Artymiuk, P.J., Bath, P.A., Grindley, H.M., Pepperrell, C.A., Poirrette, A.R., Rice, D.W., Thorner, D.A., Wild, D.J., Willett, P., Allen, F.H. and Taylor, R. (1992) Similarity searching in databases of three-dimensional molecules and macromolecules. Journal of Chemical Information and Computer Sciences, 32 (6). pp. 617-630. ISSN 0095-2338Full text not available from this repository.
This paper discusses algorithmic techniques for measuring the degree of similarity between pairs of threedimensional (3-D) chemical molecules represented by interatomic distance matrices. A comparison of four methods for the calculation of 3-D structural similarity suggests that the most effective one is a procedure that identifies pairs of atoms, one from each of the molecules that are being compared, that lie at the center of geometrically-related volumes of 3-D space. This atom mapping method enables the calculation of a wide range of types of intermolecular similarity coefficient, including measures that are based on physicochemical data. Massively-parallel implementations of the method are discussed, using the AMT Distributed Array Processor, that achieve a substantial increase in performance when compared with a sequential implementation on a UNIX workstation. Current work involves the use of angular information and the extension of the method to field-based similarity searching. Similarity searching in 3-D macromolecules is effected by the use of a maximal common subgraph (MCS) isomorphism algorithm with a novel, graph-based representation of the tertiary structures of proteins. This algorithm is being used to identify similarities between the 3-D structures of proteins in the Brookhaven Protein Data Bank; its use is exemplified by searches involving the NAD-binding fold motif.
|Academic Units:||The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)|
|Depositing User:||Information Studies|
|Date Deposited:||17 Aug 2009 10:55|
|Last Modified:||17 Aug 2009 10:55|
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