title: Exploring protein architecture using 3D shape-based signatures.
abstract: Consider the scenario where, for a prescription drug designed to treat a terminal illness, a particular protein has been successfully identified as a crucial, beneficial component in the drug compound. However, this protein has contra-indications and causes severe adverse effects in a certain subset of the population. If another protein from the same family, with similar structure and functionality, but without these adverse effects, can be found, the subsequent modification of the harmful drug has obvious benefits. This paper describes a new indexing and similarity search system to retrieve such protein structure family members, based on their 3D shape. Our approach is translation, scale and rotation invariant, which eliminates the need for prior structure alignment. Our experimental evaluation against seven (7) diverse protein families indicate that our system accurately and precisely locate all members of a family. We further illustrate this by showing that our system precisely retrieves the Homo Sapiens Hemoglobin family members, against a database containing 26,000 protein structures.
authors.affiliation: National Research Council of Canada, Ottawa, ON, K1A 0R6, Canada. eric.paquet@nrc-cnrc.gc.ca
authors.forename: Eric
authors.initials: E
authors.lastname: Paquet
authors.forename: Herna L
authors.initials: HL
authors.lastname: Viktor
mesh_terms: D000595:Amino Acid Sequence; D003198:Computer Simulation; D021621:Imaging, Three-Dimensional / Q000379:methods; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins