Accelerated protein structure comparison using TM-score-GPU
Motivation: Accurate comparisons of different protein structures play important roles in structural biology, structure prediction and functional annotation. The RMSD after optimal superposition is the predominant measure of similarity due to the ease and speed of computation. However, global RMSD is dependent on the length of the protein and can be dominated by divergent loops which can obscure local regions of similarity. A more sophisticated measure of structure similarity, TM-score, avoids these problems, and is one of the measures used by the community wide experiments of Critical Assessment of protein Structure Prediction (CASP) to compare predicted models with experimental structures. TM-score calculations are, however, much slower than RMSD calculations. We have therefore implemented a very fast version of TM-score for Graphical Processing Units (TM-score-GPU), using a new and novel hybrid Kabsch/quaternion method for calculating the optimal superposition and RMSD that is designed for parallel applications. This acceleration in speed allows TM-score to be used efficiently in computationally intensive applications such as for clustering of protein models and genome-wide comparisons of structure
Results: TM-score-GPU was applied to 6 sets of models from Nutritious Rice for the World for a total of 3 million comparisons. TM-score-GPU is 68 times faster on an ATI 5870 GPU, on average, than the original CPU single threaded implementation on an AMD Phenom II 810 quad-core processor.
Implementation: The implementation is in C++/OpenCL
Availability: The complete source, including the GPU code and the hybrid RMSD subroutine can be downloaded and used without restriction at http://software.compbio.washington.edu/misc/downloads/tmscore/.
Ling-Hong Hung and Ram Samudrala. Accelerated protein structure comparison using TM-score-GPU. Bioinformatics. 2012. [doi: 10.1093/bioinformatics/bts345] [Free PDF]
Category: Articles, Life Science, Software
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