An Effective Protein Multiple Structure Alignment Using Parallel Computing

Abstract

Multiple spatial alignments of protein structures are an important tool of structural biology. Analysis of protein structures allows us to establish their homology; i.e., the origin from a common ancestor. The rapid growth in the number of known protein structures determines the requirements for the speed of the spatial alignment algorithms. This paper proposes a strategy for using parallel computations to efficiently construct multiple spatial equalizations using multi-core cluster system. The developed algorithm is based on the well-proven sequential method of spatial alignment of Multiple Alignments with Translations and Twists (MATT). Results show that the best speedup (38.44) and the least difference between the experimental and theoretical efficiency (0.01) was obtained. The speedup and efficiency based on (128) nodes have been evaluated using LinkSCEEM-2 systems at Bibliotheca Alexandrina, Egypt.