The aggregation stability of protein therapy has always been a great challenge.
For example, insulin used for diabetes treatment will show aggregation phenomenon under acidic pH value, temperature rise or stirring, resulting in the complexity of production, storage, purification and infusion. Previous studies have found that the oligomeric stability of insulin analogues may be related to the early stage of aggregation of insulin monomers, especially the partial folding intermediate (PFI) in the folding unfolding pathway.
A set of methods for the rational design of aggregation inhibitors include the development of molecules that destroy fibers, such as the design of peptide or non peptide β – fragment analogues, and the screening of molecules that disrupt aromatic stacking interactions. Recently, a structure-based computer-aided design has successfully expanded the screening method to identify new inhibitors from a large number of designed peptides. The method of designing early aggregation inhibitors in this paper is based on the destruction of insulin dimer.
Protein protein interaction (PPI) has been shown to be mediated by a small number of residues, which provides the possibility of replacing large proteins with small peptides to simulate the interactions of these “hot” residues.
In this study, the binding interface residues of natural monomer (n) in npfi insulin homodimer were used as templates to design peptides with high specificity for PFI, which is easy to aggregate insulin. The most stable set of npfi homopolymers was determined, and then the hot spots were determined according to the area of residues embedded in the interface. Firstly, peptides were screened from the interface fragments of natural monomers according to the conformational similarity with the starting domain of natural monomers.
The second screening is to select the peptide binding to the same PFI residues as the source domain, which simulates the interaction at the n-pfi interface. The inhibitory effects of the selected peptides on insulin aggregation and denaturation were evaluated by size exclusion chromatography and far ultraviolet circular dichroism chromatography, respectively. The specificity and micellization thermodynamics of the peptide were evaluated by isothermal titration calorimetry. Finally, the effect of peptide on glucose uptake of HepG2 cells was determined by enzyme labeled spectrophotometry.
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Author information
Prof. Anurag s. rathore and GAURAV goel, Department of chemical engineering, Indian Institute of Technology
Protein target
Partial folding intermediates (PFIs) of insulin
computing method
Protein protein docking, molecular dynamics
Computing software
Hex: docking conformation for the formation of npfi complexes
Pepfold: low energy conformation for each peptide
GROMACS: for molecular dynamics simulation
Calculation process
Based on the previous simulation of Insulin protein, 14 PFIs structures were selected for docking insulin natural monomer n to determine the key residues that may participate in the formation of npfi complex. Next, the binding interface residues of npfi complex were used as templates to design peptides with high specificity for PFI, and the fragments were sorted by cumulative binding interface area Δ asementn PFI;
After further screening and modification, three 9-peptide molecules were selected for further functional verification, and MD simulation showed that they could stably bind to PFI; combined with the experimental results, two nine peptide molecules that can effectively inhibit insulin aggregation were obtained: (R6) P3 (eaayl Agly), & nbsp
（R6）P19（AAYLVAGLY）。
research contents
Five metastable sets, one lowest free energy natural state, one unfolded state, and three metastable intermediates were measured under amyloid formation (pH 2330k). These intermediates are associated with insulin aggregation and have higher natural contact with the unfolded state, which are referred to as partially folded intermediates (PFIs). Each PFI set consists of a set of dynamic structures, and the attractor is the lowest free energy structure in the ensemble.
32 PFI structures are obtained from three PFIs sets for the analysis in this paper. Gromos algorithm was used to group these PFIs, and 14 clusters pfi1-pfi14 were obtained. The cut-off value of root mean square deviation (RMSD) of C α was 0.3 nm.
Based on the C α contact diagram (distance cut-off, 0.95 nm) and residue aggregation tendency (a3d score), the structural similarity of 14 PFI conformations was further evaluated, which showed that these PFI conformations were very obvious (table S1 in supporting information). It shows complete secondary structure loss and higher solvent accessible surface area Sasa (table S2 in supporting information) than primary ensemble.
Figures 1a and b show the surface distribution of the most stable solution structure (NATURAL ensemble attractor) and easily aggregated residues in a PFI, respectively. Figure 1C shows the average (μ) a3d score and the related standard deviation (σ) for each residue in the 14 PFIs. As expected, a larger proportion of residues in PFIs have positive a3d scores, and the overall number is higher than that in the original state, indicating that residues with large positive a3d values are related to protein aggregation。
In addition, PFI has hydrophobic plaques formed by spatially linked and easily aggregated residues, so it is expected to show a higher aggregation tendency. It is also noted that there is a large correlation standard deviation among the residues, which indicates that the binding interface of PFIs is is significantly heterogeneous.
However, the difference was mainly due to the size of a3d scores rather than symbols. The a3d scores of 11 out of 14 PFIs of 22 residues in the same group were positive, while the a3d scores of 16 residues in the same group were negative in 12 out of 14 PFIs (Fig. S2 in support information). In addition, different PFIs are close to each other in motion, so 14 PFI can be regarded as a single ensemble to determine the association hot spot residues.
Fig. 1. Conformational study of PFI with different structures
Source jcim
The combination of natural monomers with easily aggregated intermediates is considered to be the early nucleation step of insulin aggregation. As shown in the program diagram in Fig. 2a, natural monomers were butted with each PFI (a total of 28) to determine the residues most likely to participate in the formation of this npfi complex. A total of 14000 npfi structures were obtained by rigid docking, which were divided into 4353 subgroups by gromos clustering method. The cut-off value of C α – RMSD was 0.3nm.
The cluster free energy fraction GC of each subset is calculated by using the combined free energy of a given cluster structure. Figure 2C shows that for the first few most stable clusters, GC has a large increment, and the spacing of subsequent clusters is much smaller. The stability of the central structure of the most stable cluster (the lowest GC, as shown in Fig. 2b) was evaluated by molecular dynamics simulation of GROMACS.
When n and PFI monomers separated along the direction perpendicular to the bonding interface, they were recombined into dimers and remained intact in five independent 200 ns simulations. Figure 2B shows the key stable interactions in this most stable complex.
The binding interface consists of 13 residues from natural monomers n (i10, C11, S12, L13, Y14, L16, F22, V23, H31, L32, E34, A35, and L38) and 11 residues of PFI (G1, I2, Q5, C6, C7, T8, H26, L27, C28, H31 and E34). Most of the interfacial residues in natural monomers belong to the α – helix (r12r20) at the C-terminal of a chain and the α – helix of B chain (r30r40), which are involved in the formation of insulin fibrils at low pH.
It was further found that the npfi complex was mainly stabilized by four pairs of hydrophobic residues, namely l13ni2pfi, l13nl32pfi, f22nl27pfi and v23nl27pfi. Two interfacial hydrogen bonds between h31n and t8pfi side chains and between y14n side chains and i2pfi main chains were also determined. H31 has been shown to play a key role in the stabilization of insulin nuclear aggregation, indicating the importance of electrostatic interactions in the aggregation process. In order to obtain a larger spectrum of important intermolecular interactions, the central structures of 15 most stable clusters were used to identify the binding domains on N and PFI monomers.
Figures 3a and b show the average and standard deviation of the binding interface area of natural monomers and PFI residues in 15 npfi dimers, respectively. The normalized binding interface area (Δ ain PFI) of N and PFI monomers has a large standard deviation, which indicates that there is significant heterogeneity of the binding interface residues.
N and PFI monomers have 43 and 50 different residues, respectively, and at least one dimer has a positive Δ ain PFI. These results are consistent with the larger changes in the tendency of residue aggregation in PFIs (Fig. 1c).
The authors used Δ ain PFI of an average of 15 npfi dimers as a proxy for determining the aggregation hot spots. Fig. 3C, D shows a good correlation between Δ an PFI and the binding energy of mm / PBSA. Residues L38, L13, H31, E34, I10, y37, y47 and P49 have the largest Δ ain PFI for natural monomers, and residues F46, y37, I2, L27, E34, r43, F45, N18, Q5, H31, T48 and C28 have the largest Δ ain PFI for PFI (see supporting information table S5). Some interactions among these residues are considered to be important factors in the formation of insulin aggregation nuclei and fibrils. The existence of polar residues on the binding interface indicates that hydrophobic and electrostatic interactions will jointly control the initial stage of insulin fibrillation.
It is also found that the natural monomer interface in npfi dimer is closely related to the receptor binding domain of insulin, thus linking the active conformation of insulin with its higher aggregation tendency. The above results indicate that the relatively clear regions on natural monomers combine with different regions of PFIs. In addition, although the composition of the binding interface is heterogeneous at the first-order sequence level, these different regions have similar composition in terms of residue polarity.
A peptide with high specificity for PFI, which is easy to gather insulin, was designed by using the binding interface residue of npfi insulin and natural monomer (n) in dimer as template. The fragments were sorted by cumulative binding interface area Δ asementn-pfi. For any 9-mer fragment, r31-r39 had the highest Δ asementn-pfi = 33.4; for any 5-mer fragment, r10-r14 and r45-r49 had the highest Δ asementn-pfi = 22.2, 14.4. Protein to protein interactions involving these fragments have been shown to stabilize mature insulin fibers.
Peptides from these fragments have been shown to reduce insulin aggregation rate and / or increase aggregation delay time. The peptides in the two studies were obtained only from a sequence linked aggregation region of natural monomers and bound to natural monomers and PFIs. In this study, we designed a peptide with higher specificity for insulin PFIs by using adjacent and sequentially linked fragments in space. The peptide sequence is composed of two adjacent fragments in a residue pair. This is achieved by inserting glycine residues, GA dipeptides or GAA tripeptides according to the distance between the C α atoms of the residue pair (see FIG. 4A, b).
A total of 12101 peptides with a length of 2-40 residues were obtained. The total contribution of residues in the sequence to the standardized binding interface area (Δ apeptiden PFI) was sequenced. The size of the peptide is limited to 9 residues because it has been proved that the peptide with similar length can effectively inhibit insulin aggregation. A total of 665 nine polymers with Δ apeptiden PFI values between 9.8 and 34.5 were obtained, of which 20 were better (see supporting information figure S4). Next, eight unique sequences were obtained, namely P1, P2, P3, P13, p16, P18, P19 and P20.
According to their conformations and the conformation of peptide PFI complex, the following two points were selected: (I) the peptide PFI complex has good binding free energy; (II) the peptide PFI complex is highly similar to the PFI residue at the interface of n-pfi dimer. The peptides P1 (icslgavly) and P19 (aaylvagly) with high cos θ value and the most prominent sequence P3 were selected (eaaylagly) to characterize the effect of inhibiting insulin aggregation. The minimum RMSD conformations of peptides P1, P3 and P19 overlap with the corresponding interface regions of natural monomers, respectively, as shown in Fig. 4c-e.
Figure 5A shows that at least one of the three peptides has a high cos θ for each npfi dimer. Figure 5b-d shows the overlapping plots of peptide PFI complex and n-pfi complex, corresponding to the highest cos θ corresponding to peptides P1, P3 and P19 respectively. As expected with high cos θ, the peptide was designed to mimic npfi interaction and thus bind to PFI at the same location as the natural monomer. However, the high proportion of hydrophobic residues in the designed peptide makes it incompatible with water-based preparations.
It is suggested that three arginine residues should be inserted to increase water solubility. Since previous studies have shown that hexa arginine as a disruption domain can achieve significant aggregation inhibition, the authors have added the same domain to the N-terminal of the designed peptide. The polar damage domain composed of short fragments has little effect on aggregation inhibition. The final sequence of amphiphilic peptide was r6icslgavly ((R6) P1), r6eaaylagly ((R6) P3) and R6 aaylvalley ((R6) P19). Furthermore, the most stable and highest cos θ peptide PFI complex was simulated by MD.
Through trajectory analysis, peptides (R6) P1 and (R6) P3 maintained contact with PFI and bound to PFI (see supporting information figure S5), while (R6) P19 was separated first and then re contacted with PFI.
The stability and receptor binding properties of insulin were evaluated by bioanalysis. Figure 6a-c shows the loss of monomer insulin and the data of oligomer in the presence and absence of peptide. All three peptides retained the monomer insulin to varying degrees in a concentration dependent manner (Fig. 6a). The effective concentration range of (R6) P1 was significantly different, which was related to the micellization behavior of these peptides.
The far UV spectrum of the best concentration formula of peptide is shown in Fig. 6D. In conclusion, these data suggest that peptides (R6) P3 and (R6) P19 effectively inhibit insulin aggregation, retain 90% of insulin in monomer form, and almost completely retain their natural α – helix rich conformation.
In addition, the monomer loss rate remained stable over a long period of time (Fig. 6b), indicating a mechanism by which aggregation prone PFI can be isolated by binding with inhibitor molecules to inhibit the early stage of insulin aggregation and nucleation. To further elucidate the stable patterns of (R6) P3 and (R6) P19, the authors studied their binding to natural insulin using ITC (see supporting information figure S8).
The SEC chromatograms (not shown here) of the sample cells before and after ITC measurement overlapped, indicating that only natural insulin monomer existed in the whole measurement process. Since the peptides and proteins in this study are highly positively charged in the pH range of 23, the formation of peptide PFI complex will be dominated by hydrophobic interaction,
This explains that the optimal stable concentration observed is close to the critical micelle concentration of each peptide. Figure 7 shows the relative absorbance of different insulin preparations (with or without peptide) at 412 nm, which are consistent with the data in Figure 6. The results showed that RP3 (6%) and RP3 (6%) remained active after incubation.
conclusion
In order to limit the homodimerization of insulin, a series of peptides with high specificity for PFI which is easy to aggregate insulin were designed rationally by using the binding interface residue of natural monomer (n) in npfi insulin homodimer as template. When the peptide / insulin molar ratio was 6:1 and 2:1, 15 mer peptides (R6) eaaylagly ((R6) P3) and (R6) aaylvalley ((R6) P19) were the most effective.
These peptides retained more than 90% of insulin in monomer form and showed characteristic α – helix tilt in CD spectra after 72 hours of incubation under amyloidosis. Under the same conditions, the preparation without peptide showed complete loss of monomer insulin and insulin activity. The formula composed of (R6) P3 and (R6) P19 retained 78% and 85% natural insulin activity respectively after 72 h incubation, so it is hopeful to further develop.
reference:
Mishra, Avinash , et al. Structure-Based Design of Small Peptide Ligands to Inhibit Early-Stage Protein Aggregation Nucleation. J. Chem. Inf. Model. 2020, 60, 33043314
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