NDLI: A local structural alignment algorithm with Variable Length Alignment Fragment Pairs

Content Provider	IEEE Xplore Digital Library
Author	Kundeti, V. Rajasekaran, S.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Univ. of Connecticut, Storrs, CT (Kundeti, V.; Rajasekaran, S.)
Abstract	With the increasing number of protein structures in Protein Data Bank(PDB) efficient and accurate algorithms similar to local alignment of sequences (BLAST) are necessary to classify newly discovered structures into appropriate super families and also to identify structural motifs. Several structural alignment algorithms have been proposed in the literature (DALI, CE, PSIST, TM-Align, etc.). Most of these algorithms perform a global structural alignment between pairs of structures and provide normalized scores which can help in classification of the structures. However they donpsilat address the problem of identification of structural motifs. In this paper we present efficient algorithms for local structural alignment based on a new idea of using Variable Length Alignment Fragment Pairs (VLAFPs) in contrast to Constant Length Alignment Fragment Pairs (CLAFPs) used by all the existing algorithms such as CE, TM-Align, DALI and PSIST. Our VLAFP algorithm is independent of the scoring schemes used to score the CLAFPs and can work with any scoring scheme like the TM-Score. We also introduce two new scoring schemes based on center of gravity of the atoms. Experiment results indicate that using VLAFPs can improve both the quality of local structural alignment and also accuracy of the classification. Using our VLAFP algorithm together with our new scoring schemes we could acheive an average super family accuracy of 84% and a class accuracy of 87% on structures with very less sequence homology.
Starting Page	1
Ending Page	7
File Size	4826873
Page Count	7
File Format	PDF
ISBN	9781424428441
DOI	10.1109/BIBE.2008.4696705
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-08
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Page description languages Gravity Protein engineering Spine Evolution (biology) Computer science Bones
Content Type	Text
Resource Type	Article

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