The overarching goal of the Xu biomedical laboratory is to address unmet healthcare needs and accelerate drug discovery using state-of-the-art computational, informatics, and experimental technologies.

(1) Integrative drug discovery (computational and experimental methods) to detect, predict, and prevent drug-induced toxicities.

Our lab has developed new computational approaches that leverage big data (clinical, pharmacological, and molecular/structural data) in high-throughput drug screening and re-purposing. The use of clinical data in preclinical studies, combined with efficient vertebrate and mammalian animal models (zebrafish, mice, and rats), significantly improves preclinical to clinical translatability and the likelihood of successful drug discovery programs. These new methods are being applied to the search of novel therapeutics that will prevent or mitigate hearing loss, a public health issue affecting 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.

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