AI Article Synopsis
- - The study introduces a flexible framework for discovering structural motifs in proteins, allowing components to be easily modified for various research applications.
- - The approach has two stages: it converts protein 3D shapes into structured sequences and then uses a tool to find conserved patterns in these sequences.
- - A database called SA-Motifbase was created to present conserved structural information, including 3D views and statistical significance of motifs, and is accessible online.
Article Abstract
This study proposes a general framework for structural motif discovery. The framework is based on a modular design in which the system components can be modified or replaced independently to increase its applicability to various studies. It is a two-stage approach that first converts protein 3D structures into structural alphabet sequences, and then applies a sequence motif-finding tool to these sequences to detect conserved motifs. We named the structural motif database we built the SA-Motifbase, which provides the structural information conserved at different hierarchical levels in SCOP. For each motif, SA-Motifbase presents its 3D view; alphabet letter preference; alphabet letter frequency distribution; and the significance. SA-Motifbase is available at http://bioinfo.cis.nctu.edu.tw/samotifbase/.
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| http://dx.doi.org/10.1016/j.compbiomed.2011.10.013 | DOI Listing |
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