Faculty Publications

Title

On complexity of protein structure alignment problem under distance constraint

Document Type

Article

Keywords

alignment algorithms, Protein structure, structural alignment, structural similarity

Journal/Book/Conference Title

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volume

9

Issue

2

First Page

511

Last Page

516

Abstract

We study the well-known Largest Common Point-set (LCP) under Bottleneck Distance Problem. Given two proteins a and b (as sequences of points in three-dimensional space) and a distance cutoff σ, the goal is to find a spatial superposition and an alignment that maximizes the number of pairs of points from a and b that can be fit under the distance σ from each other. The best to date algorithms for approximate and exact solution to this problem run in time O(n 8 ) and O(n 32), respectively, where n represents protein length. This work improves runtime of the approximation algorithm and the expected runtime of the algorithm for absolute optimum for both order-dependent and order-independent alignments. More specifically, our algorithms for near-optimal and optimal sequential alignments run in time O(n 7log n) and O(n 14log n), respectively. For nonsequential alignments, corresponding running times are O(n 7.5) and O(n 14.5). © 2012 IEEE.

Original Publication Date

2-6-2012

DOI of published version

10.1109/TCBB.2011.133

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