Literature DB >> 22168237

MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts.

Xin Deng1, Jianlin Cheng.   

Abstract

BACKGROUND: Multiple Sequence Alignment (MSA) is a basic tool for bioinformatics research and analysis. It has been used essentially in almost all bioinformatics tasks such as protein structure modeling, gene and protein function prediction, DNA motif recognition, and phylogenetic analysis. Therefore, improving the accuracy of multiple sequence alignment is important for advancing many bioinformatics fields.
RESULTS: We designed and developed a new method, MSACompro, to synergistically incorporate predicted secondary structure, relative solvent accessibility, and residue-residue contact information into the currently most accurate posterior probability-based MSA methods to improve the accuracy of multiple sequence alignments. The method is different from the multiple sequence alignment methods (e.g. 3D-Coffee) that use the tertiary structure information of some sequences since the structural information of our method is fully predicted from sequences. To the best of our knowledge, applying predicted relative solvent accessibility and contact map to multiple sequence alignment is novel. The rigorous benchmarking of our method to the standard benchmarks (i.e. BAliBASE, SABmark and OXBENCH) clearly demonstrated that incorporating predicted protein structural information improves the multiple sequence alignment accuracy over the leading multiple protein sequence alignment tools without using this information, such as MSAProbs, ProbCons, Probalign, T-coffee, MAFFT and MUSCLE. And the performance of the method is comparable to the state-of-the-art method PROMALS of using structural features and additional homologous sequences by slightly lower scores.
CONCLUSION: MSACompro is an efficient and reliable multiple protein sequence alignment tool that can effectively incorporate predicted protein structural information into multiple sequence alignment. The software is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

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Year:  2011        PMID: 22168237      PMCID: PMC3299741          DOI: 10.1186/1471-2105-12-472

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  49 in total

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2.  LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA.

Authors:  Michael Brudno; Chuong B Do; Gregory M Cooper; Michael F Kim; Eugene Davydov; Eric D Green; Arend Sidow; Serafim Batzoglou
Journal:  Genome Res       Date:  2003-03-12       Impact factor: 9.043

3.  The CHAOS/DIALIGN WWW server for multiple alignment of genomic sequences.

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Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

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Authors:  Nak-Kyeong Kim; Jun Xie
Journal:  J Comput Biol       Date:  2006-12       Impact factor: 1.479

6.  Probalign: multiple sequence alignment using partition function posterior probabilities.

Authors:  Usman Roshan; Dennis R Livesay
Journal:  Bioinformatics       Date:  2006-09-05       Impact factor: 6.937

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Journal:  Methods Enzymol       Date:  1996       Impact factor: 1.600

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Journal:  J Mol Biol       Date:  1994-02-04       Impact factor: 5.469

9.  DIALIGN-T: an improved algorithm for segment-based multiple sequence alignment.

Authors:  Amarendran R Subramanian; Jan Weyer-Menkhoff; Michael Kaufmann; Burkhard Morgenstern
Journal:  BMC Bioinformatics       Date:  2005-03-22       Impact factor: 3.169

10.  Fast statistical alignment.

Authors:  Robert K Bradley; Adam Roberts; Michael Smoot; Sudeep Juvekar; Jaeyoung Do; Colin Dewey; Ian Holmes; Lior Pachter
Journal:  PLoS Comput Biol       Date:  2009-05-29       Impact factor: 4.475

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  8 in total

1.  PROMALS3D: multiple protein sequence alignment enhanced with evolutionary and three-dimensional structural information.

Authors:  Jimin Pei; Nick V Grishin
Journal:  Methods Mol Biol       Date:  2014

2.  An Improved Integration of Template-Based and Template-Free Protein Structure Modeling Methods and its Assessment in CASP11.

Authors:  Jilong Li; Badri Adhikari; Jianlin Cheng
Journal:  Protein Pept Lett       Date:  2015       Impact factor: 1.890

3.  The MULTICOM toolbox for protein structure prediction.

Authors:  Jianlin Cheng; Jilong Li; Zheng Wang; Jesse Eickholt; Xin Deng
Journal:  BMC Bioinformatics       Date:  2012-04-30       Impact factor: 3.169

4.  Enhancing HMM-based protein profile-profile alignment with structural features and evolutionary coupling information.

Authors:  Xin Deng; Jianlin Cheng
Journal:  BMC Bioinformatics       Date:  2014-07-25       Impact factor: 3.169

5.  Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

Authors:  Yuedong Yang; Jianzhao Gao; Jihua Wang; Rhys Heffernan; Jack Hanson; Kuldip Paliwal; Yaoqi Zhou
Journal:  Brief Bioinform       Date:  2018-05-01       Impact factor: 11.622

6.  DECIPHER: harnessing local sequence context to improve protein multiple sequence alignment.

Authors:  Erik S Wright
Journal:  BMC Bioinformatics       Date:  2015-10-06       Impact factor: 3.169

7.  QuickProbs--a fast multiple sequence alignment algorithm designed for graphics processors.

Authors:  Adam Gudyś; Sebastian Deorowicz
Journal:  PLoS One       Date:  2014-02-25       Impact factor: 3.240

8.  Boosting the accuracy of protein secondary structure prediction through nearest neighbor search and method hybridization.

Authors:  Spencer Krieger; John Kececioglu
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

  8 in total

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