parMATT: parallel multiple alignment of protein 3D-structures with translations and twists for distributed-memory systems
Abstract Motivation Accurate structural alignment of proteins is crucial at studying structure-function relationship in evolutionarily distant homologues. Various software tools were proposed to align multiple protein 3D-structures utilizing one CPU and thus are of limited productivity at large-scal...
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| Vydáno v: | Bioinformatics Ročník 35; číslo 21; s. 4456 - 4458 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
England
Oxford University Press
01.11.2019
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| ISSN: | 1367-4803, 1367-4811, 1460-2059, 1367-4811 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Abstract
Motivation
Accurate structural alignment of proteins is crucial at studying structure-function relationship in evolutionarily distant homologues. Various software tools were proposed to align multiple protein 3D-structures utilizing one CPU and thus are of limited productivity at large-scale analysis of protein families/superfamilies.
Results
The parMATT is a hybrid MPI/pthreads/OpenMP parallel re-implementation of the MATT algorithm to align multiple protein 3D-structures by allowing translations and twists. The parMATT can be faster than MATT on a single multi-core CPU, and provides a much greater speedup when executed on distributed-memory systems, i.e. computing clusters and supercomputers hosting memory-independent computing nodes. The most computationally demanding steps of the MATT algorithm—the initial construction of pairwise alignments between all input structures and further iterative progression of the multiple alignment—were parallelized using MPI and pthreads, and the concluding refinement step was optimized by introducing the OpenMP support. The parMATT can significantly accelerate the time-consuming process of building a multiple structural alignment from a large set of 3D-records of homologous proteins.
Availability and implementation
The source code is available at https://biokinet.belozersky.msu.ru/parMATT.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1367-4803 1367-4811 1460-2059 1367-4811 |
| DOI: | 10.1093/bioinformatics/btz224 |