Fast protein tertiary structure retrieval based on global surface shape similarity.
Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison.
Sael
Lee
L
Department of Computer Science, College of Science, Purdue University, West Lafayette, Indiana 47907, USA.
Li
Bin
B
La
David
D
Fang
Yi
Y
Ramani
Karthik
K
Rustamov
Raif
R
Kihara
Daisuke
D
D000465:Algorithms; D030562:Databases, Protein; D017434:Protein Structure, Tertiary; D016415:Sequence Alignment / Q000379:methods*; D012984:Software