The resulting optimal prediction model was a fourvariable multiple linear equation, with the average absolute error (AAE) for the external test set being 12.673 K. The results of rigorous model validations also demonstrated satisfactory model robustness and predictivity. The present study would provide a new reliable approach for predicting the thermal stability of binary IL mixtures.

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QSAR models for describing the toxicological eﬀects of ILs against Staphylococcus aureus based on norm indexes

Cited by 31 publications

References 62 publications

Evaluating the properties of ionic liquid at variable temperatures and pressures by QSPR

Evaluating the properties of ionic liquid at variable temperatures and pressures by QSPR

Quantitative Structure-Activity Relationships to Estimate Toxicity of Ionic Liquids (ILs)

Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures

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