کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5556486 | 1403117 | 2017 | 12 صفحه PDF | دانلود رایگان |
Background and objectivePredicting blood-brain barrier permeability for novel compounds is an important goal for neurotherapeutics-focused drug discovery. It is impossible to determine experimentally the blood-brain barrier partitioning of all possible candidates. Consequently, alternative evaluation methods based on computational models are desirable or even necessary. The CORAL software (http://www.insilico.eu/coral) has been checked up as a tool to build up quantitative structure - activity relationships for blood-brain barrier permeation.MethodsThe Monte Carlo technique gives possibility to build up predictive model of an endpoint by means of selection of so-called correlation weights of various molecular features. Descriptors calculated with these weights are basis for correlations “structure â endpoint”.ResultsThe approach gives good models for three random splits into the training and validation sets. The best model characterized by the following statistics for the external validation set: the number of compounds is 41, determination coefficient is equal to 0.896, root mean squared error is equal to 0.175.ConclusionsThe suggested approach can be applied as a tool for prediction of blood-brain barrier permeation.
Journal: Journal of Pharmacological and Toxicological Methods - Volume 88, Part 1, November 2017, Pages 7-18