On the Prediction of Transmembrane Helical Segments in Membrane Proteins Based on Wavelet Transform
The prediction of transmembrane helical segments
(TMHs) in membrane proteins is an important field in the
bioinformatics research. In this paper, a new method based on discrete
wavelet transform (DWT) has been developed to predict the number
and location of TMHs in membrane proteins. PDB coded as 1KQG
was chosen as an example to describe the prediction of the number and
location of TMHs in membrane proteins by using this method. To
access the effect of the method, 80 proteins with known 3D-structure
from Mptopo database are chosen at random as the test objects
(including 325 TMHs), 308 of which can be predicted accurately, the
average predicted accuracy is 96.3%. In addition, the above 80
membrane proteins are divided into 13 groups according to their
function and type. In particular, the results of the prediction of TMHs
of the 13 groups are satisfying.
[1] A. Krogh, B. Larsson, G. von Heijne, E. Sonnhamme, "Predicting
transmembrane protein topology with a hidden Markov model:
application to complete genomes,"J. Mol. Biol., vol. 305, 2001, pp.
567-580.
[2] J. Kyte, R. F. Doolittle, "A simple method for displaying the hydrophathic
character of a protein," J. Mol. Biol., 1982, 157: 105-132.
[3] G. Heijne, "The distribution of positively charged residues in bacterial
inner membrane proteins correlates with the transmembrane topology,"
EMBO J, vol. 5, 1986, pp. 3021-3027.
[4] T. Hirokawa, S. Boon-Chieng, S. Mitaku, "SOSUI: classification and
secondary structure prediction system for membrane proteins,"
Bioinformatics, vol. 14, 1998, pp. 378-379.
[5] C. Pasquier, V. J. Promponas, G. A. Palaios, J. S. Hamodrakas, S. J.
Hamodrakas, "A novel method for predicting trsnsmembrane segments in
proteins based on a statistical analysis of the SwissProt database: the
PRED-TMR algorithm," Protein Eng., vol. 12, 1999, pp. 381-385.
[6] M. Cserzö, E. Wallin, I. Simon, G. von Heijne, A. Elofsson, "Prediction
of transmembrane alpha-helices in prokaryotic membrane proteins: the
dense alignment surface method," Protein Eng., vol. 10, 1997, pp.
673-676.
[7] B. Persson, P. Argos, "Prediction of transmembrane segments in proteins
utilizing multiple sequence alignments," J. Mol. Biol., vol. 237, 1994, pp.
182-192.
[8] B. Rost, R. Casadio, P. Fariselli, "Topology prediction for helical
transmembrane segments at 86% accuracy," Protein Sci., vol. 5, 1996, pp.
1704-1718.
[9] G. E. Tusnady, I. Simon, "Principles governing amino acid composition
of integral membrane proteins: application to topology prediction," J.
Mol. Biol., vol. 283, 1998, pp. 489-506.
[10] Altaiski, M. Mornev, O. Polozov, "Wavelet analysis of DNA sequence,"
Genet. Anal.´╝î vol. 12, 1996, pp. 165-168.
[11] B. Yu, X. H. Meng, H. J. Liu, et al, "Prediction of transmembrane helical
segments in transmembrane proteins based on wavelet transform,"
Journal of Shanghai University (English Edition), vol. 10, 2006, pp.
308-318.
[12] K. B. Li, P. Issac, A. Krishnan, "Predicting allergenic proteins using
wavelet transform," Bioinformatics, vol. 20, 2004, pp. 2572-2578.
[13] P. Li├▓, "Wavelets in bioinformatics and computational biology: state of
art and perspectives," Bioinformatics, vol. 19(1) 2003, pp. 2-9.
[14] J. P. Mena-Chalco, Y. Zana, and R. M. Cesar, "Identification of protein
coding regions using the modified Gabor-wavelet transform," IEEE/ACM
Transactions on Computational Biology and Bioinformatics, vol. 5, 2008,
pp. 198-207.
[15] S. Jayasinghe, K. Hristova, S. H. White, "MPtopo: A database of
membrane protein topology," Protein Sci., vol. 10, 2001, pp. 455-458.
[16] D. Eisenberg, A. D. Mclachlan, "Solvation energy in protein folding and
binding," Nature, vol. 319, 1986, pp. 199-203.
[17] S. Mallat, "A theory for multiresolution signal decomposition: the
wavelet representation," IEEE Trans. Pattern Anal. Math.Intell, vol. 11,
1989, pp. 674-693.
[18] M. Jormakka, S. Tornroth, B. Byrne, S. Iwata, "Molecular basis of proton
motive force generation: Structure of formate dehydrogenase-N,"
Science, vol. 295, 2002, pp. 1863-1868.
