Akademik Veri Yönetim Sistemi
Bioorganic and Medicinal Chemistry Reports, sa.5, ss.1-8, 2022 (Hakemli Dergi)
Acetylcholinesterase is the main neurotransmitter in the cholinergic system. Impairment of the cholinergic
system can be a reason for Alzheimer's and multiple sclerosis. Alzheimer's disease and multiple sclerosis affect patients
and their relatives' daily lives enormously. New therapies with more benefits than current therapies for these diseases
would facilitate patients' lives. In this respect, discovering novel acetylcholine esterase inhibitors with more effective and
fewer side effects is highly important. Machine learning algorithms are very useful to predict the activity of molecules
for a biological target. In this study, our classification models were built with Deep Neural Networks (DNN), Support
Vector Machines (SVM), and Extreme Gradient Boosting (XGBoost) to predict molecules as active or inactive for
acetylcholinesterase inhibitors. These models were evaluated with various metrics. As a result, The DNN model showed
a better ability to classify (accuracy=0.93, F1 score=0.88, MCC=0.8, Roc-Auc=0.89 in the test set) molecules than the
other models.