Accessible Requires Authentication Published by Oldenbourg Wissenschaftsverlag October 4, 2018

Quantum Chemistry Meets Deep Learning for Complex Carbohydrate and Glycopeptide Species I

M. Gokhan Habiboglu and Orkid Coskuner-Weber

Abstract

Carbohydrate complexes are crucial in many various biological and medicinal processes. The impacts of N-acetyl on the glycosidic linkage flexibility of methyl β-D-glucopyranose, and of the glycoamino acid β-D-glucopyranose-asparagine are poorly understood at the electronic level. Furthermore, the effect of D- and L-isomers of asparagine in the complexes of N-acetyl-β-D-glucopyranose-(L)-asparagine and N-acetyl-β-D-glucopyranose-(D)-asparagine is unknown. In this study, we performed density functional theory calculations of methyl β-D-glucopyranose, methyl N-acetyl-β-D-glucopyranose, and of glycoamino acids β-D-glucopyranose-asparagine, N-acetyl-β-D-glucopyranose-(L)-asparagine and N-acetyl-β-D-glucopyranose-(D)-asparagine for studying their linkage flexibilities, total solvated energies, thermochemical properties and intra-molecular hydrogen bond formations in an aqueous solution environment using the COnductor-like Screening MOdel (COSMO) for water. We linked these density functional theory calculations to deep learning via estimating the total solvated energy of each linkage torsional angle value. Our results show that deep learning methods accurately estimate the total solvated energies of complex carbohydrate and glycopeptide species and provide linkage flexibility trends for methyl β-D-glucopyranose, methyl N-acetyl-β-D-glucopyranose, and of glycoamino acids β-D-glucopyranose-asparagine, N-acetyl-β-D-glucopyranose-(L)-asparagine and N-acetyl-β-D-glucopyranose-(D)-asparagine in agreement with density functional theory results. To the best of our knowledge, this study represents the first application of density functional theory along with deep learning for complex carbohydrate and glycopeptide species in an aqueous solution medium. In addition, this study shows that a few thousands of optimization frames from DFT calculations are enough for accurate estimations by deep learning tools.

Acknowledgement

O.C.W. thanks Prof. Ulrich K. Deiters for the extensive and unique research training during her Diplomarbeit and then Doktorarbeit at the University of Cologne. O.C.W. also is thankful for the unlimited support and friendship provided by Prof. Dr. Ulrich K. Deiters. We wish a happy birthday to Prof. Dr. Ulrich K. Deiters and may the force be with him.

The authors acknowledge TRUBA resources because the numerical calculations reported in this study were performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources).

References

[1] C. Schäffer, P. Messner, Microbiology 151 (2005) 643.10.1099/mic.0.27749-015758211 Search in Google Scholar

[2] M. Sára, Trends Microbiol. 9 (2001) 47.10.1016/S0966-842X(00)01905-311173224 Search in Google Scholar

[3] J. L. Asensio, F. J. Canada, H. C. Siebert, J. Laynez, A. Poveda, P. M. Nieto, U. M. Soedjanaamadja, H. J. Gabius, J. Jimenez-Barbero, Chem. Biol. 7 (2000) 529.10.1016/S1074-5521(00)00136-810903932 Search in Google Scholar

[4] H. Zhou, A. J. Hanneman, N. D. Chasteen, V. N. Reinhold, J. Proteome Res. 12 (2013) 4547.10.1021/pr400673423919883 Search in Google Scholar

[5] M. Perbandt, E. W. Guthöhrlein, W. Rypniewski, K. Idakieva, S. Stoeva, W. Voelter, N. Genov, C. Betzel, Biochemistry-US 42 (2003) 6341.10.1021/bi020672x Search in Google Scholar

[6] M. Maras, A. Bruyn, J. Schraml, P. Herdewijn, M. Claeyssens, W. Fiers, R. Contreras, Eur. J. Biochem. 245 (1997) 617.10.1111/j.1432-1033.1997.00617.x9182997 Search in Google Scholar

[7] J. Travis, D. Johnson, Methods Enzymol. 80 (1981) 754.10.1016/S0076-6879(81)80057-2 Search in Google Scholar

[8] C. Slawson, G. W. Hart, Nat. Rev. Cancer 11 (2011) 678.10.1038/nrc311421850036 Search in Google Scholar

[9] S. R. V. Knott, E. Wagenblast, S. Khan, S. Y. Kim, M. Soto, M. Wagner, M. O. Turgeon, L. Fish, N. Erard, A. L. Gable, A. R. Maceli, S. Dickopf, E. K. Papachristou, C. S. D’ Santos, L. A. Carey, J. E. Wilkinson, J. C. Harrell, C. M. Perou, H. Goodarzi, G. Poulogiannis, G. J. Hannon, Nature 554 (2018) 378.2941494610.1038/nature25465 Search in Google Scholar

[10] J. W. Dennis, Cancer Surv. 7 (1988) 573.3072067 Search in Google Scholar

[11] K. Vaidyanathan, S. Durning, L. Wells, Crit. Rev. Biochem. Mol. Biol. 49 (2014) 140.10.3109/10409238.2014.88453524524620 Search in Google Scholar

[12] H. Guo, B. Zhang, A. V. Nairn, T. Nagy, K. W. Moremen, P. Buckhaults, M. Pierce, J. Biol. Chem. 292 (2017) 4123.2809646810.1074/jbc.M116.763201 Search in Google Scholar

[13] J. Ma, G. W. Hart, Clin. Proteomics 11 (2014) 8.2459390610.1186/1559-0275-11-8 Search in Google Scholar

[14] H. Y. Naim, H. Koblet, Arch. Virol. 122 (1992) 45.172998510.1007/BF01321117 Search in Google Scholar

[15] J. A. Mondotte, P. Y. Lozach, A. Amara, A. V. Gamarnik, J. Virol. 81 (2007) 7136.1745992510.1128/JVI.00116-07 Search in Google Scholar

[16] G. Wengler, E. Castle, U. Leidner, T. Nowak, G. Wengler, Virology 147 (1985) 264.10.1016/0042-6822(85)90129-13855247 Search in Google Scholar

[17] Y. Shi, L. Dai, H. Song, G. F. Gao, Adv. Exp. Med. Biol. 1062 (2018) 77.2984552610.1007/978-981-10-8727-1_6 Search in Google Scholar

[18] D. Sirohi, R. J. Kuhn, MBio 8 (2017) e00916.28655823 Search in Google Scholar

[19] K. Popuri, R. Balachandar, K. Alpert, D. Lu, M. Bhalla, I. R. Mackenzie, R. G. Hsiung, L. Wang, M. F. Beg, Neuroimage Clin. 18 (2018) 802.2987626610.1016/j.nicl.2018.03.007 Search in Google Scholar

[20] A. I. Duarte, M. S. Santos, C. R. Oliveira, P. I. Moreira, Neuropharmacology 136 (2018) 223.10.1016/j.neuropharm.2018.01.04429471055 Search in Google Scholar

[21] S. Olivier-Van Stichelen, J. A. Hanover, Curr. Opin. Clin. Nutr. Metab. Care 18 (2015) 339.10.1097/MCO.000000000000018826049631 Search in Google Scholar

[22] P. Polavarapu, C. Ewig, J. Comput. Chem. 13 (1992) 1255.10.1002/jcc.540131009 Search in Google Scholar

[23] U. Salzner, P. v. R. Schleyer, J. Am. Chem. Soc. 22 (1993) 10231. Search in Google Scholar

[24] L. B. A. Oliveira, G. Colherinhas, J. Mol. Liq. 237 (2017) 295.10.1016/j.molliq.2017.04.108 Search in Google Scholar

[25] M. S. Cintrón, G. P. Johnson, A. D. French, Carbohydr. Res. 443–444 (2017) 87.28411418 Search in Google Scholar

[26] V. Singh, P. K. Chhotaray, N. Islam, R. L. Gardas, J. Chem. Thermodyn. 103 (2016) 7.10.1016/j.jct.2016.07.051 Search in Google Scholar

