利用數種蛋白質序列的胺基酸對組成之資訊預測外膜蛋白質

Prediction of Outer Membrane Proteins by Support Vector Machines Using Combinations of Gapped Amino Acid Pair Compositions

黃思華(Ssu-Hua Huang)

指導教授 ： 劉如生

元智大學/資訊學院/資訊工程學系/碩士(2005年)

摘要

無資料

關鍵字

外膜蛋白質預測 ； 支援向量法 ； 有間隔的胺基酸對組成 ； β-barrel膜蛋白質

並列摘要

A Gram-negative bacterial protein can be resident at one of five primary subcellu-lar localizations. Proteins resident at outer membrane are called outer membrane pro-teins (OMPs). Because of their exposition at the surface of the bacterial cell, these pro-teins attract the research interest of drug target. Since identifying OMPs by experiments takes lengthy time, it is urgent to develop reliable methods to discriminating OMPs from other proteins.

In this thesis, we present a method for OMP prediction by Support Vector Ma-chines (SVMs) using the combinations of k-gapped amino acid pair compositions. Two dataset are used to evaluate our method. One dataset consists of 471 OMP sequences and 1,120 non-OMP sequences. These sequences are annotated with experimentally verified subcellular localizations. The other dataset consists of 377 OMPs and 1,120 globular proteins belonging to four typical structural classes. Using the former dataset, our classifier achieves 95% in precision and 92% in recall. The result indicates that the combination of k-gapped amino acid pair compositions captures more discriminatory information than the occurrences of frequent subsequences. Applied to the latter dataset, our classifier achieves as high as 96% in precision and recall. Compared to the statisti-cal method based on dipeptide composition, the result indicates that our SVM based method is better than the pure statistical method. Furthermore, our classifier performs well on an extended dataset containing additionally α-helical transmembrane proteins.

並列關鍵字

outer membrane protein prediction ； Support Vector Machine ； gapped amino acid pair composition ； β-barrel membrane proteins

參考文獻

[ 1] Martelli,P.L., Fariselli,P., Krogh,A. and Casadio,R., “A sequence-profile-based HMM for predicting and discriminating β barrel membrane proteins”, Bioinfor-matics, 18, 2002, pp. S46-S53.

[ 3] Bigelow,H.R., Petrey,D.S., Liu,J., Przybylski,D. and Rost,B., “Predicting trans-membrane beta-barrels in proteomes”, Nucleic Acids Research, 32, 2004, pp. 2566-2577.

[ 4] Zhai,Y. and Saier,M., “The β-barrel finder (BBF) program, allowing identifica-tion of outer membrane β-barrel proteins encoded within prokaryotic genomes”, Protein Science, 11, 2002, pp. 2196-2207.

[ 5] Berven,F.S., Flikka,K., Jensen,H.B. and Eidhammer, I., “BOMP: A program to predict integral β-barrel outer membrane proteins encoded within genomes of Gram-negative bacteria”, Nucleic Acids Research, 32, 2004, pp. W394-W399.

[ 6] Liu,Q., Zhu,Y., Wang,B. and Li,Y., “Identification of β-barrel membrane proteins based on amino acid composition properties and predicted secondary structure”, Computational Biology and Chemistry, 27, 2003, pp. 355-361.