Rapid discovery of Transglutaminase 2 inhibitors for celiac disease with boosting ensemble machine learning.

ABSTRACT: Celiac disease poses a significant health challenge for individuals consuming gluten-containing foods. While the availability of gluten-free products has increased, there is still a need for therapeutic treatments. The advancement of computational drug design, particularly using bio-cheminformatics-oriented machine learning, offers promising avenues for developing such therapies. One promising target is Transglutaminase 2 (TG2), a protein involved in the autoimmune response triggered by gluten consumption. In this study, we utilized data from approximately 1100 TG2 inhibition assays to develop ligand-based molecular screening techniques using ensemble machine-learning models and extensive molecular feature libraries. Various classifiers, including tree-based methods, artificial neural netw

SUBMITTER: Wichka I 

PROVIDER: S-EPMC11532751 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature