AI Algorithms Identify the Crucial Salt Bridge to Treat Diabetes and Obesity

Type 2 diabetes and obesity have become a global epidemic and pose a major threat to human health. Current treatments include lifestyle modification, oral medications, insulin therapy, and surgical intervention. Yuan J et al. utilized AI-assisted methods to find crucial salt bridges that are difficult to discover with traditional methods. The dual-target agonist can be applied to treat type 2 diabetes and obesity, not only with higher activity but also with a longer half-life in plasma.

Modeling Biological Mechanisms Using AI Algorithms

GLP-1R and GIPR are highly regarded targets for the treatment of type 2 diabetes and obesity. Tirzepatide is a dual agonist peptide that outperforms GLP-1R agonists in glycemic and weight control. Using molecular dynamics simulations, the research found that the key salt bridge formed between non-acetylated Tirzepatide and GLP-1R/GIPR at the K20 site can serve to stabilize the target's activated state conformation, a feature not observed in cryo-electron microscopy structures.

Based on these findings, the team enhanced agonist activity by repositioning the acetylated side chain. The molecular dynamics simulations used in the study were implemented using AI algorithms, which not only dynamically restore the process of molecular action, but also generate more interpretable results.

Experimental Procedure

(1) Molecular dynamics calculation software was used to model the interaction of Tirzepatide with GLP-1R and GIPR. The researchers focused on the effects of salt bridge formation and acetylated side chains at the K20 site on the agonistic activity of the targets.

(2) Based on the simulation results, BGM0504 was designed, which optimizes the interaction with the receptor by changing the position of the acetylated side chain.

(3) A cAMP accumulation assay was performed on BGM0504 to assess its agonist activity towards GLP-1R and GIPR. And the binding affinity of BGM0504 to HSA was tested using the BLI technique.

(4) The in vivo efficacy of BGM0504 was evaluated in db/db mice, including glycemic control, insulin levels, body weight and food intake. The therapeutic efficacy of BGM0504 in diabetes and NASH was assessed in STZ + HFD-induced C57 BL/6 mice.

(5) Pharmacokinetic assessment of BGM0504, including plasma clearance, volume of distribution, half-life, and bioavailability after administration via intravenous and subcutaneous injections, was performed in SD rat and Rhesus monkey models.

(6) Finally, histological assessment, biochemical analysis and statistical analysis were performed.

Optimization Strategy of TirzepatideFig. 1. Structure Analysis and Optimization Strategy of Tirzepatide. (Yuan J.; et al. 2024)

Experimental Results

  • BGM0504 was 2 to 3 times more active than Tirzepatide in agonizing GLP-1R/GIPR, with lower EC50 values, which suggests higher biological activity.
  • BGM0504 showed better blood glucose and insulin level lowering effects than Tirzepatide as well as significant reductions in body weight and food intake.
  • Pharmacokinetic studies in SD rat and Rhesus monkey models have shown that BGM0504 has an extended half-life and high plasma exposure, which supports its potential as a long-acting drug.

As a promising long-acting GLP-1R/GIPR dual-target agonist, BGM0504 shows superior efficacy in the treatment of type 2 diabetes and obesity, and also exhibits the potential to improve liver function and lipid levels in a NASH model, which warrants further clinical research and development.

This research demonstrates the importance and unique benefits of AI technology in today's drug discovery landscape. Protheragen-ING AI-Pharma provides comprehensive AI solutions to aid the development process of innovative drugs. If you are interested in our services or have a question, please feel free to contact us for more details.

Original Article:

Yuan J.; et al. (2024). Molecular dynamics-guided optimization of BGM0504 enhances dual-target agonism for combating diabetes and obesity. Scientific Reports. 2024, 14(1).

Services Related in the Article:

Target Identification
AI-powered Drug Discovery and Design

Inquiry

logo

We harness the power of artificial intelligence to transform the landscape of drug discovery. Our mission is to accelerate the development of life-saving medicines by leveraging cutting-edge AI technologies.

CONTACT US
  • Tel:
  • E-mail:
  • Address:
Top