Discovery of novel NLRP3 inhibitors based on machine learning and physical methods.

ABSTRACT: The NLRP3 inflammasome plays a crucial role in inflammatory responses, particularly in alcohol-related liver disease (ALD). Given that NLRP3 has emerged as a potential therapeutic target for ALD, the development of effective inhibitors is of great importance. In this study, we trained 11 regression models, and the results showed that LightGBM, Random Forest, and XGBoost performed the best, achieving R² values of 0.774, 0.755, and 0.719, respectively. Using machine learning models and physical methods, we screened more than 11.5 million compounds from Asinex, Princeton, UkrOrgSynthesis, Chemdiv, Chembridge, Alinda, Enamine, and Lifechemicals, which led to the identification of 26 potential NLRP3 inhibitors. Furthermore, molecular dynamics simulations and MMGBSA binding energy calculations c

SUBMITTER: Jiang T 

PROVIDER: S-EPMC11520493 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature