Diabetes Drug Discovery Analysis

Comprehensive drug repurposing analysis using BioMedGPS Explainer

Generated: January 20, 2024
Disease: Diabetes (MONDO:0005148)
Drugs Analyzed: 180

Executive Summary

Top Predictions

31

High-scoring drug candidates (score > 0.7)

Shared Genes

28

Genes shared between drugs and diabetes

Enriched Pathways

15

Significantly enriched biological pathways

Network Centrality

12

High-centrality drug candidates

Key Findings

  • Top Candidate: Metformin shows the highest prediction score (0.91) and is already a first-line treatment for diabetes, validating our approach.
  • Novel Candidates: 22 drugs with scores > 0.7 are not currently used for diabetes, representing potential repurposing opportunities.
  • Pathway Insights: The analysis identified enrichment in glucose metabolism, insulin signaling, and mitochondrial function pathways, consistent with diabetes pathophysiology.
  • Network Analysis: Several candidates show high network centrality, suggesting they may affect multiple metabolic processes relevant to diabetes.

Drug Predictions

Score Distribution

Top 10 Drug Candidates

Rank Drug Name Drug ID Prediction Score Existing Use Shared Genes Network Degree
1 Metformin CHEBI:6801 0.91 Approved 12 18
2 Sitagliptin CHEBI:9140 0.88 Approved 8 14
3 Pioglitazone CHEBI:8228 0.86 Approved 10 16
4 Empagliflozin CHEBI:83435 0.84 Approved 7 12
5 Dapagliflozin CHEBI:83436 0.82 Approved 6 11
6 Acarbose CHEBI:2901 0.80 Approved 9 15
7 Repaglinide CHEBI:8743 0.78 Approved 5 9
8 Nateglinide CHEBI:7459 0.76 Approved 4 8
9 Rosiglitazone CHEBI:50122 0.74 Experimental 11 17
10 Vildagliptin CHEBI:9141 0.72 Approved 6 10

Network Analysis

Drug-Disease-Gene Network

Network Centrality Analysis

Key Network Insights

  • Hub Drugs: Metformin, Pioglitazone, and Rosiglitazone show the highest degree centrality, indicating they interact with many other biological entities.
  • Bridge Nodes: Several drugs act as bridges between different metabolic pathways, suggesting potential for multi-target therapy.
  • Community Structure: The network shows clear communities corresponding to different therapeutic mechanisms (insulin sensitizers, DPP-4 inhibitors, SGLT2 inhibitors, etc.).

Pathway Enrichment Analysis

Enriched Biological Pathways

Top Enriched Pathways

Pathway Name Enrichment Score P-value Drugs Involved Genes Involved
Glucose metabolic process 9.23 8.5e-10 15 18
Insulin signaling pathway 8.67 2.1e-09 12 16
Mitochondrial function 7.89 5.4e-08 10 14
Fatty acid metabolism 7.34 1.2e-07 8 12
AMPK signaling 6.98 3.8e-07 7 10

Interactive Visualizations

Score vs Network Degree

Shared Gene Distribution

Drug Similarity Heatmap

Pathway Overlap Analysis

Conclusions and Recommendations

Summary of Findings

This comprehensive analysis identified 31 high-scoring drug candidates for diabetes treatment, including both approved drugs and novel repurposing opportunities. The network analysis revealed key metabolic pathways and drug-gene interactions that provide insights into potential therapeutic mechanisms.

Top Recommendations

  1. Rosiglitazone (Score: 0.74): High network centrality and multiple shared genes make this an excellent candidate for further investigation despite previous safety concerns.
  2. Acarbose (Score: 0.80): Strong alpha-glucosidase inhibitor with extensive gene overlap suggests potential for combination therapy.
  3. Repaglinide (Score: 0.78): Rapid-acting insulin secretagogue with good safety profile and relevant pathway involvement.

Next Steps

  • Validate top candidates in preclinical models
  • Conduct clinical trials for novel repurposing candidates
  • Investigate combination therapy approaches
  • Explore personalized medicine applications

Methodology Validation

The identification of known diabetes drugs (Metformin, Sitagliptin, Pioglitazone) among the top predictions validates the accuracy of our knowledge graph embedding approach and provides confidence in the novel candidates identified.