Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Sep 8;126(35):6642-6653.
doi: 10.1021/acs.jpcb.2c04245. Epub 2022 Aug 25.

Extension of the CHARMM Classical Drude Polarizable Force Field to N- and O-Linked Glycopeptides and Glycoproteins

Abhishek A Kognole  1 , Asaminew H Aytenfisu  1 , Alexander D MacKerell Jr  1
Affiliations

Extension of the CHARMM Classical Drude Polarizable Force Field to N- and O-Linked Glycopeptides and Glycoproteins

Abhishek A Kognole et al. J Phys Chem B. .

Abstract

Molecular dynamic simulations are an effective tool to study complex molecular systems and are contingent upon the availability of an accurate and reliable molecular mechanics force field. The Drude polarizable force field, which allows for the explicit treatment of electronic polarization in a computationally efficient fashion, has been shown to reproduce experimental properties that were difficult or impossible to reproduce with the CHARMM additive force field, including peptide folding cooperativity, RNA hairpin structures, and DNA base flipping. Glycoproteins are essential components of glycoconjugate vaccines, antibodies, and many pharmaceutically important molecules, and an accurate polarizable force field that includes compatibility between the protein and carbohydrate aspect of the force field is essential to study these types of systems. In this work, we present an extension of the Drude polarizable force field to glycoproteins, including both N- and O-linked species. Parameter optimization focused on the dihedral terms using a reweighting protocol targeting NMR solution J-coupling data for model glycopeptides. Validation of the model include eight model glycopeptides and four glycoproteins with multiple N- and O-linked glycosylations. The new glycoprotein carbohydrate force field can be used in conjunction with the remainder of Drude polarizable force field through a variety of MD simulation programs including GROMACS, OPENMM, NAMD, and CHARMM and may be accessed through the Drude Prepper module in the CHARMM-GUI.

PubMed Disclaimer

Conflict of interest statement

The authors declare the following competing interest(s): ADM Jr. is cofounder and CSO of SilcsBio LLC.

Figures

Figure 1.
Figure 1.
Model compounds used in dihedral fitting of the O- and N-linkages. For O-linkage, an initial simple model compound based on THP-Thr/Ser without the hydroxyls on the hexopyranose ring was used (top of left panel) to perform the dihedral potential energy scans. Subsequently the full model compounds with the hydroxyls (bottom of left panel) were created based on conformations of the THP-based model compounds. Both α and β anomers of both the N- and O-glycan linkages were included explicitly in this study, therefore the linkages are represented with dotted line.
Figure 2.
Figure 2.
Relative conformational energies of selected conformations of hexopyranose with N-acetyl substituted at C1 for both the α and β anomers. All the model compound conformations with relative QM energies below 12 kcal/mol are included. RMSE of Drude and additive C36 relative energies with respect to QM are included in parentheses shown in the inset.
Figure 3.
Figure 3.
2D protein φ/ψ distribution of target data used during the O-linked dihedral fitting. The distribution is overlaid on the structure of the full O-linked Thr model compound (Figure 1, bottom left panel).
Figure 4.
Figure 4.
Relative conformational energies of selected conformations of the hexopyranose monosaccharide linked to the Ser and Thr dipeptides for both the α and β anomers. All the model compound conformations with relative QM energies below 12 kcal/mol are included. RMSE of Drude and additive C36 relative energies with respect to QM are included in parentheses shown in the inset.
Figure 5.
Figure 5.
3JHαHβ vs φ (protein) distribution obtained from MD. 3JHαHβ calculated based on eq 1 for every 1° form −180° to 180°. “QM” indicates the initial QM-based dihedral parameters.
Figure 6.
Figure 6.
J-coupling values for the protein (φ) dihedral C-N-CA-C for the model compounds SER-BGLCNA and THR-BGLCNA. (A) and (C) represent the Drude FF results. (B) and (D) represent the additive C36 FF results. The results for the other six compounds are provided in the Supporting Information.
Figure 7.
Figure 7.
J-coupling values for the dihedral HN-N-C2-H2 for the model compounds SER-BGLCNA and THR-BGLCNA. (A) and (C) represent the Drude FF results. (B) and (D) represent the additive C36 FF results. The results for the other four compounds are provided in the Supporting Information.
Figure 8.
Figure 8.
J-coupling values for the dihedral N-CA-CB-OG for the model compounds SER-BGLCNA and THR-BGLCNA. (A) and (C) represent the Drude FF results. (B) and (D) represent the additive C36 FF results. With THR-BGLCNA experimental data is not available. The results for the other four compounds are provided in the Supporting Information.
Figure 9.
Figure 9.
Boltzmann inverted glycosidic dihedral angle distributions associated with all the N-glycans from all four glycoproteins. A) C1-ND2-CG-CB vs. O5-C1-ND2-CG, B) ND2-CG-CB-CA vs. C1-ND2-CG-CB, and C) CG-CB-CA-N vs. ND2-CG-CB-CA. Black dots indicate the values of the dihedrals observed in crystallographic structures.
Figure 10.
Figure 10.
Boltzmann inverted glycosidic dihedral angle distributions associated with all the O-glycans from all four glycoproteins. (A) C1-OG-CB-CA vs. O5-C1-OG-CB in Ser O-linkages, (B) OG-CB-CA-N vs. C1-OG-CB-CA in Ser O-linkages, (C) C1-OG1-CB-CA vs. O5-C1-OG1-CB in Thr O-linkages, and (D) OG1-CB-CA-N vs. C1-OG1-CB-CA in Thr O-linkages. Black dots indicate the values of dihedrals observed in crystallographic structures.
Figure 11.
Figure 11.
Monosaccharide dipole moment analysis for the N-glycan of PDB code 1MYR at Asn265 (segment ID: CARB assigned by CHARMM-GUI, see Table 1). Changes in dipole moment across the simulation are shown on left. On right, the normalized probabilities of dipole moment are shown for each monosaccharide.
See this image and copyright information in PMC

