Literature DB >> 15531601

Non-sequential structure-based alignments reveal topology-independent core packing arrangements in proteins.

Xin Yuan1, Christopher Bystroff.   

Abstract

MOTIVATION: Proteins of the same class often share a secondary structure packing arrangement but differ in how the secondary structure units are ordered in the sequence. We find that proteins that share a common core also share local sequence-structure similarities, and these can be exploited to align structures with different topologies. In this study, segments from a library of local sequence-structure alignments were assembled hierarchically, enforcing the compactness and conserved inter-residue contacts but not sequential ordering. Previous structure-based alignment methods often ignore sequence similarity, local structural equivalence and compactness.
RESULTS: The new program, SCALI (Structural Core ALIgnment), can efficiently find conserved packing arrangements, even if they are non-sequentially ordered in space. SCALI alignments conserve remote sequence similarity and contain fewer alignment errors. Clustering of our pairwise non-sequential alignments shows that recurrent packing arrangements exist in topologically different structures. For example, the three-layer sandwich domain architecture may be divided into four structural subclasses based on internal packing arrangements. These subclasses represent an intermediate level of structure classification, more general than topology, but more specific than architecture as defined in CATH. A strategy is presented for developing a set of predictive hidden Markov models based on multiple SCALI alignments.

Mesh:

Substances:

Year:  2004        PMID: 15531601     DOI: 10.1093/bioinformatics/bti128

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  15 in total

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8.  Connectivity independent protein-structure alignment: a hierarchical approach.

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Journal:  BMC Bioinformatics       Date:  2006-11-21       Impact factor: 3.169

9.  MICAN: a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C(α) only models, Alternative alignments, and Non-sequential alignments.

Authors:  Shintaro Minami; Kengo Sawada; George Chikenji
Journal:  BMC Bioinformatics       Date:  2013-01-18       Impact factor: 3.169

10.  A comprehensive analysis of non-sequential alignments between all protein structures.

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Journal:  BMC Struct Biol       Date:  2007-11-16
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