Automated multiple structure alignment and detection of a common substructural motif

2001 ◽  
Vol 43 (3) ◽  
pp. 235-245 ◽  
Author(s):  
Nathaniel Leibowitz ◽  
Zipora Y. Fligelman ◽  
Ruth Nussinov ◽  
Haim J. Wolfson
Keyword(s):  
Structure Alignment ◽  
Multiple Structure

scholarly journals Structure-Based Phylogeny of the Metallo-β-Lactamases

2005 ◽  
Vol 49 (7) ◽  
pp. 2778-2784 ◽  
Author(s):  
Gianpiero Garau ◽  
Anne Marie Di Guilmi ◽  
Barry G. Hall
Keyword(s):  
Protein Structure ◽  
Phylogenetic Tree ◽  
Sequence Homology ◽  
Structure Alignment ◽  
Alignment Program ◽  
Homologous Proteins ◽  
Multiple Structure ◽  
Structure Level ◽  
Class B

ABSTRACTThe metallo-β-lactamases fall into two groups: Ambler class B subgroups B1 and B2 and Ambler class B subgroup B3. The two groups are so distantly related that there is no detectable sequence homology between members of the two different groups, but homology is clearly detectable at the protein structure level. The multiple structure alignment program MAPS has been used to align the structures of eight metallo-β-lactamases and five structurally homologous proteins from the metallo-β-lactamase superfamily, and that alignment has been used to construct a phylogenetic tree of the metallo-β-lactamases. The presence of genes fromEubacteria,Archaebacteria, andEukaryotaon that tree is consistent with a very ancient origin of the metallo-β-lactamase family.

MULTIPLE STRUCTURE ALIGNMENT BASED ON GEOMETRICAL CORRELATION OF SECONDARY STRUCTURE ELEMENTS

2010 ◽  
Vol 06 (01) ◽  
pp. 77-95
Author(s):  
TUN-WEN PAI ◽  
RUEI-HSIANG CHANG ◽  
CHIEN-MING CHEN ◽  
PO-HAN SU ◽  
LEE-JYI WANG ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Structural Alignment ◽  
Scoring Function ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Tertiary Structures ◽  
Structural Class ◽  
Mutual Correlation ◽  
Distance Map ◽  
Multiple Structure

Protein structure alignment facilitates the analysis of protein functionality. Through superimposed structures and the comparison of variant components, common or specific features of proteins can be identified. Several known protein families exhibit analogous tertiary structures but divergent primary sequences. These proteins in the same structural class are unable to be aligned by sequence-based methods. The main objective of the present study was to develop an efficient and effective algorithm for multiple structure alignment based on geometrical correlation of secondary structures, which are conserved in evolutionary heritage. The method utilizes mutual correlation analysis of secondary structure elements (SSEs) and selects representative segments as the key anchors for structural alignment. The system exploits a fast vector transformation technique to represent SSEs in vector format, and the mutual geometrical relationship among vectors is projected onto an angle-distance map. Through a scoring function and filtering mechanisms, the best candidates of vectors are selected, and an effective constrained multiple structural alignment module is performed. The correctness of the algorithm was verified by the multiple structure alignment of proteins in the SCOP database. Several protein sets with low sequence identities were aligned, and the results were compared with those obtained by three well-known structural alignment approaches. The results show that the proposed method is able to perform multiple structural alignments effectively and to obtain satisfactory results, especially for proteins possessing low sequence identity.

scholarly journals A new progressive-iterative algorithm for multiple structure alignment

2005 ◽  
Vol 21 (15) ◽  
pp. 3255-3263 ◽  
Author(s):  
D. Lupyan ◽  
A. Leo-Macias ◽  
A. R. Ortiz
Keyword(s):  
Iterative Algorithm ◽  
Structure Alignment ◽  
Multiple Structure
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