Structure-Guided Comparative Analysis of Proteins: Principles, Tools, and Applications for Predicting Function | Zendy

Raja Mazumder | Zendy; Sona Vasudevan | Zendy

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Structure-Guided Comparative Analysis of Proteins: Principles, Tools, and Applications for Predicting Function

Author(s) -

Raja Mazumder,

Sona Vasudevan

Publication year - 2008

Publication title -

plos computational biology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.628

H-Index - 182

eISSN - 1553-7358

pISSN - 1553-734X

DOI - 10.1371/journal.pcbi.1000151

Subject(s) - inference , computational biology , computer science , function (biology) , sequence alignment , protein structure database , sequence analysis , operon , sequence (biology) , protein function prediction , data mining , bioinformatics , protein function , biology , artificial intelligence , sequence database , genetics , peptide sequence , gene , escherichia coli

The main objective of this article was to define a ten-step procedure, largely guided by the percent-identity scale, that can be followed as a general rule for functional inference of an uncharacterized protein. This procedure is by no means exhaustive but can be used as an initial process for functional assignment. In many cases, additional clues and complementary information may be obtained from pathway analysis, operon information, and other non-homology based methods. We have demonstrated how by following the ten steps a function could be assigned for an uncharacterized conserved protein with its related sequences. In addition, the goal was to provide an overview of the available tools and databases to carry out comparative sequence and structural analysis.

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