Progressive Combinatorial Algorithm for Multiple Structural Alignments:Application to Distantly Related Proteins Maria Elena Ochagavia and Shoshana Wodak.

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Presentation transcript:

Progressive Combinatorial Algorithm for Multiple Structural Alignments:Application to Distantly Related Proteins Maria Elena Ochagavia and Shoshana Wodak PROTEINS:Structure,Function and Bioinformatics, Vol. 55, pp , 2004 Reporter: Chia-Chang Wang Date: Nov. 12, 2004

Introduction MALECON It uses a library of pairwise alignments and proceeds by a combinational approach. The key issue is maximizing the consistency between the pairwise and multiple alignments.

Methods-Constructing the Library of Pairwise Superpositions SoFist input: The atomic coordinate of the two proteins Similarity is Evaluated by RMSD

SoFist(1) Identifying polypeptide segments with similar backbone conformations in both 3D structures

SoFist(2)

SoFist(3)

Methods-Constructing three- protein superpositions

Methods-Extending the Alignment to n-protein

2R

A B

Results

Results(cont.) Trade-off between the number if aligned residues and proteins and alignment consistency

Conclusion When no consistent multiple alignments can be derived for all members of a protein group,this method is useful. To perform a meaningful selection, those might in turn depend on the subsequent use that one wants to make of the multiple alignments.

Thanks for your attention.