Predicting N-terminal acetylation based on feature selection method.
Methionine aminopeptidase and N-terminal acetyltransferase are two enzymes that contribute most to the N-terminal acetylation, which has long been recognized as a frequent and important kind of co-translational modifications [R.A. Bradshaw, W.W. Brickey, K.W. Walker, N-terminal processing: the methionine aminopeptidase and N alpha-acetyl transferase families, Trends Biochem. Sci. 23 (1998) 263-267]. The combined action of these two enzymes leads to two types of N-terminal acetylated proteins that are with/without the initiator methionine after the N-terminal acetylation. To accurately predict these two types of N-terminal acetylation, a new method based on feature selection has been developed. 1047 N-terminal acetylated and non-acetylated decapeptides retrieved from Swiss-Prot database (http://cn.expasy.org) are encoded into feature vectors by amino acid properties collected in Amino Acid Index database (http://www.genome.jp/aaindex). The Maximum Relevance Minimum Redundancy method (mRMR) combining with Incremental Feature Selection (IFS) and Feature Forward Selection (FFS) is then applied to extract informative features. Nearest Neighbor Algorithm (NNA) is used to build prediction models. Tested by Jackknife Cross-Validation, the correct rate of predictors reach 91.34% and 75.49% for each type, which are both better than that of 84.41% and 62.99% acquired by using motif methods [S. Huang, R.C. Elliott, P.S. Liu, R.K. Koduri, J.L. Weickmann, J.H. Lee, L.C. Blair, P. Ghosh-Dastidar, R.A. Bradshaw, K.M. Bryan, et al., Specificity of cotranslational amino-terminal processing of proteins in yeast, Biochemistry 26 (1987) 8242-8246; R. Yamada, R.A. Bradshaw, Rat liver polysome N alpha-acetyltransferase: substrate specificity, Biochemistry 30 (1991) 1017-1021]. Furthermore, the analysis of the informative features indicates that at least six downstream residues might have effect on the rules that guide the N-terminal acetylation, besides the penultimate residue. The software is available upon request.
Cai
Yu-Dong
YD
Department of Combinatorics and Geometry, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, People's Republic of China. cyd@picb.ac.cn
Lu
Lin
L
D000107:Acetylation; D000123:Acetyltransferases / Q000378:metabolism; D000626:Aminopeptidases / Q000378:metabolism; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D006801:Humans; D063208:Methionyl Aminopeptidases; D011499:Protein Processing, Post-Translational; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
D000123:Acetyltransferases; D000626:Aminopeptidases; D063208:Methionyl Aminopeptidases