MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems

González-Domínguez, Jorge; Liu, Yong-Chao; Touriño, Juan; Schmidt, Bertil

doi:10.1093/bioinformatics/btw558

Cited by 25 publications

(13 citation statements)

References 7 publications

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“…Clustal Omega is a multiple sequence alignment program that uses seeded guide trees and HMM profile-profile techniques to generate alignments[ 36 ]. MSAProbs is based on a combination of pair hidden Markov models, partition functions calculating posterior probabilities, weighted probabilistic consistency transformations and weighted profile-profile alignments[ 37 ]. Twelve alignments were generated: i .…”

Section: Resultsmentioning

confidence: 99%

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Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification

2017

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The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand—receptor interactions for reference compounds.

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Section: Resultsmentioning

confidence: 99%

“…The third intracellular loop (ICL3) was not modeled. For sequence alignment, Clustal Omega[ 36 ] and MSAProbs[ 37 ] programs were used. The study used a direct sequence alignment of the hH3R sequence with template sequences and multiple alignment with sequences of other human histamine receptors (H1–H4) and human muscarinic (M1–M5).…”

Section: Methodsmentioning

confidence: 99%

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification

2017

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“…To compare, we used the model plant Arabidopsis thaliana H + -ATPase as a query to perform BLASTx searches against diverse species present in SeagrassDB with an E-value cutoff of 1E-5 revealing the presence of H + -ATPase across all the species. Subsequently, protein alignments were done using MSAProbs 50 , revealing a high degree of conservation across the domains present in H + -ATPase (Fig. 4a ).…”

Section: Resultsmentioning

confidence: 99%

SeagrassDB: An open-source transcriptomics landscape for phylogenetically profiled seagrasses and aquatic plants

Sablok

Hayward

Davey

et al. 2018

Sci Rep

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Seagrasses and aquatic plants are important clades of higher plants, significant for carbon sequestration and marine ecological restoration. They are valuable in the sense that they allow us to understand how plants have developed traits to adapt to high salinity and photosynthetically challenged environments. Here, we present a large-scale phylogenetically profiled transcriptomics repository covering seagrasses and aquatic plants. SeagrassDB encompasses a total of 1,052,262 unigenes with a minimum and maximum contig length of 8,831 bp and 16,705 bp respectively. SeagrassDB provides access to 34,455 transcription factors, 470,568 PFAM domains, 382,528 prosite models and 482,121 InterPro domains across 9 species. SeagrassDB allows for the comparative gene mining using BLAST-based approaches and subsequent unigenes sequence retrieval with associated features such as expression (FPKM values), gene ontologies, functional assignments, family level classification, Interpro domains, KEGG orthology (KO), transcription factors and prosite information. SeagrassDB is available to the scientific community for exploring the functional genic landscape of seagrass and aquatic plants at: http://115.146.91.129/index.php.

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“…MAFFT [15,16], PRRP [17], ProbCons [18] , PROMALS [19], PROMALS3D [20],GLprobs [21],MSAprobs [22], and NAST [23] etc. MSA methods are generally applied for the identification of family of a new protein, locating DNA regulatory elements such as binding sites, protein structure prediction, and phylogenetic analysis.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Leading Protein Multiple Sequence Alignment Methods

Mishra*,

Tripathi,

Soam

2019

IJEAT

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Protein Multiple sequence alignment (MSA) is a process, that helps in alignment of more than two protein sequences to establish an evolutionary relationship between the sequences. As part of Protein MSA, the biological sequences are aligned in a way to identify maximum similarities. Over time the sequencing technologies are becoming more sophisticated and hence the volume of biological data generated is increasing at an enormous rate. This increase in volume of data poses a challenge to the existing methods used to perform effective MSA as with the increase in data volume the computational complexities also increases and the speed to process decreases. The accuracy of MSA is another factor critically important as many bioinformatics inferences are dependent on the output of MSA. This paper elaborates on the existing state of the art methods of protein MSA and performs a comparison of four leading methods namely MAFFT, Clustal Omega, MUSCLE and ProbCons based on the speed and accuracy of these methods. BAliBASE version 3.0 (BAliBASE is a repository of manually refined multiple sequence alignments) has been used as a benchmark database and accuracy of alignment methods is computed through the two widely used criteria named Sum of pair score (SPscore) and total column score (TCscore). We also recorded the execution time for each method in order to compute the execution speed.

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MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems

Abstract: Source code in C ++ and MPI running on Linux systems as well as a reference manual are available at http://msaprobs.sourceforge.net CONTACT: jgonzalezd@udc.esSupplementary information: Supplementary data are available at Bioinformatics online.

Cited by 25 publications

References 7 publications

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification

SeagrassDB: An open-source transcriptomics landscape for phylogenetically profiled seagrasses and aquatic plants

Performance Evaluation of Leading Protein Multiple Sequence Alignment Methods

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