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Details

Autor(en) / Beteiligte
Titel
CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds
Ist Teil von
  • PloS one, 2018-01, Vol.13 (1), p.e0191838-e0191838
Ort / Verlag
United States: Public Library of Science
Erscheinungsjahr
2018
Quelle
Free E-Journal (出版社公開部分のみ)
Beschreibungen/Notizen
  • In silico methods of phenotypic screening are necessary to reduce the time and cost of the experimental in vivo screening of anticancer agents through dozens of millions of natural and synthetic chemical compounds. We used the previously developed PASS (Prediction of Activity Spectra for Substances) algorithm to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data. A training set from 59,882 structures of compounds was created based on the experimental data (IG50, IC50, and % inhibition values) from ChEMBL. The average accuracy of prediction (AUC) calculated by leave-one-out and a 20-fold cross-validation procedure during the training was 0.930 and 0.927 for 278 cancer cell lines, respectively, and 0.948 and 0.947 for cytotoxicity prediction for 27 normal cell lines, respectively. Using the given SAR models, we developed a freely available web-service for cell-line cytotoxicity profile prediction (CLC-Pred: Cell-Line Cytotoxicity Predictor) based on the following structural formula: http://way2drug.com/Cell-line/.

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