Structural feature extraction protocol for classifying reversible membrane binding protein domains

Author

Källberg, Morten ; Lu, Hui

Author_Institution

Dept. of Bioeng. - Bioinf. program, Univ. of Illinois at Chicago, Chicago, IL, USA

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

6735

Lastpage

6738

Abstract

Machine learning based classification protocols for automated function annotation of protein structures have in many instances proven superior to simpler sequence based procedures. Here we present an automated method for extracting features from protein structures by construction of surface patches to be used in such protocols. The utility of the developed patch-growing procedure is exemplified by its ability to identify reversible membrane binding domains from the C1, C2, and PH families.

Keywords

biomembranes; feature extraction; learning (artificial intelligence); molecular biophysics; proteins; automated function annotation; classification protocols; feature extraction; machine learning; protein structure; reversible membrane binding domains; sequence based procedures; surface patch construction; Algorithms; Artificial Intelligence; Automation; Cell Membrane; Databases, Protein; Hydrogen Bonding; Hydrophobic and Hydrophilic Interactions; Protein Binding; Protein Structure, Tertiary; Proteins; Solvents; Static Electricity;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5332856

Filename

5332856