[27] J. Y. Salpin, J. Tortajada, J. Mass. Spectrom. 39 (2004) 930.1532984510.1002/jms.671 Search in Google Scholar

[28] X. Qian, M. R. Nimlos, M. Davis, D. K. Johnson, M. E. Himmel, Carbohydr. Res. 340 (2005) 2319.10.1016/j.carres.2005.07.02116095579 Search in Google Scholar

[29] O. Coskuner, J. Chem. Phys. 127 (2007) 015101.1762736810.1063/1.2747238 Search in Google Scholar

[30] O. Coskuner, D. E. Bergeron, L. Rincon, J. W. Hudgens, C. A. Gonzalez, J. Phys. Chem. A 112 (2008) 2940.1830235510.1021/jp711759q Search in Google Scholar

[31] O. Coskuner, D. E. Bergeron, L. Rincon, J. W. Hudgens, C. A. Gonzalez, J. Phys. Chem. A 113 (2009) 2491.10.1021/jp805747f19236000 Search in Google Scholar

[32] O. Coskuner, D. E. Bergeron, L. Rincon, J. W. Hudgens, C. A. Gonzalez, J. Phys. Chem. A 129 (2008) 045102.10.1063/1.2958916 Search in Google Scholar

[33] T. H. Dunning, J. Chem. Phys. 90 (1989) 1007.10.1063/1.456153 Search in Google Scholar

[34] O. Wise-Scira, L. Xu, T. Kitahara, G. Perry, O. Coskuner, J. Chem. Phys. 135 (2011) 205101.2212895710.1063/1.3662490 Search in Google Scholar

[35] R. Ramakrishnan, O. A. von Lilienfeld, Reviews in Computational Chemistry, Wiley, New Jersey, Chapter 5 (2017). Search in Google Scholar

[36] G. B. Goh, N. O. Hodas, A. Vishnu, J. Comput. Chem. 38 (2017) 1291.2827281010.1002/jcc.24764 Search in Google Scholar

[37] H. D. Li, Y. Z. Liang, Q. S. Xu, Chemometr. Intell. Lab. 95 (2009) 188.10.1016/j.chemolab.2008.10.007 Search in Google Scholar

[38] G. Hautier, C. C. Fischer, A. Jain, T. Mueller, G. Ceder, Chem. Mater. 22 (2010) 3762.10.1021/cm100795d Search in Google Scholar

[39] K. R. Muller, G. Ratsch, S. Sonnenburg, S. Mika, M. Grimm, N. Heinrich, J. Chem. Inf. Model. 45 (2005) 249.10.1021/ci049737o15807485 Search in Google Scholar

[40] A. P. Bartok, M. J. Gillan, F. R. Manby, G. Csanyi, Phys. Rev. B 88 (2013) 054104.10.1103/PhysRevB.88.054104 Search in Google Scholar

[41] M. Rupp, A. Tkatchenko, K. R. Müller, O. A. von Lilienfeld, Phys. Rev. Lett. 108 (2012) 058301.10.1103/PhysRevLett.108.05830122400967 Search in Google Scholar

[42] J. C. Snyder, M. Rupp, K. Hansen, K. R. Müller, K. Burke, Phys. Rev. Lett. 108 (2012) 253002.2300459310.1103/PhysRevLett.108.253002 Search in Google Scholar

[43] J. Lee, A. Seko, K. Shitara, K. Nakayama, I. Tanaka, Phys. Rev. B 93 (2016) 115104.10.1103/PhysRevB.93.115104 Search in Google Scholar

[44] R. M. Balabin, E. I. Lomakina, J. Chem. Phys. 131 (2009) 074104.1970872910.1063/1.3206326 Search in Google Scholar

[45] K. Yao, J.E. Herr, J. Parkhill, J. Chem. Phys. 146 (2017) 014106.10.1063/1.497338028063436 Search in Google Scholar

[46] J. Behler, J. Chem. Phys. 145 (2016) 170901.10.1063/1.496619227825224 Search in Google Scholar

