alexa Hong-yu Li | OMICS International | The University of Ar
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Journal of Developing Drugs
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Hong-yu Li
Hong-yu Li Hong-yu Li
Associate Professor
Department of Pharmacology and Toxicology
University of Arizona

Hong-yu Li is currently an associate professor of Medicinal Chemistry in College of Pharmacy, the University of Arizona. He received his Ph.D. degree from the University of Tokyo, and did his postdoctoral trainings at Columbia University (with Professor Koji Nakanishi) and Harvard University (with Professor Yoshito Kishi). He previously worked at Eli Lilly where he focused on oncology drug discovery.His current research interests are in chemical biology and drug discovery, especially for oncology related targets and phenotypes.In his lab at the University of Arizona, a highly potent (picomolar activity in an oncogene-driven cancer cell line), selective, and orally bioavailable small molecule drug inhibitor was discovered, and is currently ready for preclinical development and further IND filing.

Research Interest

Dr. Li’s research interest is drug discovery and development of kinase inhibitors for rare and/or neglected cancer diseases in a High-Throughput manner. To discover active hits, a novel type of kinase fragment library will be generated in a High-Throughput manner. This kinase fragment library will be designed to overcome most of issues concerning kinase fragment libraries. Compounds identified from the library as an active will be further optimized for better activity and toxicity profiles. The optimization will be done through the library synthesis approach, rather than the industry standard approach of solving SAR (structure-activity relationship) problems one molecule at a time. The one-by-one approach may work well in the beginning of the sequence of the drug discovery value chain, but you may run the risk of encountering the initial problems when trying to solve the next problem. One-cycle library iteration will produce a wide range of SAR information including toxicity for the next library design and production. Three to five cycle iterations of libraries will generate advanced compounds with properties to produce the desired in vivo efficacy with acceptable toxicity profile. The library design approach aided by the computer modeling and calculation will focus on solving any unforeseen SAR problems for each cycle.


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Mining the Association Rules of Transcription Factor Binding Sites in Human Tandem Repeats Using Aprior Algorithm
Zhong-yu Liu, Yi-Yang
Research Article: J Comput Sci Syst Biol 2009, 2: 180-185
DOI: 10.4172/jcsb.1000030
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