progressive combinatorial algorithm for multiple structural alignments:application to distantly...
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![Page 1: Progressive Combinatorial Algorithm for Multiple Structural Alignments:Application to Distantly Related Proteins Maria Elena Ochagavia and Shoshana Wodak](https://reader035.vdocuments.net/reader035/viewer/2022070323/56649d365503460f94a0e1c8/html5/thumbnails/1.jpg)
Progressive Combinatorial Algorithm for Multiple Structural Alignments:Application to Distantly Related Proteins
Maria Elena Ochagavia and Shoshana WodakPROTEINS:Structure,Function and Bioinformatics, Vol. 55, pp. 436-454, 2004
Reporter: Chia-Chang WangDate: Nov. 12, 2004
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Introduction
MALECONIt 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.
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Methods-Constructing the Library of Pairwise Superpositions
SoFistinput:
The atomic coordinate of the two proteinsSimilarity is Evaluated by RMSD
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SoFist(1)
Identifying polypeptide segments with similar backbone conformations in both 3D structures
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SoFist(2)
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SoFist(3)
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Methods-Constructing three-protein superpositions
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Methods-Extending the Alignment to n-protein
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ije
2R
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A
B
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Results
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Results(cont.)
Trade-off between the number if aligned residues and proteins and alignment consistency
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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.
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Thanks for your attention.