[1] A. Krogh, B. Larsson, G. von Heijne, E. Sonnhamme, "Predicting
transmembrane protein topology with a hidden Markov model:
application to complete genomes,"J. Mol. Biol., vol. 305, 2001, pp.
567-580.
[2] J. Kyte, R. F. Doolittle, "A simple method for displaying the hydrophathic
character of a protein," J. Mol. Biol., 1982, 157: 105-132.
[3] G. Heijne, "The distribution of positively charged residues in bacterial
inner membrane proteins correlates with the transmembrane topology,"
EMBO J, vol. 5, 1986, pp. 3021-3027.
[4] T. Hirokawa, S. Boon-Chieng, S. Mitaku, "SOSUI: classification and
secondary structure prediction system for membrane proteins,"
Bioinformatics, vol. 14, 1998, pp. 378-379.
[5] C. Pasquier, V. J. Promponas, G. A. Palaios, J. S. Hamodrakas, S. J.
Hamodrakas, "A novel method for predicting trsnsmembrane segments in
proteins based on a statistical analysis of the SwissProt database: the
PRED-TMR algorithm," Protein Eng., vol. 12, 1999, pp. 381-385.
[6] M. Cserzö, E. Wallin, I. Simon, G. von Heijne, A. Elofsson, "Prediction
of transmembrane alpha-helices in prokaryotic membrane proteins: the
dense alignment surface method," Protein Eng., vol. 10, 1997, pp.
673-676.
[7] B. Persson, P. Argos, "Prediction of transmembrane segments in proteins
utilizing multiple sequence alignments," J. Mol. Biol., vol. 237, 1994, pp.
182-192.
[8] B. Rost, R. Casadio, P. Fariselli, "Topology prediction for helical
transmembrane segments at 86% accuracy," Protein Sci., vol. 5, 1996, pp.
1704-1718.
[9] G. E. Tusnady, I. Simon, "Principles governing amino acid composition
of integral membrane proteins: application to topology prediction," J.
Mol. Biol., vol. 283, 1998, pp. 489-506.
[10] Altaiski, M. Mornev, O. Polozov, "Wavelet analysis of DNA sequence,"
Genet. Anal.´╝î vol. 12, 1996, pp. 165-168.
[11] B. Yu, X. H. Meng, H. J. Liu, et al, "Prediction of transmembrane helical
segments in transmembrane proteins based on wavelet transform,"
Journal of Shanghai University (English Edition), vol. 10, 2006, pp.
308-318.
[12] K. B. Li, P. Issac, A. Krishnan, "Predicting allergenic proteins using
wavelet transform," Bioinformatics, vol. 20, 2004, pp. 2572-2578.
[13] P. Li├▓, "Wavelets in bioinformatics and computational biology: state of
art and perspectives," Bioinformatics, vol. 19(1) 2003, pp. 2-9.
[14] J. P. Mena-Chalco, Y. Zana, and R. M. Cesar, "Identification of protein
coding regions using the modified Gabor-wavelet transform," IEEE/ACM
Transactions on Computational Biology and Bioinformatics, vol. 5, 2008,
pp. 198-207.
[15] S. Jayasinghe, K. Hristova, S. H. White, "MPtopo: A database of
membrane protein topology," Protein Sci., vol. 10, 2001, pp. 455-458.
[16] D. Eisenberg, A. D. Mclachlan, "Solvation energy in protein folding and
binding," Nature, vol. 319, 1986, pp. 199-203.
[17] S. Mallat, "A theory for multiresolution signal decomposition: the
wavelet representation," IEEE Trans. Pattern Anal. Math.Intell, vol. 11,
1989, pp. 674-693.
[18] M. Jormakka, S. Tornroth, B. Byrne, S. Iwata, "Molecular basis of proton
motive force generation: Structure of formate dehydrogenase-N,"
Science, vol. 295, 2002, pp. 1863-1868.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:60926", author = "Yu Bin and Zhang Yan", title = "On the Prediction of Transmembrane Helical Segments in Membrane Proteins Based on Wavelet Transform", abstract = "The prediction of transmembrane helical segments
(TMHs) in membrane proteins is an important field in the
bioinformatics research. In this paper, a new method based on discrete
wavelet transform (DWT) has been developed to predict the number
and location of TMHs in membrane proteins. PDB coded as 1KQG
was chosen as an example to describe the prediction of the number and
location of TMHs in membrane proteins by using this method. To
access the effect of the method, 80 proteins with known 3D-structure
from Mptopo database are chosen at random as the test objects
(including 325 TMHs), 308 of which can be predicted accurately, the
average predicted accuracy is 96.3%. In addition, the above 80
membrane proteins are divided into 13 groups according to their
function and type. In particular, the results of the prediction of TMHs
of the 13 groups are satisfying.", keywords = "discrete wavelet transform, hydrophobicity,membrane protein, transmembrane helical segments", volume = "4", number = "1", pages = "119-6", }
