Yun Tang

TL;DR: An ADMET structure-activity relationship database that collects, curates, and manages available ADMET-associated properties data from the published literature, and provides a user-friendly interface to query a specific chemical profile, using either CAS registry number, common name, or structure similarity.

TL;DR: Three supervised inference methods were developed here to predict DTI and used for drug repositioning and indicated that these methods could be powerful tools in prediction of DTIs and drugRepositioning.

TL;DR: This update of admetSAR, developed as a comprehensive source and free tool for the prediction of chemical ADMET properties, focuses on extension and optimization of existing models with significant quantity and quality improvement on training data.

TL;DR: This study developed an intensely fluorescent, rapidly responsive, pH-resistant, genetically encoded sensor of wide dynamic range, denoted SoNar, for tracking cytosolic NAD(+) and NADH redox states in living cells and in vivo, and identified KP372-1 as a potent NQO1-mediated redox cycling agent that produced extreme oxidative stress, selectively induced cancer cell apoptosis, and effectively decreased tumor growth in vivo.

TL;DR: A new classification method based on substructure pattern recognition, in which each molecule is represented as a subst structure pattern fingerprint based on a predefined substructure dictionary, and then a support vector machine (SVM) algorithm is applied to build the prediction model.