COMP 60 |
| Erin K. Bradley1, Erik Evensen1, Hans Purkey1, Ken Lind1, Andrew C. Braisted2, and Michelle R. Arkin3. (1) Computational Sciences, Sunesis Pharmaceuticals Inc, 341 Oyster Point Blvd., South San Francisco, CA 94080, (2) Chemistry, Sunesis Pharmaceuticals Inc, 341 Oyster Point Blvd., South San Francisco, CA 94080, (3) Biology, Sunesis Pharmaceuticals Inc, 341 Oyster Point Blvd., South San Francisco, CA 94080 |
| Protein-protein binding interfaces are considered improbable sites for high-affinity small molecule ligands; yet this target class represents the majority of therapeutically relevant targets. Until recently, understanding the binding properties at protein-protein interfaces has been limited to structural and mutational analysis. We will present a computational method, that when combined with tethering data, can be used to identify sites to exploit for small molecule binding. The method uses simple descriptors and informational data mining techniques, and produces a ranking of binding sites (and in most cases initial selection of anchoring fragments). We will compare this technique to high-throughput virtual screening, and demonstrate the utility on several targets, including IL2. |
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Computational Chemistry in Drug Discovery: Are High Information Content Calculations Better than Low Information Content Calculations?
1:30 PM-4:35 PM, Monday, September 8, 2003 Javits Convention Center -- 1E13, Oral
Division of Computers in Chemistry |