Effective Search of Triterpenes with Anti-HSV-1 Activity Using a Classification Model by Logistic Regression.

ABSTRACT: Natural products are an excellent source of skeletons for medicinal seeds. Triterpenes and saponins are representative natural products that exhibit anti-herpes simplex virus type 1 (HSV-1) activity. However, there has been a lack of comprehensive information on the anti-HSV-1 activity of triterpenes. Therefore, expanding information on the anti-HSV-1 activity of triterpenes and improving the efficiency of their exploration are urgently required. To improve the efficiency of the development of anti-HSV-1 active compounds, we constructed a predictive model for the anti-HSV-1 activity of triterpenes by using the information obtained from previous studies using machine learning methods. In this study, we constructed a binary classification model (i.e., active or inactive) using a logistic reg

SUBMITTER: Ogawa K 

PROVIDER: S-EPMC8593400 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature