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. 2017 Feb 15;38(5):276-287.
doi: 10.1002/jcc.24679. Epub 2016 Nov 30.

Residue-centric modeling and design of saccharide and glycoconjugate structures

Jason W Labonte  1 , Jared Adolf-Bryfogle  2 , William R Schief  2   3 , Jeffrey J Gray  1
Affiliations

Residue-centric modeling and design of saccharide and glycoconjugate structures

Jason W Labonte et al. J Comput Chem. .

Erratum in

  • Erratum.
    [No authors listed] [No authors listed] J Comput Chem. 2017 May 15;38(13):1015. doi: 10.1002/jcc.24777. Epub 2017 Mar 16. J Comput Chem. 2017. PMID: 28340288 No abstract available.

Abstract

The RosettaCarbohydrate framework is a new tool for modeling a wide variety of saccharide and glycoconjugate structures. This report describes the development of the framework and highlights its applications. The framework integrates with established protocols within the Rosetta modeling and design suite, and it handles the vast complexity and variety of carbohydrate molecules, including branching and sugar modifications. To address challenges of sampling and scoring, RosettaCarbohydrate can sample glycosidic bonds, side-chain conformations, and ring forms, and it utilizes a glycan-specific term within its scoring function. Rosetta can work with standard PDB, GLYCAM, and GlycoWorkbench (.gws) file formats. Saccharide residue-specific chemical information is stored internally, permitting glycoengineering and design. Carbohydrate-specific applications described herein include virtual glycosylation, loop-modeling of carbohydrates, and docking of glyco-ligands to antibodies. Benchmarking data are presented and compared to other studies, demonstrating Rosetta's ability to predict glyco-ligand binding. The framework expands the tools available to glycoscientists and engineers. © 2016 Wiley Periodicals, Inc.

Keywords: Rosetta; carbohydrates; computation; docking; glycoconjugates; glycoproteins; modeling; oligosaccharides; structure.

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Figures

Figure 1
Figure 1
A comparison of the degrees of freedom (DoFs) found in polypeptide (a) and polysaccharide (b) chains. The first and second residue are labeled and colored red and blue respectively. Torsion angles are indicated by arrows and labeled.
Figure 2
Figure 2
A unified modeling language (UML) diagram of the RosettaCarbohydrate framework. New data objects introduced in this paper are shown with bold rectangles. In UML, solid diamonds (◆) indicate ownership of data, (e.g., Pose owns n Residues); open diamonds (◇) indicate access of data; and arrows describe functional relationships.
Figure 3
Figure 3
A branched, completely unnatural sugar generated with the PyRosetta command pose_from_saccharide_sequence( whacky_sugar, ‘b-D-Fruf-(2->8)-a-Neup5Ac-(2->4)-b-D-GlcpNS6S-(1->4)-[a-D-Xylp-(1->3)]-b-L-GulpA-(1->5)-b-D-Psip’ ), to demonstrate Rosetta’s ability to generate and handle ketoses, uronic acids, L-sugars, sulfated sugars, sialic acids, furanoses, and pentoses. The structure is not refined.
Figure 4
Figure 4
Funnel plots comparing flexible bound–unbound glyco-ligand docking of maltose-binding protein (MBP) with maltotetraose (G4). The docking funnel is steeper when the sugar_bb scoring term is used. 50 decoys were generated per plot.
Figure 5
Figure 5
A PyRosetta script, demonstrating the glycosylate_pose_by_file() function, and its output structure (overlay, CFG colors). A small peptide is first created from sequence, and its main-chain torsion angles are set to typical β-turn values (some lines omitted). After glycosylating, the structure is minimized to remove clashes. The man3.iupac file contains the sequence: a-D-Manp-(1->3)-[a-D-Manp-(1->6)]-b-D-Manp-(1->4)-b-D-GlcpNAc-(1->4)-b-D-GlcpNAc-.
Figure 6
Figure 6
A superimposition of the lowest-scoring Rosetta loop model (CFG colors) and the native structure from IgG Fc–FcγRIII (gray, PDB ID 3AY4). Saccharide residues are shown with thicker lines. Hydrogen bonds are shown in green dashed lines. The initial GlcNAc and terminal Gal residues were fixed as the start and end of a “loop” remodeled using the cyclic coordinate descent (CCD) algorithm with a “cut” in the middle of the loop.
Figure 7
Figure 7
The seven glyco-ligands selected for the glycan docking benchmark. Symbols follow standard CFG notation.
Figure 8
Figure 8
A comparison of ligand docking results. (a)–(c): Plots of interface score in Rosetta energy units vs. ligand RMSD for 5,000 structures created from independent starting configurations. (d)–(f): Rosetta decoys superimposed with the relaxed native structures. Hydrogen bonds are shown with green dashed lines. (d): The decoy with best interface score in CFG colors. (e): The decoy with the second-best interface score in CFG colors and the one with best interface score colored by element. (f): The decoy with the lowest RMSD in CFG colors and the one with best interface score colored by element.
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