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Shape based profiling of fragment collections | 680
Drug Designing: Open Access

Drug Designing: Open Access
Open Access

ISSN: 2169-0138

+44 1223 790975

Shape based profiling of fragment collections


International Conference and Exhibition on Computer Aided Drug Design & QSAR

October 29-31, 2012 DoubleTree by Hilton Chicago-North Shore, USA

Dave Sheppard

Accepted Abstracts: Drug Design

Abstract :

As a method for hit identification, fragment screening offers advantages including greater coverage of chemical space and the potential to identify starting points with higher ligand efficiency. The success of this process is largely driven by the content of the fragment collection. One aspect of this is the shape space covered by the molecules in the dataset. We have developed a series of approaches to assess the shape profiles of fragment collections. Visualisation approaches are used in parallel with a proprietary method, the cube fingerprint approach. For the visualisation, we use enhanced triangle plots, building on the work of Sauer and Schwarz 1 , and simple 3D graphs based on the length, width and thickness of the dataset of molecule conformations. In the cube fingerprint approach, molecule conformations are binned according to their length, width and thickness so as to produce 1 multi-conformer fingerprint per molecule. This facilitates the comparison of multiple compound collections in terms of their flexibility, the coverage of shape space and the efficiency with which this is achieved. The utility of these methods in compound collection comparison will be demonstrated using test cases. Comparing the BioFocus Frag04 dataset (orange) with a commercially available fragment library (green)

Biography :

Dave joined BioFocus in of 2007 to head the CADD group. Through his team, Dave is responsible for the delivery of innovative and high quality computational chemistry data on integrated and stand alone drug discovery projects. Previous companies include Medivir, Protherics/Tularik/Amgen where he worked on protein classes including GPCRs, nuclear hormone receptors, proteases and kinases in hit identification, hit optimisation and lead optimisation phases. Initially educated in Scotland, Dave read chemistry at the University of St Andrews and followed this with a Ph.D at The University of Manchester under the supervision of Professor Ian Hillier and Dr. Neil Burton.

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