ArticleBMC bioinformatics2011
MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A Max-Margin Model for Predicting Residue-Base Contacts in Protein-RNA Interactions.Life (Basel, Switzerland) · 2021Article
- The influence of dataset homology and a rigorous evaluation strategy on protein secondary structure prediction.PloS one · 2021Article
- Refining pairwise sequence alignments of membrane proteins by the incorporation of anchors.PloS one · 2021Article
- Boosting the accuracy of protein secondary structure prediction through nearest neighbor search and method hybridization.Bioinformatics (Oxford, England) · 2020Article
- Sixty-five years of the long march in protein secondary structure prediction: the final stretch?Briefings in bioinformatics · 2018Article
- DECIPHER: harnessing local sequence context to improve protein multiple sequence alignment.BMC bioinformatics · 2015Article
- An Improved Integration of Template-Based and Template-Free Protein Structure Modeling Methods and its Assessment in CASP11.Protein and peptide letters · 2015Article
- Enhancing HMM-based protein profile-profile alignment with structural features and evolutionary coupling information.BMC bioinformatics · 2014Article
- PROMALS3D: multiple protein sequence alignment enhanced with evolutionary and three-dimensional structural information.Methods in molecular biology (Clifton, N.J.) · 2014Article
- QuickProbs--a fast multiple sequence alignment algorithm designed for graphics processors.PloS one · 2014Article
- The MULTICOM toolbox for protein structure prediction.BMC bioinformatics · 2012Article
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2 authors.
Funding
Abstract
backgroundMultiple 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.
resultsWe 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.
conclusionMSACompro 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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