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Letters in Organic Chemistry

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ISSN (Print): 1570-1786
ISSN (Online): 1875-6255

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Research Article

N-MyristoylG-PseAAC: Sequence-based Prediction of N-Myristoyl Glycine Sites in Proteins by Integration of PseAAC and Statistical Moments

Author(s): Sher Afzal Khan*, Yaser Daanial Khan, Shakeel Ahmad and Khalid H. Allehaibi

Volume 16, Issue 3, 2019

Page: [226 - 234] Pages: 9

DOI: 10.2174/1570178616666181217153958

Price: $65

Abstract

N-Myristoylation, an irreversible protein modification, occurs by the covalent attachment of myristate with the N-terminal glycine of the eukaryotic and viral proteins, and is associated with a variety of pathogens and disease-related proteins. Identification of myristoylation sites through experimental mechanisms can be costly, labour associated and time-consuming. Due to the association of N-myristoylation with various diseases, its timely prediction can help in diagnosing and controlling the associated fatal diseases. Herein, we present a method named N-MyristoylG-PseAAC in which we have incorporated PseAAC with statistical moments for the prediction of N-Myristoyl Glycine (NMG) sites. A benchmark dataset of 893 positive and 1093 negative samples was collected and used in this study. For feature vector, various position and composition relative features along with the statistical moments were calculated. Later on, a back propagation neural network was trained using feature vectors and scaled conjugate gradient descent with adaptive learning was used as an optimizer. Selfconsistency testing and 10-fold cross-validation were performed to evaluate the performance of N-MyristoylG-PseAAC, by using accuracy metrics. For self-consistency testing, 99.80% Acc, 99.78% Sp, 99.81% Sn and 0.99 MCC were observed, whereas, for 10-fold cross validation, 97.18% Acc, 98.54% Sp, 96.07% Sn and 0.94 MCC were observed. Thus, it was found that the proposed predictor can help in predicting the myristoylation sites in an efficient and accurate way.

Keywords: N-Myristoylation, N-Myristoyl Glycine, PseAAC, 5-step rule, statistical moments, prediction.

