Chapter 1: Mining the Sequence Databases for Homology Detection: Application to Recognition of Functions of Trypanosoma brucei brucei Proteins and Drug Targets
WORLD SCIENTIFIC eBooks, Dec 17, 2013
ABSTRACT With the amount of data deluge as a result of high-throughput sequencing techniques and ... more ABSTRACT With the amount of data deluge as a result of high-throughput sequencing techniques and structural genomics initiatives, there comes a need to leverage the large-scale data. Consequently, the role of computational methods to characterize genes and proteins solely from their sequence information becomes increasingly important. Over the past decade, development of sensitive profile-based sequence database search algorithms has improved the quality of structural and functional inferences from protein sequence. This chapter highlights the use of such sensitive approaches in recognition of evolutionary related proteins when the amino acid sequence similarity is very low. We further demonstrate the use of sequence database mining based remote homology detection methods in exploring the repertoire of functions and three dimensional structures of parasitic proteins in Trypanosoma brucei brucei, causative agent of African sleeping sickness. With an emphasis on various metabolic pathways, the sequence-function and structure-function relationships are investigated. Integrating the information of parasitic proteins in metabolic pathways along with their homology to targets of FDA-approved drugs, attractive drug targets have been proposed.
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