References

    1. Whitford PC; Blanchard SC; Cate JH; Sanbonmatsu KY Connecting the kinetics and energy landscape of tRNA translocation on the ribosome. PLoS Comput Biol 2013, 9 (3), e1003003. DOI: 10.1371/journal.pcbi.1003003. - DOI - PMC - PubMed
    2. Dror RO; Pan AC; Arlow DH; Borhani DW; Maragakis P; Shan Y; Xu H; Shaw DE Pathway and mechanism of drug binding to G-protein-coupled receptors. Proc Natl Acad Sci U S A 2011, 108 (32), 13118–13123. DOI: 10.1073/pnas.1104614108. - DOI - PMC - PubMed
    3. Shaw DE; Maragakis P; Lindorff-Larsen K; Piana S; Dror RO; Eastwood MP; Bank JA; Jumper JM; Salmon JK; Shan Y; et al. Atomic-level characterization of the structural dynamics of proteins. Science 2010, 330 (6002), 341–346. DOI: 10.1126/science.1187409. - DOI - PubMed
    4. McCammon JA; Gelin BR; Karplus M Dynamics of folded proteins. Nature 1977, 267 (5612), 585–590. DOI: 10.1038/267585a0. - DOI - PubMed
    1. Fadda E Molecular Simulations of complex carbohydrates and glycoconjugates. Curr. Opin. Chem. Biology 2022, 69, 102175. - PubMed
    1. Cornell WD; Cieplak P; Bayly CI; Gould IR; Merz KM; Ferguson DM; Spellmeyer DC; Fox T; Caldwell JW; Kollman PA A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules. Journal of the American Chemical Society 1995, 117 (19), 5179–5197. DOI: 10.1021/ja00124a002. - DOI
    2. MacKerell AD; Bashford D; Bellott M; Dunbrack RL; Evanseck JD; Field MJ; Fischer S; Gao J; Guo H; Ha S; et al. All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 1998, 102 (18), 3586–3616. DOI: 10.1021/jp973084f. - DOI - PubMed
    3. MacKerell AD; Brooks B; Brooks CL; Nilsson L; Roux B; Won Y; Karplus M CHARMM: The Energy Function and Its Parameterization. In Encyclopedia of Computational Chemistry, John Wiley & Sons, Ltd, 2002.
    4. MacKerell AD Jr.; Banavali N; Foloppe N Development and current status of the CHARMM force field for nucleic acids. Biopolymers 2000, 56 (4), 257–265. DOI: 10.1002/1097-0282(2000)56:4<257::AID-BIP10029>3.0.CO;2-W. - DOI - PubMed
    5. Pastor RW; Mackerell AD Jr. Development of the CHARMM Force Field for Lipids. J Phys Chem Lett 2011, 2 (13), 1526–1532. DOI: 10.1021/jz200167q. - DOI - PMC - PubMed
    6. Kaminski GA; Friesner RA; Tirado-Rives J; Jorgensen WL Evaluation and Reparametrization of the OPLS-AA Force Field for Proteins via Comparison with Accurate Quantum Chemical Calculations on Peptides. The Journal of Physical Chemistry B 2001, 105 (28), 6474–6487. DOI: 10.1021/jp003919d. - DOI
