Computational formulation study of insulin on biodegradable polymers

Abstract

Insulin administered orally has a limited therapeutic profile due to factors such as digestion enzymes, pH, temperature, and acidic conditions in the gastrointestinal tract. Type 1 diabetes patients are typically restricted to use intradermal insulin injections to manage their blood sugar levels as oral administration is not available. Research has shown that polymers could enhance the oral bioavailability of therapeutic biologicals, but traditional methods for developing suitable polymers are time-consuming and resource-intensive. Although computational formulations can be used to identify the best polymers more quickly. The true potential of biological formulations has not been fully explored due to a lack of benchmarking studies. Therefore, molecular modelling techniques were used as a case study in this research to determine which polymer is most compatible among five natural biodegradable polymers to address insulin stability. Specially, molecular dynamics simulations were conducted in order to compare insulin-polymer mixtures at different pH levels and temperatures. Hormonal peptide morphological properties were analyzed in body and storage conditions to assess stability of insulin with and without polymers. According to our computational simulations and energetic analyses, polymer cyclodextrin and chitosan maintain insulin stability the most effectively, while alginate and pectin are less effective relatively. Overall, this study contributes valuable insight into the role of biopolymers in stabilizing hormonal peptides in biological and storage conditions. A study such as this could have a significant impact on the development of new drug delivery systems and encourage scientists to utilize them in the formulation of biologicals.

Fig. 1. (A) 2D and (B) 3D non-bonding Interactions (purple and yellow arrows) between monomeric insulin proteins chains A and B.

Fig. 2. Insulin thermal stability (T_g) temperature probability distribution.

Fig. 3. Representative polymer–insulin formulation frames of molecular dynamics simulation.

Fig. 4. Insulin radius of gyration (RG) along with natural biopolymers at 280 and 310 K temperature.

Fig. 5. Comparative amino acids Root Mean Square Fluctuations (RMSF) of monomeric insulin in formulation at (A) 280 and (B) 310 Kelvin with orange color (raw insulin), light green color (poly alginate), pink (poly pectin), blue (poly chitosan), poly dextran as orange color and dark green color (poly cyclodextrin).

Fig. 6. Comprehensive protein backbone Root Mean Square Deviations (RMSD) line plot at (A) 280 K and (B) 310 K of insulin root mean square deviations plots in bioformulation where raw insulin (brown color), poly alginate (purple), polypectin (red).

Fig. 7. Consolidated solvent accessible surface area (Ų) violin plot of insulin in bio-polymer formulation at (A) 280 K and (B) 310 K.

Fig. 8. Molecular dynamics 100 ns insulin–polymer formulation energetics profile at (A) 280 K and (B) 310 K.

Fig. 9. Binding energy analysis of insulin in polymeric formulation at (A) 280 K and (B) 310 K.

Fig. 10. Formulation insulin inter and intra H-bond interactions counts during 100 ns molecular dynamics simulation.