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ThinkMind // International Journal On Advances in Life Sciences, volume 4, numbers 1 and 2, 2012 // View article lifsci_v4_n12_2012_4

Identifying the Building Blocks of Protein Structures from Contact Maps Using Protein Sequence and Evolutionary Information

Authors:
Hazem R. Ahmed
Janice I. Glasgow

Keywords: protein structure prediction; contact map; case-based reasoning; evolutionary information; sequence information.

Abstract:
1D protein sequences, 2D contact maps and 3D structures are three different representational levels of detail for proteins. The problem of protein 3D structure prediction from 1D protein sequences remains one of the challenges of modern bioinformatics. The main issue here is that it is computationally complex to reliably predict the full 3D structure of a protein from its 1D sequence. A 2D contact map has, therefore, been used as an intermediate step in this problem. A contact map is a simpler, yet representative, alternative for the 3D protein structure. In this paper, we focus on the problem of identifying similar substructural patterns of protein contact maps (the building blocks of protein structures) using a structural pattern matching approach that incorporates protein sequence and evolutionary information. These substructural patterns are of particular interest to our research, because they could potentially be used as building blocks for a computational bottom-up approach towards the ultimate goal of protein structure prediction from contact maps. The results are benchmarked using a large standard protein dataset. We assess the consistency and the efficiency of identifying these similar substructural patterns by performing different statistical analyses (e.g., Harrell-Davis Quantiles and Bagplots) on different subsets of the experimental results. We further studied the effect of the local sequence information, global sequence information, and evolutionary information on the performance of the method. The results show that both local and global sequence information are more helpful in locating short-range contacts than long-range contacts. Moreover, incorporating evolutionary information has remarkably improved the performance of locating similar short-range contacts between contact map pairs.

Pages: 33 to 43

Copyright: Copyright (c) to authors, 2012. Used with permission.

Publication date: June 30, 2012

Published in: journal

ISSN: 1942-2660
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