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Accelerating Large Scale Protein Structural Alignments with Graphics Processing Units

University of Missouri researchers have developed an algorithm, called ppsAlign, which is a high-performance protein structural alignment tool designed to tackle the computational complexity issues from protein structural data. Results have indicated a many-fold increase in speed over other highly touted alignment algorithms, while maintaining comparable or better quality in all cases.

Large-scale protein structural alignment, an indispensable tool to life sciences and pharmaceutical industry, poses a tremendous challenge on computational resources. To ensure structural alignment accuracy and efficiency, other research attempts to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and are of limited accessibility. Others trade alignment quality for speed by using high-level characteristics of structure fragments for structure comparisons. An inexpensive, accurate, and speedy algorithm is needed to handle the ever-growing size of protein structures.

This algorithm uses a parallel protein structural alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs).

Computational Biology
-Drug discovery

Implements structural alignment at the residue level
-Parallel computing framework
-Efficient organization of memory layout and retrieval

Ready to be commercialized


Additional Details


University of Missouri - Columbia

Intellectual Property Protection

Pending Patent

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