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Aided Mol. Design, 20(12): 773-788 (2006) Fig. 1. Structure-based 3D pharmacophore derived from PDB complex 1KE7 (cyclin-dependent kinase 2) with the original ligand and virtual screening hits accurately identified and aligned using the presented virtual screening approach. Rhodes, September 19-24, 2010 55 ORAL PRESENTATION 3 RECOVERING DESIGN STRATEGIES OF GPCRs MODULATORS FROM EXPLORATIONS OF THE CHEMICAL SPACE Antonio Macchiarulo1, Chiara Custodi1, Roberto Nuti1, Tudor Oprea2, Roberto Pellicciari1 1 Dipartimento di Chimica e Tecnologia del Farmaco, University of Perugia.

References: [1] Review in: J. Bajorath, L. Peltason, M. Wawer, R. Guha, M. S. Lajiness, J. H. van Drie, Drug Discovery Today 2009, 14, 698. [2] A. G. D. Jones, D. A. Cosgrove, P. W. Kenny, L. Ruston, P. MacFaul, J. M. Colclough, B. Law, J. Med. Chem. 2006, 49, 6672. 58 18th European Symposium on Quantitative Structure-Activity Relationships ORAL PRESENTATION 6 BIOPHYSICS-BASED LIBRARY DESIGN: DISCOVERY OF “NON-ACID” INHIBITORS OF S1 DHFR Veer Shanmugasundaram*, Kris Borzilleri, Jeanne Chang, Boris Chrunyk, Mark Flanagan, Seungil Han, Melissa Harris, Brian Lacey, Richard Miller, Parag Sahasrabudhe, Ron Sarver, Holly Soutter, Jane Withka Antibacterials Chemistry/Discovery Technologies, Pfizer PharmaTherapeutics Research & Development, Groton, CT - 06333, USA Methicillin-resistant Staphylococcus aureus (MRSA), the causative agent of many serious nosocomial and community acquired infections, and other gram-positive organisms can show resistance to trimethoprim (TMP) through mutation of the chromosomal gene or acquisition of an alternative DHFR termed "S1 DHFR" To develop new therapies for health threats such as MRSA, it is important to understand the molecular basis of TMP resistance and use that knowledge to design and develop novel inhibitors that are effective against S1 DHFR.

A distinguishing element of our approach is that the core organizing principles are not derived by automated means but by the medicinal chemists themselves, thus striking an optimal balance between automation and flexibility. Collectively, these tools allow the user to get a “bird’s-eye” view of the chemical space spanned by a particular data set, map and aggregate any physicochemical property or biological activity of interest onto the individual scaffolds and/or substituents, understand scaffold, R-group, and individual substituent effects across multiple biological dimensions, and quickly distinguish promising parts of the molecule from less interesting or problematic ones.

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18th European Symposium on Quantitative Structure – Activity Relationships by n a


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