The role of weak interactions in lignin polymerization
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Lignin is the most abundant natural polymer composed by aromatic moieties. Its chemical composition and its abundance have focused efforts to unlock its potential as a source of aromatic compounds for many years. The lack of a proper way for lignin de-polymerization has hampered its success as a natural solution for commodity aromatic chemicals, which is also due to the lack of understanding of the underlying mechanisms of lignin polymerization. A fuller fundamental understanding of polymerization mechanisms could lead to improvements in de-polymerization strategies, and therefore a proper methodology and a predictive theoretical framework are required for such purpose. This work presents a complete computational study on some of the key steps of lignin polymerization mechanisms. Density functional theory (DFT) calculations have been performed to evaluate the most appropriate methodology and to compute the chemical structures and reaction enthalpies for the monolignol dimerization, the simplest key step that controls the polymerization. Quantum theory of atoms in molecules (QTAIM) has been applied to understand the coupling reaction mechanisms, for which the radical species and transition states (TSs) involved have been characterized. The coupling that leads to the formation of the β–O–4 linkage has been theoretically reproduced according to proposed mechanisms, for which weak interactions have been found to play a key role in the arrangement of reactants. The hydrogen bond formed between the oxygen of the phenoxy radical, and the alcohol of the aliphatic chain, together with the interaction between aromatic rings, locates the reactants in a position that favors such β–O–4 linkage.
KeywordsDensity functional theory Lignin polymerization QTAIM Monolignols
This work was financed by Proyecto Prometeo, Secretaría de Educación Superior, Ciencia, Tecnología e Innovación of the Republic of Ecuador. We also thank the “Centro de Servicios de Informática y Redes de Comunicaciones” (CSIRC) (UGRGrid), University of Granada and Universidad Técnica Particular de Loja for providing computing time. Mr. David Nesbitt reviewed the English version of the manuscript. We want to thank Dr. Santiago Melchor for his help in the management of computing resources.
- 15.Besombes S, Robert D, Utille J, Taravel FR, Mazeau K (2003) Molecular modeling of syringyl and p-hydroxyphenyl β–O–4 dimers. Comparative study of the computed and experimental conformational properties of lignin β–O–4 model compounds. J Agric Food Chem 51:34–42. doi: 10.1021/jf0206668 CrossRefGoogle Scholar
- 17.Besombes S, Utille J, Mazeau K, Robert D, Taravel FR (2004) Conformational study of a guaiacyl β-O-4 lignin model compound by NMR. Examination of intramolecular hydrogen bonding interactions and conformational flexibility in solution. Magn Reson Chem 42:337–347. doi: 10.1002/mrc.1317 CrossRefGoogle Scholar
- 23.Beste A, Buchanan III AC (2013) Computational investigation of the pyrolysis product selectivity for α–hydroxy phenethyl phenyl ether and phenethyl phenyl ether: analysis of substituent effects and reactant conformer selection. J Phys Chem A 117:3235–3242. doi: 10.1021/jp4015004 CrossRefGoogle Scholar
- 32.Ayers PW, Yang W, Bartolotti LJ (2009) The Fukui function in chemical reactivity theory: a density functional view. (Ed: Chattaraj PK). CRC Press, New York, pp 255–267Google Scholar
- 37.Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery Jr JA, Peralta JE, Ogliaro F, Bearpark M, Heyd JJ, Brothers E, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam JM, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin A J, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, Dapprich S, Daniels AD, Farkas Ö , Foresman JB, Ortiz JV, Cioslowski J, Fox DJ (2009) Gaussian 09 revision B.01. Gaussian Inc., WallingfordGoogle Scholar
- 42.Zhao Y, Truhlar DG (2008) The m06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four m06-class functionals and 12 other functionals. Theor Chem Account 120:215–241. doi: 10.1007/s00214-007-0310-x CrossRefGoogle Scholar
- 45.AIMALl (version 15.09.27), Todd AK, gristmill TK software, Overland Park KS, USA, 2015 (aim.tkgristmill.com)
- 46.Young D (2001) Computational chemistry: a practical guide for applying techniques to real world problems. Wiley Interscience, New YorkGoogle Scholar
- 48.Bader RFW (1990) Atoms in molecules: a quantum theory. Clarendon Press, Oxford, UKGoogle Scholar
- 49.Sjöström E (1981) Wood chemistry: fundamentals and applications. Academic Press, New YorkGoogle Scholar
- 50.Setälä H, Pajunen A, Rummakko P, Sipilä J, Brunow G (1999) A novel type of spiro compound formed by oxidative cross coupling of methyl sinapate with a syringyl lignin model compound. a model system for the β–1 pathway in lignin biosynthesis. J Chem Soc Perkin Trans 1:461–464. doi: 10.1039/A808884E CrossRefGoogle Scholar