Research

The overarching goal of the Xu Drug Discovery Lab is to address unmet healthcare needs and accelerate drug discovery using state-of-the-art computational, data science, and experimental technologies.

(1) Integrative Drug Discovery for the Prevention and Treatment of Drug-Induced and Noise-Induced Hearing Loss.

We have developed novel computational approaches that leverage big data (clinical, gene expression, pharmacological, and molecular data) for high-throughput drug screening and repurposing. Combined with proven animal models (zebrafish and rodents), our integrative drug discovery pipeline significantly improves screening efficiency, preclinical-to-clinical translatability, and as a result the likelihood of successful drug discovery programs. These new methods are being applied to the search of novel therapeutics that will prevent or restore hearing loss that affects 15% Americans and 500 million people worldwide.

(2) Software Development of the ezCADD Web Drug Discovery Platform

State-of-the-art computational methods are being implemented into the ezCADD web drug discovery platform, designed to empower non-computational biomedical researchers around the world. ezCADD delivers a rapid, rich, smooth, dynamic, and desktop-like WYSIWYG ("what you see is what you get") modeling experience using a web browser with jobs completed within the human interactive time scale (seconds to minutes). Key features include web-based 2D/3D molecular visualization, structure-based and ligand-based drug design, molecular docking, high-throughput virtual screening, cheminformatics, bioinformatics, homology modeling, molecular dynamics, free energy calculations, machine learning, AWS cloud computing support, etc.