Research on Neuroimmune Gastrointestinal Diseases Based on Artificial Intelligence: Molecular Dynamics Analysis of Caffeine and DRD3 Protein.

Abstract

Objectives: The aim of this study was to develop a clinical application model for the rational use of caffeine.

Background: Caffeine is related to the incidence of neuro immune gastrointestinal diseases. Coffee consumption needs to be optimized in order to reduce the incidence rate.

Purpose: By using KEEG analysis to explore potential molecular signaling pathways involved in the progression of neurological immune gastrointestinal diseases, and analyzing the details of this signaling Pathway using molecular simulation results, which can support AI system for doctor.

Methods: The research team designed a controlled experiment to analyze the differences in reward and reinforcement of Brain pleasure/addiction and dopamine related signaling pathways function between multiple groups of people with different coffee drinking habits and a blank control group. The study team used molecular dynamics methods to investigate the signaling route that links coffee with the binding of dopamine receptor D3.AI is used to predict the prevalence of gastric reflux disease.

Results: Human experiments have shown a correlation between caffeine intake and gastroesophageal reflux disease. AI algorithm results can provide clinical support, and molecular simulation results are consistent with human experimental results. Caffeine and DRD3 protein have a stable interaction system.

Conclusion: The research team elucidated the intermolecular interaction between caffeine and DRD3, and AI algorithms can predict the likelihood of disease occurrence, providing a new strategy for clinical practice. This study has passed ethical approval at Chifeng Cancer Hospital, and the ethical documents for this study have been submitted to the World Health Organization for filing.