A method for simultaneous alignment of multiple protein structures

Shatsky, Maxim; Nussinov, Ruth; Wolfson, Haim J.

doi:10.1002/prot.10628

Cited by 414 publications

(344 citation statements)

References 34 publications

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“…The performance of our approach (mulPBA) was extensively assessed against the alignments in HOMSTRAD [50], the reference dataset used to assess the performance of different alignment methods [18,31]. The results of this comparison clearly show that the alignments are improved significantly with mulPBA approach.…”

Section: Resultsmentioning

confidence: 97%

“…This score is termed as N rms . A similar score was used to assess the performance of MULTIPROT [18] (ii) Quantifying the global alignment quality: For each combination of pairwise alignment extracted from the multiple alignment, the number of aligned residue pairs that are within a distance of 3.5Å was counted. An average was then calculated for all the pairwise alignments, this score was named as N 3.5 .…”

Section: Multiple Alignment Scoresmentioning

confidence: 99%

“…The length of these fragments is either predefined [13][14][15][16] or constrained by a measure for structural similarity between fragments [17,18]. The most common and efficient technique for sequence order dependant comparisons, is dynamic programming [9,13,15,17,19].…”

Section: Introductionmentioning

confidence: 99%

“…Few other approaches are not dependant on the order of protein fragments, the structural similarity and the relative orientation of these fragments being the major constraint for comparison. They are mainly based on algorithms like geometric hashing [10,18,20,21], Monte Carlo Optimization [5], graph-matching [11] etc. These methods detect relationships based on sequence permutations and recombinations.…”

Section: Introductionmentioning

confidence: 99%

“…Another set of methods compute a simultaneous comparison of all structures without using a hierarchical procedure or a reference structure [10,18,20]. The latter group works by using techniques like geometric hashing [33] to identify the set of structural regions common for all structures.…”

Section: Introductionmentioning

confidence: 99%

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Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

2012

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Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a 1D sequence string.A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition.Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods.3

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Section: Resultsmentioning

confidence: 97%

Section: Multiple Alignment Scoresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

2012

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Comparative Protein Structure Modeling Using MODELLER

Webb

Šali

2014

CP in Bioinformatics

900

474

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Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

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Structure Comparison and Alignment

Bourne

Shindyalov

2003

Structural Bioinformatics

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Since the 1970s, after the seminal work of Rossmann and Argos (1978) comparing binding sites of known enzyme structures, the comparison and alignment of protein structures has come to be a fundamental and widely used task in computational structure biology. Three main steps are needed for comparing two protein structures: first, the detection of their common similarities; second, the alignment of the structures based on such similarities; and third, a statistical measure of the similarity. Considering the first two steps, structure comparison refers to the analysis of the similarities and differences between two or more structures, and structure alignment refers to establishing which amino acid residues are equivalent between them. The majority of commonly used methods do a reasonably good job in recognizing obvious similarities between protein structures. However, the alignment of two or more structures is a more difficult task, and its accuracy may depend on the method or program used as well as what the user is trying to accomplish, which will be discussed subsequently. All programs that are briefly described in this chapter perform both steps and are commonly known as protein structure alignment methods.It is also important to immediately clear up any confusion between structure alignment and structure superposition since such terms are often interchanged in the literature. As mentioned above, structure alignment tries to identify the equivalences between pairs of amino acid residues from the structures to superpose, while structure superposition requires the previous knowledge of such equivalences. Thus, structure superposition tries to solve the simpler geometrical task of minimizing the distance between already known equivalent residues of the superimposed structures by finding a transformation that produces either the lowest root-mean-square deviation (RMSD) or the maximal equivalences within an

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A method for simultaneous alignment of multiple protein structures

Cited by 414 publications

References 34 publications

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

Comparative Protein Structure Modeling Using MODELLER

Structure Comparison and Alignment

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