[47] G. Montavon, M. Rupp, V. Gobre, A. V. Mayagoitia, K. Hansen, A. Tkatchenko, K. R. Müller, O. A. v. Lilienfeld, New J. Phys. 15 (2013) 095003.10.1088/1367-2630/15/9/095003 Search in Google Scholar

[48] G. Schaftenaar, J. H. Noordik, J. Comput. Aided Mol. Des. 14 (2000) 123.10.1023/A:100819380543610721501 Search in Google Scholar

[49] A. D. Becke, J. Chem. Phys. 98 (1993) 5648.10.1063/1.464913 Search in Google Scholar

[50] C. Lee, W. Yang, R. G. Parr, Phys. Rev. B 37 (1988) 785.10.1103/PhysRevB.37.785 Search in Google Scholar

[51] S. H. Vosko, L. Wilk, M. Nusair, Can. J. Phys. 58 (1980) 1200.10.1139/p80-159 Search in Google Scholar

[52] P. J. Stephens, F. J. Devlin, C. F. Chabalowski, M. J. Frisch, J. Phys. Chem. 98 (1994) 11623.10.1021/j100096a001 Search in Google Scholar

[53] M. W. Schmidt, K. K. Baldridge, J. A. Boatz, S. T. Elbert, M. S. Gordon, J. H. Jensen, S. Koseki, N. Matsunaga, K. A. Nguyen, S. Su, T. L. Windus, M. Dupuis, J. A. Montgomery, J. Comput. Chem. 14 (1993) 1347.10.1002/jcc.540141112 Search in Google Scholar

[54] R. S. Mulliken, J. Chem. Phys. 23 (1955) 1833.10.1063/1.1740588 Search in Google Scholar

[55] A. E. Reed, R. B. Weinstock, F. Weinhold, J. Chem. Phys. 83 (1985) 735.10.1063/1.449486 Search in Google Scholar

[56] A. Klamt, G. Schüürmann, J. Chem. Soc. Perkin Trans. 2 0 (1993) 799. Search in Google Scholar

[57] A. Bondi, J. Phys. Chem. 68 (1964) 441.10.1021/j100785a001 Search in Google Scholar

[58] D. Nguyen, B. Widrow, Improving the Learning Speed of 2-layer Neural Networks by Choosing Initial Values of the Adaptive Weights, in: Proceedings of the International Joint Conference on Neural Networks, San Diego, CA, 3 (1990) 21. Search in Google Scholar

[59] M. F. Møller, Neural Netw. 6 (1993) 525.10.1016/S0893-6080(05)80056-5 Search in Google Scholar

[60] D. L. Elliott, A Better Activation Function for Artificial Neural Networks, Institute for Systems Research, University of Maryland (1993). Search in Google Scholar

[61] W. G. Ferrier, Acta Cryst. 13 (1960) 678.10.1107/S0365110X60001588 Search in Google Scholar

[62] R. A. Jacobson, J. A. Wunderlich, Nature 184 (1959) 1719.10.1038/1841719a0 Search in Google Scholar

[63] C. J. Brown, J. Chem. Soc. A (1966) 927. Search in Google Scholar

[64] S. S. Chu, G. A. Jeffrey, Acta Cryst. B24 (1968) 830. Search in Google Scholar

[65] M. Mathiselvam, B. Varghese, D. Loganathan, Glycoconj. J. 28 (2011) 573.10.1007/s10719-011-9357-y22033850 Search in Google Scholar

[66] L. T. Delbaere, Biochem. J. 143 (1974) 197.446485010.1042/bj1430197 Search in Google Scholar

[67] J. J. Verbist, M. S. Lehmann, T. F. Koetzle, W. C. Hamilton, Acta Cryst. 28 (1972) 3006.10.1107/S0567740872007368 Search in Google Scholar

[68] J. S. Lomas, L. Joubert, Magn. Reson. Chem. 55 (2017) 893.10.1002/mrc.459928432857 Search in Google Scholar

Supplementary Material

The online version of this article offers supplementary material (DOI: https://doi.org/10.1515/zpch-2018-1251).

Received: 2018-06-13
Accepted: 2018-09-10
Published Online: 2018-10-04
Published in Print: 2019-04-24

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