Integrated virtual screening, molecular modeling and machine learning approaches revealed potential natural inhibitors for epilepsy.

ABSTRACT: Epilepsy, a prevalent chronic disorder of the central nervous system, is typified by recurrent seizures. Present treatments predominantly offer symptomatic relief by managing seizures, yet fall short of influencing epileptogenesis. This study endeavored to identify novel phytochemicals with potential therapeutic efficacy against S100B, an influential protein in epileptogenesis, through an innovative application of machine learning-enabled virtual screening. Our study incorporated the use of multiple machine learning algorithms, including Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naive Bayes (NB), and Random Forest (RF). These algorithms were employed not only for virtual screening but also for essential feature extraction and selection, enhancing our ability to distinguish b

SUBMITTER: Alshehri FF 

PROVIDER: S-EPMC10641561 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature