Wang, Dan published the artcileSupport vector machine and KStar models predict the o-dealkylation reaction mediated by cytochrome P450, Computed Properties of 33697-81-3, the publication is Wuli Huaxue Xuebao (2011), 27(2), 343-351, database is CAplus.
Nested prediction model was constructed based on support vector machines (SVM) and the KStar method. The models consisted of a mol. shape discriminative model for metabolites, which was used to predict the o-dealkylation reaction mediated by cytochrome P 450, in addition to the metabolic site discriminative model, which was used to judge C-O bond breaking in mols. 1280 Mol. descriptors including topol. descriptors, 2D autocorrelation descriptors, and geometric descriptors were calculated and to characterize the physicochem. properties of 272 mols. A mol. shape discriminative model, represented by the classification models, was constructed by machine learning methods including SVM, decision tree, Bayesian network, and k nearest neighbors method. The results showed that the SVM model was superior to the other methods. Twenty-six quantum chem. features including charge-related, valency-related, and energy-related features were calculated for the 538 metabolism sites for the o-dealkylation reaction in the metabolic site discriminative model. Machine learning methods including decision tree, Bayesian network, KStar, and the artificial neural network method were also used to develop classification models. It showed that the KStar model with its prediction accuracy, sensitivity, and specificity of more than 90% outperformed the other classification models. Fifteen traditional Chinese medicine medicinal mols. were used to validate the model. The results showed that the nested models had certain accuracy and could contribute to the prediction of metabolites from traditional Chinese medicines.
Wuli Huaxue Xuebao published new progress about 33697-81-3. 33697-81-3 belongs to chlorides-buliding-blocks, auxiliary class Chloride,Carboxylic acid,Benzene,Phenol, name is 3-Chloro-4-hydroxyphenylacetic acid, and the molecular formula is C6H3ClFNO2, Computed Properties of 33697-81-3.
Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics