Approximate multiple protein structure alignment using the sum-of-pairs distance.
Jieping Ye,Ravi Janardan +1 more
TL;DR: An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus (pseudo) protein for the set using an approach analogous to the center-star method for multiple sequence alignment.
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Abstract: An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus (pseudo) protein for the set. The algorithm is a heuristic in that it computes an approximation to the optimal multiple structure alignment that minimizes the sum of the pairwise distances between the protein structures. The algorithm chooses an input protein as the initial consensus and computes a correspondence between the protein structures (which are represented as sets of unit vectors) using an approach analogous to the center-star method for multiple sequence alignment. From this correspondence, a set of rotation matrices (optimal for the given correspondence) is derived to align the structures and derive the new consensus. The process is iterated until the sum of pairwise distances converges. The computation of the optimal rotations is itself an iterative process that both makes use of the current consensus and generates simultaneously a new one. This approach is based on an interesting result that allows the sum of all pairwise distances to be represented compactly as distances to the consensus. Experimental results on several protein families are presented, showing that the algorithm converges quite rapidly.
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Citations
MUSTANG: a multiple structural alignment algorithm.
TL;DR: A reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures, based on the progressive pairwise heuristic, which performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins.
Multiple structure alignment and consensus identification for proteins
Jieping Ye,Ivaylo Ilinkin,Ravi Janardan,Adam Isom +3 more
- 11 Sep 2006
TL;DR: An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus structure which captures common substructures present in the given proteins, and it works directly with the coordinate representation in three dimensions with no loss of spatial information.
23
The use of a conformational alphabet for fast alignment of protein structures
Wei-Mou Zheng
- 06 May 2008
TL;DR: Extending the concept of SFPs to that of similar fragment blocks formultiple structure alignment leads to a fast tool for multiple structurealignment called BLOMAPS, which is reliable, and about two or three orders faster than some well-known algorithms.
16
Fast Multiple Alignment of Protein Structures Using Conformational Letter Blocks
Wang Sheng,Zheng Wei-Mou +1 more
TL;DR: The proposed tool, BLOMAPS, is greedy in nature, guided by CLESUM similarity scores, and consists of several steps including finding similar fragment blocks based on a pivot protein, removing block redundancy, constructing scaffold by checking consistency in spatial arrangement among fragments from different blocks, dealing with unanchored structures, and the final step of refinement where the average template for alignment is obtained.
Multiple structure alignment by optimal RMSD implies that the average structure is a consensus.
Xueyi Wang,Jack Snoeyink +1 more
- 01 Jan 2006
TL;DR: This work establishes the properties of the average structure, and shows that an iterative algorithm proposed by Sutcliffe and co-authors can find it efficiently--each iteration takes linear time and the number of iterations is small.
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