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parMATT: parallel multiple alignment of protein 3D-structures with translations and twists for distributed-memory

Maksim V Shegay¹, Dmitry A Suplatov², Nina N Popova¹

¹Faculty of Computational Mathematics and Cybernetics, Moscow, Russia.

Bioinformatics (Oxford, England)

|March 29, 2019

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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