High dimensional indexing for protein structure matching
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For determining functionality dependencies between two proteins, both represented as 3D structures, it is an essential condition that they have a matching structure. As 3D structures for proteins are large, complex and constantly evolving, it is very time-consuming to identify possible locations and sizes of such a matching structure for a given protein against a large protein database. In this paper, we introduce a novel representation model and apply a transformation and formalization to this problem. We then propose a database solution by using innovative high dimensional indexing mechanisms. Experimental results demonstrate a promising performance of the high dimensional indexing to this biologically critical but previously computationally prohibitive problem.