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Multiple structure alignment with msTALI.

Shealy P, Valafar H - BMC Bioinformatics (2012)

Bottom Line: Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification.We also demonstrate success at building a database of protein cores using 341 randomly selected CATH domains and highlight the contribution of msTALI compared to the CATH classifications.In addition to its performance on standard comparison databases, it utilizes clear, informative features, allowing further customization for domain-specific applications.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA.

ABSTRACT

Background: Multiple structure alignments have received increasing attention in recent years as an alternative to multiple sequence alignments. Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification. A method that is capable of solving a variety of problems using structure comparison is still absent. Here we introduce a program msTALI for aligning multiple protein structures. Our algorithm uses several informative features to guide its alignments: torsion angles, backbone Cα atom positions, secondary structure, residue type, surface accessibility, and properties of nearby atoms. The algorithm allows the user to weight the types of information used to generate the alignment, which expands its utility to a wide variety of problems.

Results: msTALI exhibits competitive results on 824 families from the Homstrad and SABmark databases when compared to Matt and Mustang. We also demonstrate success at building a database of protein cores using 341 randomly selected CATH domains and highlight the contribution of msTALI compared to the CATH classifications. Finally, we present an example applying msTALI to the problem of detecting hinges in a protein undergoing rigid-body motion.

Conclusions: msTALI is an effective algorithm for multiple structure alignment. In addition to its performance on standard comparison databases, it utilizes clear, informative features, allowing further customization for domain-specific applications. The C++ source code for msTALI is available for Linux on the web at http://ifestos.cse.sc.edu/mstali.

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Aligned structures from a Rossmann fold. The conserved cores (top) and fully aligned structures (bottom) for the Rossmann fold family from SABmark, as aligned by Matt, Mustang, and msTALI. Only four structures are illustrated for clarity. Figures are rendered using PyMol [33].
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Figure 4: Aligned structures from a Rossmann fold. The conserved cores (top) and fully aligned structures (bottom) for the Rossmann fold family from SABmark, as aligned by Matt, Mustang, and msTALI. Only four structures are illustrated for clarity. Figures are rendered using PyMol [33].

Mentions: The data presented in Tables 4 and 5 and Figure3 conclude that msTALI performs significantly better on the two comparison databases used for analysis. However, an example can be informative. Here we illustrate msTALI on a Rossmann fold [32] group from SABmark. The alignments produced by Mustang, Matt, and msTALI are shown in Figure4. The core Rossmann fold is known to consist of a β-sheet of at least three strands enclosed by at least two α-helices. msTALI has correctly aligned the five central β-strands and the three surrounding α-helices. A fourth α-helix, in the top-right portion of the image, is partially conserved as well. In contrast, Matt has only aligned one β-strand and two α-helices. Mustang does somewhat better, aligning three β- sheets and two α-helices. However, it has also aligned α-helices from some structures with β-sheets of other structures. Furthermore, several of the secondary structures are not properly matched, resulting in a poor fit of the core between structures. The msTALI core contains 110 residues and a backbone RMSD of 2.2 Å. This is significantly better than cores identified by Matt, which has 54 residues and an RMSD of 3.5 Å, and Mustang, which has 110 residues and an RMSD of 4.5 Å.


Multiple structure alignment with msTALI.

Shealy P, Valafar H - BMC Bioinformatics (2012)

Aligned structures from a Rossmann fold. The conserved cores (top) and fully aligned structures (bottom) for the Rossmann fold family from SABmark, as aligned by Matt, Mustang, and msTALI. Only four structures are illustrated for clarity. Figures are rendered using PyMol [33].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3473313&req=5

Figure 4: Aligned structures from a Rossmann fold. The conserved cores (top) and fully aligned structures (bottom) for the Rossmann fold family from SABmark, as aligned by Matt, Mustang, and msTALI. Only four structures are illustrated for clarity. Figures are rendered using PyMol [33].
Mentions: The data presented in Tables 4 and 5 and Figure3 conclude that msTALI performs significantly better on the two comparison databases used for analysis. However, an example can be informative. Here we illustrate msTALI on a Rossmann fold [32] group from SABmark. The alignments produced by Mustang, Matt, and msTALI are shown in Figure4. The core Rossmann fold is known to consist of a β-sheet of at least three strands enclosed by at least two α-helices. msTALI has correctly aligned the five central β-strands and the three surrounding α-helices. A fourth α-helix, in the top-right portion of the image, is partially conserved as well. In contrast, Matt has only aligned one β-strand and two α-helices. Mustang does somewhat better, aligning three β- sheets and two α-helices. However, it has also aligned α-helices from some structures with β-sheets of other structures. Furthermore, several of the secondary structures are not properly matched, resulting in a poor fit of the core between structures. The msTALI core contains 110 residues and a backbone RMSD of 2.2 Å. This is significantly better than cores identified by Matt, which has 54 residues and an RMSD of 3.5 Å, and Mustang, which has 110 residues and an RMSD of 4.5 Å.

Bottom Line: Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification.We also demonstrate success at building a database of protein cores using 341 randomly selected CATH domains and highlight the contribution of msTALI compared to the CATH classifications.In addition to its performance on standard comparison databases, it utilizes clear, informative features, allowing further customization for domain-specific applications.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA.

ABSTRACT

Background: Multiple structure alignments have received increasing attention in recent years as an alternative to multiple sequence alignments. Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification. A method that is capable of solving a variety of problems using structure comparison is still absent. Here we introduce a program msTALI for aligning multiple protein structures. Our algorithm uses several informative features to guide its alignments: torsion angles, backbone Cα atom positions, secondary structure, residue type, surface accessibility, and properties of nearby atoms. The algorithm allows the user to weight the types of information used to generate the alignment, which expands its utility to a wide variety of problems.

Results: msTALI exhibits competitive results on 824 families from the Homstrad and SABmark databases when compared to Matt and Mustang. We also demonstrate success at building a database of protein cores using 341 randomly selected CATH domains and highlight the contribution of msTALI compared to the CATH classifications. Finally, we present an example applying msTALI to the problem of detecting hinges in a protein undergoing rigid-body motion.

Conclusions: msTALI is an effective algorithm for multiple structure alignment. In addition to its performance on standard comparison databases, it utilizes clear, informative features, allowing further customization for domain-specific applications. The C++ source code for msTALI is available for Linux on the web at http://ifestos.cse.sc.edu/mstali.

Show MeSH
Related in: MedlinePlus