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

Abstract

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.