TarDict: RandomForestClassifier-based software predict Drug-Tartget interaction in human Based on drug simplified molecular-input line-entry system (SMILES)
Peter Tharwat HabibiD, Alsamman M. AlsammaniD, Sameh E. HassaneiniD, Aladdin HamwiehiD
Abstract
Predicting the target of unknown or/and drugs under investigation from data of already identified drugs is very important not only for the understanding of various drug and molecular interaction processes but also for the development of novel drugs. Here we introduce TarDict, a RandomForestClassifier based-software predict the target pathway or protein based on SMILES of chemical. TarDict receives SMILES and returns a list of the possible similar drug, then export list to the user the target that drug contribute in. Training data set of 20442 entry and testing reveal %95 accuracy.
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