Interactions between proteins and their small molecule ligands are of great importance for the process of drug design. Here we report an unbiased molecular dynamics simulation of systems containing hevein domain (HEV32) with N-acetylglucosamine mono-, di- or trisaccharide. Carbohydrate molecules were placed outside the binding site. Three of six simulations (6 × 2 μs) led to binding of a carbohydrate ligand into the binding mode in agreement with the experimentally determined structure. Unbinding was observed in one simulation (monosaccharide). There were no remarkable intermediates of binding for mono and disaccharide. Trisaccharide binding was initiated by formation of carbohydrate-aromatic CH/π interactions. Our results indicate that binding of ligands followed the model of conformational selection because the conformation of the protein ready for ligand binding was observed before the binding. This study extends the concept of docking by dynamics on carbohydrate-protein interactions.

Department of Biochemistry and Microbiology University of Chemistry and Technology Prague Technická 3 Prague 6 166 28 Czech Republic

Institute of Chemistry Centre for Glycomics Slovak Academy of Sciences Dúbravská cesta 9 Bratislava 845 38 Slovakia

Zobrazit více v PubMed

Gabius HJ, André S, Jiménez-Barbero J, Romero A, Solís D. From lectin structure to functional glycomics: Principles of the sugar code. Trends Biochem. Sci. 2011;36:298–313. doi: 10.1016/j.tibs.2011.01.005. PubMed DOI

Pérez S, Tvaroška I. Carbohydrate–protein interactions: Molecular modeling insights. Adv. Carbohydr. Chem. Biochem. 2014;71:9–136. doi: 10.1016/B978-0-12-800128-8.00001-7. PubMed DOI

Müller C, Despras G, Lindhorst TK. Organizing multivalency in carbohydrate recognition. Chem. Soc. Rev. 2016;45:3275–3302. doi: 10.1039/C6CS00165C. PubMed DOI

Gioia D, Bertazzo M, Recanatini M, Masetti M, Cavalli A. Dynamic docking: A paradigm shift in computational drug discovery. Molecules. 2017;22:2029. doi: 10.3390/molecules22112029. PubMed DOI PMC

De Vivo M, Masetti M, Bottegoni G, Cavalli A. Role of molecular dynamics and related methods in drug discovery. J. Med. Chem. 2016;59:4035–4061. doi: 10.1021/acs.jmedchem.5b01684. PubMed DOI

Zeller F, Luitz MP, Bomblies R, Zacharias M. Multiscale simulation of receptor–drug association kinetics: Application to neuraminidase inhibitors. J. Chem. Theory Comput. 2017;13:5097–5105. doi: 10.1021/acs.jctc.7b00631. PubMed DOI

Aboitiz N, et al. NMR and modeling studies of protein-carbohydrate interactions: Synthesis, three-dimensional structure, and recognition properties of a minimum hevein domain with binding affinity for chitooligosaccharides. ChemBioChem. 2004;5:1245–1245. doi: 10.1002/cbic.200400025. PubMed DOI

Berthelota K, Peruch F, Lecomte S. Highlights on Hevea brasiliensis (pro)hevein proteins. Biochimie. 2016;127:258–270. doi: 10.1016/j.biochi.2016.06.006. PubMed DOI

Chávez MI, et al. On the importance of carbohydrate-aromatic interactions for the molecular recognition of oligosaccharides by proteins: NMR studies of the structure and binding affinity of AcAMP2-like peptides with non-natural naphthyl and fluoroaromatic residues. Chem. Eur. J. 2005;11:7060–7074. doi: 10.1002/chem.200500367. PubMed DOI

Colombo G, Meli M, Cañada J, Asensio JL, Jiménez-Barbero J. Toward the understanding of the structure and dynamics of protein-carbohydrate interactions: molecular dynamics studies of the complexes between hevein and oligosaccharidic ligands. Carbohydr. Res. 2004;339:985–994. doi: 10.1016/j.carres.2003.10.030. PubMed DOI

Mareška V, Tvaroška I, Králová B, Spiwok V. Molecular simulations of hevein/(GlcNAc)3 complex with weakened OH/O and CH/π hydrogen bonds: Implications for their role in complex stabilization. Carbohydr. Res. 2015;408:1–7. doi: 10.1016/j.carres.2015.02.012. PubMed DOI

Pettersen EF, et al. UCSF Chimera – a visualization system for exploratory research and analysis. J. Comput. Chem. 2004;25:1605–1612. doi: 10.1002/jcc.20084. PubMed DOI

Spiwok V. CH/π interactions in carbohydrate recognition. Molecules. 2017;22:1038. doi: 10.3390/molecules22071038. PubMed DOI PMC

Asensio JL, Ardá A, Cañada FJ, Jiménez-Barbero J. Carbohydrate-aromatic interactions. Acc. Chem. Res. 2013;46:946–954. doi: 10.1021/ar300024d. PubMed DOI

Abraham MJ, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1–2:19–25. doi: 10.1016/j.softx.2015.06.001. DOI

Lindorff-Larsen K, et al. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins. 2010;78:1950–1958. doi: 10.1002/prot.22711. PubMed DOI PMC

Kirschner KN, et al. GLYCAM06: A generalizable biomolecular force field. carbohydrates. J. Comput. Chem. 2008;29:622–655. doi: 10.1002/jcc.20820. PubMed DOI PMC

Sousa da Silva AW, Vranken WF. ACPYPE – AnteChamber PYthon Parser interfacE. BMC Res. Notes. 2012;5:367. doi: 10.1186/1756-0500-5-367. PubMed DOI PMC

Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. Lincs: A linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472, https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H (1997).

Darden T, Perera L, Li L, Pedersen L. New tricks for modelers from the crystallography toolkit: The particle mesh ewald algorithm and its use in nucleic acid simulations. Structure. 1999;7:R55–R60. doi: 10.1016/S0969-2126(99)80033-1. PubMed DOI

Bussi G, Donadio D, Parrinello M. Canonical sampling through velocity rescaling. J. Chem. Phys. 2007;126:014101. doi: 10.1063/1.2408420. PubMed DOI