Applications of
Cheminformatics & Chemical Modelling
to Drug Discovery
Moriaud, F



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About Fabrice Moriaud
Fabrice Moriaud joined MEDIT on 2004 as CSO where he is heading the R&D and drug design services. He manages the collaborations with academic groups and with partners in the French competitiveness clusters Medicen. He brought to MEDIT his experience of drug design in interaction with medicinal chemists from Sanofi-Synthelabo and his background in, chemistry, computational chemistry and biochemistry.

From 2002 to 2004, he was a Postdoctoral fellow at Sanofi-Synthelabo (Strasbourg, FR) where he worked as molecular modeler interacting with medicinal chemists. He developed a predictive code and integrated it within a graphical user interface. From 1999 to 2001, he was a postdoctoral fellow at Leiden University (Leiden, NL) where he trained in biochemistry and spectroscopy of proteins. Fabrice holds a Ph.D. in chemistry from the Grenoble Joseph Fourier University. He was hosted at the CEA Grenoble where he used magnetic resonance and quantum chemistry to unravel the magnetic properties of bioinorganic mimics of Iron-sulfur Proteins. He has trained in protein structure determination by nuclear magnetic resonance, quantitative structure-activity relationships and alloys crystallography. He lives in Paris and has one child. He has French nationality.
Abstract
Discover MED-Hybridiser for innovative Fragment-based Drug Design at PDB scale

Fabrice Moriaud, MEDIT

MED-Hybridiser is an innovative software protocol that generates fragment-based chemical compounds by crossing the Protein Data Bank (PDB) and chemical supplier databases.

MED-Hybridiser is based on the validated MED-SuMo technology, a powerful target-based drug design software that compares any interaction surface against the full PDB in a few minutes. Using MED-SuMo makes it possible to retrieve all MED-Portions (fragment compounds from chemical suppliers) exerting 3D local interaction similarities with your protein of interest. Those MED-Portions are then combined in 3D and compared, using fast structure comparison technology, to chemical supplier databases. As an output of MED-Hybridiser, users obtain a large list of innovative compound showing interactions with the 3D target.

By taking advantage of the PDB quadratic growth, MED-Hybridiser is able to generate large numbers of innovative compounds in many cases. Because MED-portions and all output molecules originate from the selected chemical libraries, it produces material that adheres to the medicinal chemistry area. Compared to other de novo methods in fragment-based drug design, MED-hybridiser is the first protocol to take advantage of both chemical information from the PDB and chemical suppliers lists to deliver new active compounds to medicinal chemists.

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