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Title: High throughput virtual drug screening using spherical harmonic molecular surface representations
Author: Mavridis, Lazaros
ISNI:       0000 0004 2674 4155
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2009
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This thesis presents new spherical harmonic (SH) approaches for ligand-based high-throughput virtual screening (HTVS). If it is assumed that small drug molecules may be adequately superposed and distinguished by co-locating their centers of mass and by performing rotational correlations of their shapes, then to a good approximation each molecule may be represented very compactly using a two dimensional (2D) SH surface envelope. Of course, this assumes that the true molecular surface is star-like, or single-valued, with respect to radial rays projecting from the selected origin. However, this often holds to a very good approximation for small globular molecules. Even when this is not the case, it is nonetheless reasonable to suppose that similar molecules should give similar radial projections and, therefore, that they should share very similar SH representations. Following this premise, a new program called “SpotLight” was developed. The results obtained with this software show that SH-based global shape matching provides a powerful new way to perform HTVS. SH surface representations are increasingly being applied to a broad range of object recognition and registration tasks, and have also been used to model protein-ligand shape complementarity. Most current shape similarity techniques search for global similarities, and may therefore miss finding active compounds with different overall shapes and sizes but which share similar substructures or surface features. Existing molecular fragment matching algorithms can identify common covalent substructures but they are not well suited for performing scaffold-hopping shape-based database searches. This thesis introduces a novel SH fragment-based shape matching approach that can exploit knowledge of structures of existing protein-ligand complexes to perform virtual screening using as queries SH surface fragments derived from crystallographic ligand binding surfaces.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Drugs ; High throughput screening (Drug development)