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- Cummings, M
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| Frank Hollinger, Locus Pharmaceuticals |
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Dr. Frank Hollinger joined Locus Pharmaceuticals in 2000 as employee number 3. Locus is currently hovering around 50 employees, with a full R&D shop which has harnessed the Locus’ proprietary drug discovery technology to deliver their first IND in 2006. Today, as Director of the Computational Chemistry group at Locus, he leads a talented group of scientists whose primary responsibility includes the application of Locus’ fragment based drug design software toward the successful design of lead molecules and their optimization into IND candidates for both internal programs and programs done with collaborators.
Prior to joining Locus, he spent over 7 years focusing on a variety of pharmaceutical targets at Wyeth Research and Schering-Plough Research Institute with a focus on structure based and ligand based drug design approaches.
Dr. Hollinger obtained a Ph.D. in chemistry from Columbia University in 1993 where he combined computational design of host-guest complexes with synthetic chemistry to enable him to synthesize the molecules he designed. Dr. Hollinger also holds a M.S. in Medicinal Chemistry from Stevens Institute of Technology where he focused on synthesizing potential anti-viral and anti-microbial compounds.
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Harnessing the power of Structure Based Drug Design using a Fragment Based Approach
Frank Hollinger, Locus Pharmaceuticals
Prospective structure based drug design is one of the more challenging aspects of drug discovery. A powerful design process has been developed which allows the identification and optimization of novel, diverse and potent ligands with druggable properties. This design process has been made possible by harnessing the power of fragment centered structure based drug design.
The development of a novel grand canonical Monte Carlo (GCMC) simulation paradigm permits the generation of binding free energies for fragments to a protein. The output of such a simulation provides all the information necessary to accurately identify high affinity interaction sites, binding sites and druggable binding sites on a protein surface. This computational approach also enables the design team to understand the role of water (just another fragment in our paradigm) and to take full advantage of that information. Using novel analysis tools we are able to combine fragments into synthetically accessible drug-like molecules for evaluation against a desired protein target. A case study will be presented describing the design of novel, potent and selective allosteric inhibitors for p38-alpha. Experimental data will be presented which validates our process of using fragment based ligand design approaches to identify leads and optimize their properties.
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