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Proteins comparison through probabilistic optimal structure local alignment.

Micale G, Pulvirenti A, Giugno R, Ferro A - Front Genet (2014)

Bottom Line: Only the distances between all pairs of residues in the structures are computed.To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures.We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Pisa Pisa, Italy.

ABSTRACT
Multiple local structure comparison helps to identify common structural motifs or conserved binding sites in 3D structures in distantly related proteins. Since there is no best way to compare structures and evaluate the alignment, a wide variety of techniques and different similarity scoring schemes have been proposed. Existing algorithms usually compute the best superposition of two structures or attempt to solve it as an optimization problem in a simpler setting (e.g., considering contact maps or distance matrices). Here, we present PROPOSAL (PROteins comparison through Probabilistic Optimal Structure local ALignment), a stochastic algorithm based on iterative sampling for multiple local alignment of protein structures. Our method can efficiently find conserved motifs across a set of protein structures. Only the distances between all pairs of residues in the structures are computed. To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures. We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs. PROPOSAL is available as a Java 2D standalone application or a command line program at http://ferrolab.dmi.unict.it/proposal/proposal.html.

No MeSH data available.


Related in: MedlinePlus

Outline of PROPOSAL.
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Figure 1: Outline of PROPOSAL.

Mentions: Finally, in the third phase, the alignment is refined, by iteratively removing and adding single nodes to each aligned motif. This refinement phase produces the final local alignment (see Figure 1). The set of local alignments is then filtered by removing highly overlapping alignments.


Proteins comparison through probabilistic optimal structure local alignment.

Micale G, Pulvirenti A, Giugno R, Ferro A - Front Genet (2014)

Outline of PROPOSAL.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4151033&req=5

Figure 1: Outline of PROPOSAL.
Mentions: Finally, in the third phase, the alignment is refined, by iteratively removing and adding single nodes to each aligned motif. This refinement phase produces the final local alignment (see Figure 1). The set of local alignments is then filtered by removing highly overlapping alignments.

Bottom Line: Only the distances between all pairs of residues in the structures are computed.To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures.We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Pisa Pisa, Italy.

ABSTRACT
Multiple local structure comparison helps to identify common structural motifs or conserved binding sites in 3D structures in distantly related proteins. Since there is no best way to compare structures and evaluate the alignment, a wide variety of techniques and different similarity scoring schemes have been proposed. Existing algorithms usually compute the best superposition of two structures or attempt to solve it as an optimization problem in a simpler setting (e.g., considering contact maps or distance matrices). Here, we present PROPOSAL (PROteins comparison through Probabilistic Optimal Structure local ALignment), a stochastic algorithm based on iterative sampling for multiple local alignment of protein structures. Our method can efficiently find conserved motifs across a set of protein structures. Only the distances between all pairs of residues in the structures are computed. To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures. We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs. PROPOSAL is available as a Java 2D standalone application or a command line program at http://ferrolab.dmi.unict.it/proposal/proposal.html.

No MeSH data available.


Related in: MedlinePlus