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[1]
Jiang, H.; Zhang, X.; Chen, X.; Aramsangtienchai, P.; Tong, Z.; Lin, H. Chem. Rev., 2018, 118, 919-988.
[2]
Eisenhaber, F.; Eisenhaber, B.; Kubina, W.; Maurer-Stroh, S.; Neuberger, G.; Schneider, G.; Wildpaner, M. Nucleic Acids Res., 2003, 31, 3631-3634.
[3]
Blanden, M.J.; Suazo, K.F.; Hildebrandt, E.R.; Hardgrove, D.S.; Patel, M.; Saunders, W.P.; Distefano, M.D.; Schmidt, W.K.; Hougland, J.L. J. Biol. Chem., 2017, 8, 2770-2785.
[4]
Moriya, K.; Nagatoshi, K.; Noriyasu, Y.; Okamura, T.; Takamitsu, E.; Suzuki, T.; Utsumi, T. PLoS One, 2013, 8, e78235.
[5]
Ganesan, L.; Levental, I. J. Membr. Biol., 2015, 248, 929-941.
[6]
Maurer-Stroh, S.; Eisenhaber, B.; Eisenhaber, F. J. Mol. Biol., 2002, 317, 523-540.
[7]
Udenwobele, D.I.; Su, R-C.; Good, S.V.; Ball, T.B.; Varma Shrivastav, S.; Shrivastav, A. Front. Immunol., 2017, 8, 751.
[8]
Maurer-Stroh, S.; Eisenhaber, B.; Eisenhaber, F. J. Mol. Biol., 2002, 317, 541-557.
[9]
Martin, D.D.; Beauchamp, E.; Berthiaume, L.G. Biochimie, 2011, 93, 18-31.
[10]
Wang, S.; Zhang, Y-H.; Cai, Y-D.; Huang, G.; Chen, L. Comb. Chem. High Throughput Screen., 2017, 20, 96-106.
[11]
Cordeddu, V.; Di Schiavi, E.; Pennacchio, L.A.; Ma’ayan, A.; Sarkozy, A.; Fodale, V.; Cecchetti, S.; Cardinale, A.; Martin, J.; Schackwitz, W. Nat. Genet., 2009, 41, 1022.
[12]
Mazzanti, L.; Cacciari, E.; Cicognani, A.; Bergamaschi, R.; Scarano, E.; Forabosco, A. Am. J. Med. Genet. A., 2003, 118, 279-286.
[13]
Schubbert, S.; Shannon, K.; Bollag, G. Nat. Rev. Cancer, 2007, 7, 295.
[14]
Bowyer, P.W.; Gunaratne, R.S.; Grainger, M.; Withers-Martinez, C.; Wickramsinghe, S.R.; Tate, E.W.; Leatherbarrow, R.J.; Brown, K.A.; Holder, A.A.; Smith, D.F. Biochem. J., 2007, 408, 173-180.
[15]
Brannigan, J.A.; Smith, B.A.; Yu, Z.; Brzozowski, A.M.; Hodgkinson, M.R.; Maroof, A.; Price, H.P.; Meier, F.; Leatherbarrow, R.J.; Tate, E.W. J. Mol. Biol., 2010, 396, 985-999.
[16]
Panethymitaki, C.; Bowyer, P.W.; Price, H.P.; Leatherbarrow, R.J.; Brown, K.A.; Smith, D.F. Biochem. J., 2006, 396, 277-285.
[17]
Magnuson, B.A.; Raju, R.V.; Moyana, T.N.; Sharma, R.K. J. Natl. Cancer Inst., 1995, 87, 1630-1635.
[18]
Raju, R.V.; Moyana, T.N.; Sharma, R.K. Exp. Cell Res., 1997, 235, 145-154.
[19]
Xie, Y.; Zheng, Y.; Li, H.; Luo, X.; He, Z.; Cao, S.; Shi, Y.; Zhao, Q.; Xue, Y.; Zuo, Z. Sci. Rep., 2016, 6, 28249.
[20]
Bologna, G.; Yvon, C.; Duvaud, S.; Veuthey, A.L. Proteomics, 2004, 4, 1626-1632.
[21]
Podell, S.; Gribskov, M. BMC Genomics, 2004, 5, 37.
[22]
Chou, K-C. J. Theor. Biol., 2011, 273, 236-247.
[23]
Chou, K-C. Protein Eng., 2001, 14, 75-79.
[24]
Chen, J.; Liu, H.; Yang, J.; Chou, K-C. Amino Acids, 2007, 33, 423-428.
[25]
Xu, Y.; Ding, J.; Wu, L-Y.; Chou, K-C. PLoS One, 2013, 8, e55844.
[26]
Chen, W.; Feng, P-M.; Lin, H.; Chou, K-C. Nucleic Acids Res., 2013, 41, e68-e68.
[27]
Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chen, W.; Chou, K-C. Genomics, 2018.
[28]
Song, J.; Li, F.; Takemoto, K.; Haffari, G.; Akutsu, T.; Chou, K-C.; Webb, G.I. J. Theor. Biol., 2018, 443, 125-137.
[29]
Song, J.; Wang, Y.; Li, F.; Akutsu, T.; Rawlings, N.D.; Webb, G.I.; Chou, K-C. Brief. Bioinform., 2018.
[30]
Chou, K-C. Mol. BioSys., 2013, 9, 1092-1100.
[31]
Xu, Y.; Wen, X.; Shao, X-J.; Deng, N-Y.; Chou, K-C. Int. J. Mol. Sci., 2014, 15, 7594-7610.
[32]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K-C. J. Theor. Biol., 2016, 394, 223-230.
[33]
Qiu, W-R.; Xiao, X.; Lin, W-Z.; Chou, K-C. J. Biomol. Struct. Dyn., 2015, 33, 1731-1742.
[34]
Qiu, W.-R.; Xiao, X.; Lin, W.-Z.; Chou, K.-C. BioMed. Res. Int.,, 2014, 2014.
[35]
Xu, Y.; Wen, X.; Wen, L-S.; Wu, L-Y.; Deng, N-Y.; Chou, K-C. PLoS One, 2014, 9, e105018.
[36]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K-C. J. Biomol. Struct. Dyn., 2016, 34, 1946-1961.
[37]
Qiu, W-R.; Xiao, X.; Xu, Z-C.; Chou, K-C. Oncotarget, 2016, 7, 51270.
[38]
Shen, H-B.; Chou, K-C. Biochem. Biophys. Res. Commun., 2007, 363, 297-303.
[39]
Jiao, Y.; Du, P. Quant. Biol., 2016, 4, 320-330.
[40]
Qiu, W-R.; Sun, B-Q.; Xiao, X.; Xu, Z-C.; Chou, K-C. Bioinformatics, 2016, 32, 3116-3123.
[41]
Chou, K-C. Peptides, 2001, 22, 1973-1979.
[42]
Chou, K-C. Med. Chem., 2015, 11, 218-234.
[43]
Chou, K.C. Proteins: Struct. Func. Bioinform., 2001, 43, 246-255.
[44]
Khan, Y.D.; Ahmad, F.; Anwar, M.W. World Appl. Sci. J., 2012, 16, 678-685.
[45]
Khan, Y.D.; Ahmed, F.; Khan, S.A. Neural Comput. Appl., 2014, 24, 1519-1529.
[46]
Butt, A.H.; Khan, S.A.; Jamil, H.; Rasool, N.; Khan, Y.D. BioMed. Res. Int., 2016, 2016.
[47]
Butt, A.H.; Rasool, N.; Khan, Y.D. J. Membr. Biol., 2017, 250, 55-76.
[48]
Khan, Y.D.; Khan, N.S.; Farooq, S.; Abid, A.; Khan, S.A.; Ahmad, F.; Mahmood, M.K. Sci. World J.,, 2014, 2014.
[49]
Khan, Y.D.; Khan, S.A.; Ahmad, F.; Islam, S. 2014.
[50]
Khan, Y.D.; Rasool, N.; Hussain, W.; Khan, S.A.; Chou, K-C. Anal. Biochem., 2018, 550, 109-116.
[51]
Akmal, M.A.; Rasool, N.; Khan, Y.D. PLoS One, 2017, 12, e0181966.
[52]
Chen, Z.; Zhao, P.; Li, F.; Leier, A.; Marquez-Lago, T.T.; Wang, Y.; Webb, G.I.; Smith, A.I.; Daly, R.J.; Chou, K-C. Bioinformatics, 2018, 1, 4.
[53]
Cheng, X.; Xiao, X.; Chou, K-C. Bioinformatics, 2018, 34, 1448-1456.
[54]
Ehsan, A.; Mahmood, K.; Khan, Y.D.; Khan, S.A.; Chou, K-C. Sci. Rep., 2018, 8, 1039.
[55]
Hayashida, M.; Rocker, A.; Zhang, Y.; Akutsu, T.; Chou, K-C.; Strugnell, R.A.; Song, J.; Lithgow, T. Bioinformatics, 2018, 1, 10.
[56]
Liu, B.; Weng, F.; Huang, D-S.; Chou, K-C. Bioinformatics, 2018, 1, 8.
[57]
Yang, H.; Qiu, W-R.; Liu, G.; Guo, F-B.; Lin, H. Int. J. Biol. Sci., 2018, 14(8), 883.

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