Please use this identifier to cite or link to this item: https://doi.org/10.1142/S0218213005002417
Title: Towards SCALEable protein structure comparison and database search
Authors: Chionh, C.-H.
Huang, Z. 
Tan, K.-L. 
Yao, Z. 
Keywords: Protein structure
Secondary structure elements
Sequence alignment
Similarity search
Structural properties
Issue Date: 2005
Citation: Chionh, C.-H., Huang, Z., Tan, K.-L., Yao, Z. (2005). Towards SCALEable protein structure comparison and database search. International Journal on Artificial Intelligence Tools 14 (5) : 827-848. ScholarBank@NUS Repository. https://doi.org/10.1142/S0218213005002417
Abstract: Comparing protein structures in three dimensions is a computationally expensive process that makes a full scan of a protein against a library of known protein structures impractical. To reduce the cost, we can use an approximation of the three dimensional structure that allows protein comparison to be performed quickly to filter away dissimilar proteins. In this paper, we present a new algorithm, called SCALE, for protein structure comparison. In SCALE, a protein is represented as a sequence of secondary structure elements (SSEs) augmented with 3D structural properties such as the distances and angles between the SSEs. As such, the comparison between two proteins is reduced to a sequence alignment problem between their corresponding sequences of SSEs. The 3-D structural properties of the proteins contribute to the similarity score between the two sequences. We have implemented SCALE, and compared its performance against existing schemes. Our performance study shows that SCALE outperforms existing methods in terms of both efficiency and effectiveness (measured in terms of precision and recall). To avoid exhaustive search, an index based on the structural properties is also proposed. The index prunes away a considerable amount of dissimilar proteins given a query protein. © World Scientific Publishing Company.
Source Title: International Journal on Artificial Intelligence Tools
URI: http://scholarbank.nus.edu.sg/handle/10635/39236
ISSN: 02182130
DOI: 10.1142/S0218213005002417
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