TMBETA-NET: discrimination and prediction of membrane spanning beta-strands in outer membrane proteins.
We have developed a web-server, TMBETA-NET for discriminating outer membrane proteins and predicting their membrane spanning beta-strand segments. The amino acid compositions of globular and outer membrane proteins have been systematically analyzed and a statistical method has been proposed for discriminating outer membrane proteins. The prediction of membrane spanning segments is mainly based on feed forward neural network and refined with beta-strand length. Our program takes the amino acid sequence as input and displays the type of the protein along with membrane-spanning beta-strand segments as a stretch of highlighted amino acid residues. Further, the probability of residues to be in transmembrane beta-strand has been provided with a coloring scheme. We observed that outer membrane proteins were discriminated with an accuracy of 89% and their membrane spanning beta-strand segments at an accuracy of 73% just from amino acid sequence information. The prediction server is available at http://psfs.cbrc.jp/tmbeta-net/.
Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), AIST Tokyo Waterfront Bio-IT Research Building, 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan. michael-gromiha@aist.go.jp
M Michael
MM
Gromiha
Shandar
S
Ahmad
Makiko
M
Suwa
D000596:Amino Acids / Q000737:chemistry; D002462:Cell Membrane / Q000737:chemistry; D020407:Internet; D008565:Membrane Proteins / Q000737:chemistry*; D017433:Protein Structure, Secondary; D012984:Software
D000596:Amino Acids; D008565:Membrane Proteins