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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1842/4333
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| File |
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Shave2010.doc | File not available for download | 14.27 MB | Microsoft Word | | | Shave2010.pdf | PhD thesis | 13.46 MB | Adobe PDF | View/Open |
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| Title: | Development of high performance structure and ligand based virtual screening techniques |
| Authors: | Shave, Steven R. |
| Supervisor(s): | Walkinshaw, Malcolm Taylor, Paul |
| Issue Date: | 2010 |
| Publisher: | The University of Edinburgh |
| Abstract: | Virtual Sreening (VS) is an in silico technique for drug discovery. An overview of
VS methods is given and is seen to be approachable from two sides: structure based
and ligand based. Structure based virtual screening uses explicit knowledge of the
target receptor to suggest candidate receptor-ligand complexes. Ligand based virtual
screening can infer required characteristics of binders from known ligands. A
consideration for all virtual screening techniques is the amount of computing time
required to arrive at a solution. For this reason, techniques of high performance
computing have been applied to both the structural and ligand based approaches.
A proven structure based virtual screening code LIDAEUS (Ligand Discovery At
Edinburgh University) has been ported and parallelised to a massively parallel
computing platform, the University of Edinburgh’s IBM Bluegene/l, consisting of
2,048 processor cores. A challenge in achieving scaling to such a large number of
processors required implementation of a minimal communication parallel sort
algorithm. Parallel efficiencies achieved within this parallelisation exceeded 99%,
confirming that a near optimum strategy has been followed and capacity for running
the code on a greater number of processors exists. This implementation of the
program has been successfully used with a number of protein targets.
The development of a new ligand based virtual screening code has been completed.
The program UFSRAT (Ultra Fast Shape Recognition with Atom Types) takes the features of known binders and suggests molecules which will be able to make similar
interactions. This similarity method is both fast (1 million molecules per hour per
processor) and independent of input orientation. Along with UFSRAT, some other
methods (VolRAT and UFSRGraph) based on UFSRAT have been developed,
addressing different approaches to ligand based virtual screening. UFSRAT as an
approach to discovering novel protein-ligand complexes has been validated with the
discovery of a number of inhibitors for 11β-Hydroxysteroid Dehydrogenase type 1
and FK binding protein 12. |
| Keywords: | high preformance computing virtual screening structure based virtual screening ligand based virtual screening |
| URI: | http://hdl.handle.net/1842/4333 |
| Appears in Collections: | Biological Sciences thesis and dissertation collection
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