Detecting Periodicity Associated with the Alpha-Helix Structure Using Fourier Transform

Abstract

Alpha helix is a common type of secondary structure in the protein structure that consists of repeating helical turns. Patterns in the protein sequences that cause this repetitive pattern in the structure have long been sought. We used the discrete Fourier transform (DFT) to detect the periodicity signals correlated to the helical structure. We studied the distribution of multiple properties along the protein sequence, and found a property that showed strong periodicity correlated with the helical structure. Using a short-time Fourier transform (STFT) method, we investigated the amplitude of the periodical signals at each amino acid position. The results show that residues in the helix structure tend to display higher amplitudes than residues outside of the helices. This tendency is dramatically strengthen when sequence profiles obtained from multiple alignment were used to detect the periodicity. A simple method that predicted helices based on the amplitude yielded overall true positive rate (TPR) of 63%, 49% sensitivity, 72% specificity, and 0.22 Matthews Correlation Coefficient (MCC). The performance seemed to depend on the length of helices that the proteins had.

Share and Cite:

W. Cheng and C. Yan, "Detecting Periodicity Associated with the Alpha-Helix Structure Using Fourier Transform," Computational Molecular Bioscience, Vol. 2 No. 4, 2012, pp. 109-114. doi: 10.4236/cmb.2012.24011.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] A. D. McLachlan, “Coiled Coil Formation and Sequence Regularities in the Helical Regions of Alpha-Keratin,” Journal of Molecular Biology, Vol. 124, No. 1, 1978, pp. 297-304. doi:10.1016/0022-2836(78)90163-8
[2] A. D. McLachlan and J. Karn, “Periodic Features in the Amino Acid Sequence of Nematode Myosin Rod,” Journal of Molecular Biology, Vol. 164, No. 4, 1983, pp. 605- 626. doi:10.1016/0022-2836(83)90053-0
[3] A. D. McLachlan and M. Stewart, “The 14-Fold Periodicity in Alpha-Tropomyosin and the Interaction with Actin,” Journal of Molecular Biology, Vol. 103, No. 2, 1976, pp. 271-298. doi:10.1016/0022-2836(76)90313-2
[4] J. Marshall and D. V. Holberton, “Sequence and Structure of a New Coiled Coil Protein from a Microtubule Bundle in Giardia,” Journal of Molecular Biology, Vol. 231, No. 2, 1993, pp. 521-530. doi:10.1006/jmbi.1993.1303
[5] E. Hoiczyk, et al., “Structure and Sequence Analysis of Yersinia YadA and Moraxella UspAs Reveal a Novel Class of Adhesins,” EMBO Journal, Vol. 19, No. 22, 2000, pp. 5989-5999.
[6] C. Pasquier, et al., “A Web Server to Locate Periodicities in a Sequence,” Bioinformatics, Vol. 14, No. 8, 1998, pp. 749-750. doi:10.1093/oxfordjournals.bioinformatics.a011054
[7] M. Gruber, J. Soding and A. N. Lupas, “REPPER-Repeats and Their Periodicities in Fibrous Proteins,” Nucleic Acids Research, Vol. 33, Suppl. 2, 2005, pp. W239- W243. doi:10.1093/nar/gki405
[8] L. Marsella, et al., “REPETITA: Detection and Discrimination of the Periodicity of Protein Solenoid Repeats by Discrete Fourier Transform,” Bioinformatics, Vol. 25, No. 12, 2009, pp. i289-i295. doi:10.1093/bioinformatics/btp232
[9] W. R. Atchley, et al., “Solving the Protein Sequence Metric Problem,” Proceedings of the National Academy of Sciences of the United States of America, Vol. 102, No. 18, 2005, pp. 6395-6400. doi:10.1073/pnas.0408677102
[10] Q. Fang and I. Cosic, “Can Short Time Fourier Transform Detect the Localized Latent Periodicity of a Protein Sequence?” IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, Melbourne, 20-22 October 2003, pp. 66-67. doi:10.1109/APBME.2003.1302586
[11] P. Ramachandran, A. Antoniou and P. P. Vaidyanathan, “Identification and Location of Hot Spots in Proteins Using the Short-Time Discrete Fourier Transform,” 38th Asilomar Conference on Signals, Systems and Computers, Vol. 2, 2004, pp. 1656-1660. doi:10.1109/ACSSC.2004.1399439
[12] A. G. Murzin, et al., “SCOP: A Structural Classification of Proteins Database for the Investigation of Sequences and Structures,” Journal of Molecular Biology, Vol. 247, No. 4, 1995, pp. 536-540. doi:10.1016/S0022-2836(05)80134-2
[13] S. Kawashima, et al., “AAindex: Amino Acid Index Database, Progress Report 2008,” Nucleic Acids Research, Vol. 36, Suppl. 1, 2008, pp. D202-D205. doi:10.1093/nar/gkm998
[14] B. Rost and C. Sander, “Improved Prediction of Protein Secondary Structure by Use of Sequence Profiles and Neural Networks,” Proceedings of the National Academy of Sciences of the United States of America, Vol. 90, No. 16, 1993, pp. 7558-7562. doi:10.1073/pnas.90.16.7558
[15] J. A. Cuff and G. J. Barton, “Application of Multiple Sequence Alignment Profiles to Improve Protein Secondary Structure Prediction,” Proteins: Structure, Function, and Bioinformatics, Vol. 40, No. 3, 2000, pp. 502-511. doi:10.1002/1097-0134(20000815)40:3<502::AID-PROT170>3.0.CO;2-Q
[16] S. Altschul, et al., “Gapped BLAST and PSI-BLAST: A New Generation of Protein Database Search Programs,” Nucleic Acids Research, Vol. 25, No. 17, 1997, pp. 3389-3402. doi:10.1093/nar/25.17.3389

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.