Author(s): GOMIDE, J.; MELO-MINARDI, R.; SANTOS, M. A. dos; NESHICH, G.; MEIRA JUNIOR, W.; LOPES, J. C.; SANTORO, M.

Summary: In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.

Publication year: 2009

Types of publication: Journal article

Unit: Embrapa Digital Agriculture

Keywords: Biologia molecular, Classificação de proteína, Contact maps, Latent semantic indexing, Linear algebra, Mapas de contato, Molecular biology, Protein classification, Singular value decomposition, Álgebra linear