    7. Damm W; Frontera A; Tirado–Rives J; Jorgensen WL OPLS all-atom force field for carbohydrates. Journal of Computational Chemistry 1997, 18 (16), 1955–1970. DOI: 10.1002/(SICI)1096-987X(199712)18:16<1955::AID-JCC1>3.0.CO;2-L (acccessed 2020/01/13). - DOI
    8. Soares TA; Hunenberger PH; Kastenholz MA; Krautler V; Lenz T; Lins RD; Oostenbrink C; van Gunsteren WF An improved nucleic acid parameter set for the GROMOS force field. J Comput Chem 2005, 26 (7), 725–737. DOI: 10.1002/jcc.20193. - DOI - PubMed
    9. Pol-Fachin L; Rusu VH; Verli H; Lins RD GROMOS 53A6GLYC, an Improved GROMOS Force Field for Hexopyranose-Based Carbohydrates. J Chem Theory Comput 2012, 8 (11), 4681–4690. DOI: 10.1021/ct300479h. - DOI - PubMed
    1. Guvench O; Hatcher ER; Venable RM; Pastor RW; MacKerell AD Jr. CHARMM Additive All-Atom Force Field for Glycosidic Linkages between Hexopyranoses. J Chem Theory Comput 2009, 5 (9), 2353–2370. - PMC - PubMed
    1. Shi Y; Xia Z; Zhang J; Best R; Wu C; Ponder JW; Ren P The Polarizable Atomic Multipole-based AMOEBA Force Field for Proteins. J Chem Theory Comput 2013, 9 (9), 4046–4063. DOI: 10.1021/ct4003702. - DOI - PMC - PubMed
    2. Patel S; Brooks CL III CHARMM Fluctuating Charge Force Fields for Proteins: I Paramaterization and application to bulk organic liquid simulations. J Comp Chem 2004, 25 (1), 1–16. - PubMed
    3. Wang ZX; Zhang W; Wu C; Lei H; Cieplak P; Duan Y Strike a balance: optimization of backbone torsion parameters of AMBER polarizable force field for simulations of proteins and peptides. J Comput Chem 2006, 27 (6), 781–790. DOI: 10.1002/jcc.20386. - DOI - PMC - PubMed
    4. Halgren TA; Damm W Polarizable force fields. Current Opinion in Structural Biology 2001, 11 (2), 236–242. DOI: 10.1016/S0959-440X(00)00196-2. - DOI - PubMed
    5. Lemkul JA; Huang J; Roux B; MacKerell AD Jr. An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications. Chem Rev 2016, 116 (9), 4983–5013. DOI: 10.1021/acs.chemrev.5b00505. - DOI - PMC - PubMed
    6. Cieplak P; Dupradeau FY; Duan Y; Wang J Polarization effects in molecular mechanical force fields. J Phys Condens Matter 2009, 21 (33), 333102. DOI: 10.1088/0953-8984/21/33/333102. - DOI - PMC - PubMed
    7. Ponder JW; Case DA Force fields for protein simulations. Advances in Protein Chemistry 2003, 66, 27–85. - PubMed
    8. Baker CM Polarizable force fields for molecular dynamics simulations of biomolecules. Wiley Interdisciplinary Reviews: Computational Molecular Science 2015, 5 (2), 241–254. DOI: 10.1002/wcms.1215 (acccessed 2020/01/15). - DOI

Publication types