ArticleBMC research notes2012
Accelerating large-scale protein structure alignments with graphics processing units.
Article in BMC research notes, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Chemogenomic approach to identifying nematode chemoreceptor drug targets in the entomopathogenic nematode Heterorhabditis bacteriophora.Computational biology and chemistry · 2021Article
- pmTM-align: scalable pairwise and multiple structure alignment with Apache Spark and OpenMP.BMC bioinformatics · 2020Article
- MADOKA: an ultra-fast approach for large-scale protein structure similarity searching.BMC bioinformatics · 2019Article
- Graphics processing units in bioinformatics, computational biology and systems biology.Briefings in bioinformatics · 2017Review
- Efficient Multicriteria Protein Structure Comparison on Modern Processor Architectures.BioMed research international · 2015Article
- Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA.Journal of molecular modeling · 2014Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLarge-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons.
findingsWe present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs). As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH.
conclusionsppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU.
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