QSAR studies about cytotoxicity of benzophenazines with dual inhibition toward both topoisomerases I and II: 3D-MoRSE descriptors and statistical considerations about variable selection

Saı́z-Urra, Liane; González, Maykel Pérez; Teijeira, Marta

doi:10.1016/j.bmc.2006.05.081

Cited by 59 publications

(29 citation statements)

References 48 publications

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“…The 3D-MoRSE (3D-Molecule Representation of Structures based on Electron diffraction, descriptor Mor26e in this case) descriptors afford the possibility for choosing an appropriate atomic property [20]. They present the advantage that they code with fixed-length representation of 3D molecular structure, allowing the comparison of data sets comprising molecules of different size, and number of atoms.…”

Section: Resultsmentioning

confidence: 99%

<strong>QSAR MODELING ON FUNGICIDAL ACTIVITY OF MANNICH BASES</strong>

Funar-Timofei

Borota

Bora

et al. 2015

Proceedings of the 19th International Electronic Conference on Synthetic Organic Chemistry

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Section: Resultsmentioning

confidence: 99%

<strong>QSAR MODELING ON FUNGICIDAL ACTIVITY OF MANNICH BASES</strong>

Funar-Timofei

Borota

Bora

et al. 2015

Proceedings of the 19th International Electronic Conference on Synthetic Organic Chemistry

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“…However, the value and sign of the 3D-MoRSE descriptor depend, to a large extent, on the values of s and r ij . 49 Thus, it could not be concluded that atomic volumes have a specific effect on the λ max values, either negative or positive, only taking into account the coefficient sign of the descriptor. When the coefficient and the descriptor have the same sign, the contribution of the descriptor is positive, else, negative.…”

Section: Resultsmentioning

confidence: 99%

QSPR Study of the Absorption Maxima of Azobenzene Dyes

Wang²,

Liu³

et al. 2011

Bulletin of the Korean Chemical Society

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A quantitative structure-property relationship (QSPR) study was performed for the prediction of the absorption maxima of azobenzene dyes. The entire set of 191 azobenzenes was divided into a training set of 150 azobenzenes and a test set of 41 azobenzenes according to Kennard and Stones algorithm. A seven-descriptor model, with squared correlation coefficient (R 2 ) of 0.8755 and standard error of estimation (s) of 14.476, was developed by applying stepwise multiple linear regression (MLR) analysis on the training set. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-many-out crossvalidation procedure, randomization tests, and validation through the test set.

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“…Mor17m retains important structural features such as the [49] Thus, it could not be concluded that atomic masses have a specific effect on the K salt values, either negative or positive, only taking into account the coefficient sign of the descriptor. When the coefficient and the descriptor have the same sign, the contribution of the descriptor is positive, else, negative.…”

Section: Descriptor Contribution Analysis and Interpretationmentioning

confidence: 93%

QSPR study of Setschenow constants of organic compounds using MLR, ANN, and SVM analyses

Wang

et al. 2011

J Comput Chem

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A quantitative structure-property relationship (QSPR) study was performed for the prediction of the Setschenow constants (K(salt)) by sodium chloride of organic compounds. The entire set of 101 compounds was randomly divided into a training set of 71 compounds and a test set of 30 compounds. Multiple linear regression, artificial neural network (ANN), and support vector machine (SVM) were utilized to build the linear and nonlinear QSPR models, respectively. The obtained models with four descriptors involved show good predictive ability. The linear model fits the training set with R(2) = 0.8680, while ANN and SVM higher values of R(2) = 0.8898 and 0.9302, respectively. The validation results through the test set indicate that the proposed models are robust and satisfactory. The QSPR study suggests that the molecular lipophilicity is closely related to the Setschenow constants.

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QSAR studies about cytotoxicity of benzophenazines with dual inhibition toward both topoisomerases I and II: 3D-MoRSE descriptors and statistical considerations about variable selection

Cited by 59 publications

References 48 publications

<strong>QSAR MODELING ON FUNGICIDAL ACTIVITY OF MANNICH BASES</strong>

<strong>QSAR MODELING ON FUNGICIDAL ACTIVITY OF MANNICH BASES</strong>

QSPR Study of the Absorption Maxima of Azobenzene Dyes

QSPR study of Setschenow constants of organic compounds using MLR, ANN, and SVM analyses

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