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. 2022 Apr;36(4):313-328.
doi: 10.1007/s10822-022-00453-6. Epub 2022 May 4.

Identifying signatures of proteolytic stability and monomeric propensity in O-glycosylated insulin using molecular simulation

Wei-Tse Hsu  1 , Dominique A Ramirez  2 , Tarek Sammakia  3 , Zhongping Tan  4 , Michael R Shirts  5
Affiliations

Identifying signatures of proteolytic stability and monomeric propensity in O-glycosylated insulin using molecular simulation

Wei-Tse Hsu et al. J Comput Aided Mol Des. 2022 Apr.

Abstract

Insulin has been commonly adopted as a peptide drug to treat diabetes as it facilitates the uptake of glucose from the blood. The development of oral insulin remains elusive over decades owing to its susceptibility to the enzymes in the gastrointestinal tract and poor permeability through the intestinal epithelium upon dimerization. Recent experimental studies have revealed that certain O-linked glycosylation patterns could enhance insulin's proteolytic stability and reduce its dimerization propensity, but understanding such phenomena at the molecular level is still difficult. To address this challenge, we proposed and tested several structural determinants that could potentially influence insulin's proteolytic stability and dimerization propensity. We used these metrics to assess the properties of interest from [Formula: see text] aggregate molecular dynamics of each of 12 targeted insulin glyco-variants from multiple wild-type crystal structures. We found that glycan-involved hydrogen bonds and glycan-dimer occlusion were useful metrics predicting the proteolytic stability and dimerization propensity of insulin, respectively, as was in part the solvent-accessible surface area of proteolytic sites. However, other plausible metrics were not generally predictive. This work helps better explain how O-linked glycosylation influences the proteolytic stability and monomeric propensity of insulin, illuminating a path towards rational molecular design of insulin glycoforms.

Keywords: Insulin; Molecular dynamics; O-glycosylation; Protein degradation; Stability.

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Figures

Fig. 1
Fig. 1
Structures of a human insulin monomer and glycoforms studied in this work. Two types of sugar moieties (N-acetylgalactosamine (GalNAc) and mannose (Man) in the α-anomer) with varying lengths (e.g. a mannose monomer, dimer, or trimer) were attached to five different glycosylation sites of insulin, including SerA9 (teal), SerA12 (purple), SerB9 (blue), ThrB27 (orange) and ThrB30 (green) all represented as beads. The glycosylation pattern of each glycoform is implied by its name—for example, GalNAcα (SerA9) represents the glycoform having an N-acetylgalactosamine (GalNAc) attached to the A chain Ser9 residue. Note that glycoforms having a mannose dimer or trimer as the glycan all have a α−1,2-linkage, so Tri-Manα (ThrB27) refers to the glycoform containing an α−1,2-linked tri-mannose at the B chain Thr27 residue.
Fig. 2
Fig. 2
Structures of wild-type insulin models used in this study. (A) The initial monomer structures, after equilibration and before production simulation, are superimposed and are shown from different views. (B) Representative dimer structure illustrating the dimerization interface (colored in salmon). The 3I3Z crystal structure was used to reconstruct an insulin dimer in the first two images. Residues GlyB23–TyrB26 (salmon) are highlighted. The last image shows the superimposed equilibrated wild-type structures with residue labels for the dimer interface.
Fig. 3
Fig. 3
The P- and P’-sites of the two most important cleavage sites, residues PheB25 and TyrB26. The cleavage sites are shown as orange sticks, while the remaining part of the protein is shown in cartoon representation. Schechter-Berger nomenclature for residues surrounding the cleavage sites are shown in varying shades of magenta and are labeled P1–3 and P1’−2’.
Fig. 4
Fig. 4
Classification of occlusion and no-occlusion states. Representative frames from four different glycoform trajectories show occlusion (GF 13, GF 10) and no occlusion (GF 4, GF 8) states. Insulin monomer is presented in translucent blue-white cartoon, dimerization residues presented in salmon sticks, and glycan moiety presented in yellow spheres. The 3I3Z dimer structure is provided as the reference.
Fig. 5
Fig. 5
The SASA of both the scissile bonds and the P1 sites are weakly correlated with α-chymotrypsin half-life, implying moderate predictiveness for the proteolytic stability. (A) The correlation plot between the α-chymotrypsin half-life and the average SASA of the scissile bonds in the glycoforms (GF). (B) The correlation plot between the α-chymotrypsin half-life and the average SASA of the P1 sites in the glycoform (GF). Different regions were colored to indicate glycoforms having longer, comparable, or shorter half-life as compared with the wild type. Uncertainty in Kendall’s tau correlation coefficient (τ) was calculated as described in Section 2.3. The error bars of the α-chymotrypsin half-life were the standard deviations of three experimental repetitions, while the error bars of the computational metrics were calculated as the standard deviations over simulations from the five different wildtype models. The distributions of the SASAs are provided in Supplemental Figure S2.
Fig. 6
Fig. 6
The correlation plot between the α-chymotrypsin half-life and the average β-sheet propensity of residues B22 to B25. The β-sheet propensity of the P1-P3 region does not clearly correlate with α-chymotrypsin half-life. Different regions were colored to indicate glycoforms having longer, comparable, or shorter half-life as compared with the wild type. Uncertainty in the Kendall’s tau correlation coefficient (τ) was estimated as described in Section 2.3. The error bars of the α-chymotrypsin half-life were the standard deviations of three experimental repetitions, while the error bars of the computational metrics were calculated as the standard deviations across simulations from the five different wildtype models.
Fig. 7
Fig. 7
The most proteolytically stable glycoforms tend to have more glycan-involved hydrogen bonds, especially the ones involving the residues PheB24 and ThrB27. The figure shows the percentage of the time each kind of hydrogen bond existed in the MD simulations. The experimental results are summarized such that +(yellow), −(red), and ≈(magenta) respectively indicate that the corresponding glycoform was experimentally found to have higher, lower and comparable proteolytic stability as compared to the wild type. The error bars of the existence percentage were calculated as the standard deviations across the results based on the 5 different wildtype models. Note that in the name of each hydrogen bond, the index of the sugar moiety in the glycan is shown in the bracket following the name of the glycan. The atom type is shown in the parenthesis right after the residue name (see Supplemental Table S6 for more details of the atom types shown in the figure). For example, ThrB27(N)–Man[2](O6) means the hydrogen bond formed between the amide N atom of ThrB27 as the donor and one of the oxygen atoms of the second mannose as the acceptor. Texts for hydrogen bonds that involve any of the P1–P3 or the P2’ residues are colored in blue, which in our case only include PheB24 and ThrB27.
Fig. 8
Fig. 8
Average occlusion analysis distinguishes glycoforms with low, medium, and high occlusion proportion. All five models for each glycoform were averaged for occlusion proportions, with their error bars estimated as the standard deviations of the results based on the 5 different wildtype models. Axis labels in red indicate glycoforms with experimental dimerization data.
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