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Alan C. Cheng earned his undergraduate degrees in Electrical Engineering & Computer Science and Molecular Cell Biology at UC Berkeley. He went on to complete his Ph.D. in Biophysics at UC San Francisco. Following his graduate studies, Alan joined Pfizer Global R&D, where he was involved in computer-aided drug design and led small teams in target analysis and the identification of allosteric kinase inhibitors. He joined Amgen in 2006, where he is currently involved in several projects in the oncology and neuroscience areas, primarily working with chemists and biologists in computer-aided design of novel small molecule therapeutics. Alan is also an adjunct faculty member at Brandeis University, where he co-teaches a graduate course on protein structure analysis. He has published a number of papers on structural bioinformatics and structure-based drug design.
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Structure-based prediction of small-molecule druggability
Alan C. Cheng, Amgen
Over half of drug discovery efforts fail in lead identification or in optimization of leads for drug-like properties. We set out to reduce the failure rate by identifying the more druggable targets early on, and discovered that a model based on basic biophysical principles does this very well. The basic idea is to quantitatively estimate the maximal affinity achievable at a given binding site by a small molecule with certain ‘drug-like’ properties. These estimates turn out to correlate reasonably well with drug discovery outcomes and are useful in the prioritization of small-molecule drug targets. Computer-aided approaches that have potential in tackling difficult druggability targets will also be presented.
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