Skip to content

Based on my review of the GO-CAM model with ID 62b4ffe300004795 and the relevant literature about insulin receptor signaling, I'll now provide a comprehensive review of this model.

Review of GO-CAM model: gomodel:62b4ffe300004795

General Information

Title: Insulin receptor signaling pathway 1 (Mouse)
Taxon: NCBITaxon:10090 (Mouse)
Status: production
ID: gomodel:62b4ffe300004795

Overview of the Model

This GO-CAM model represents the insulin receptor signaling pathway in mouse. The model captures a classic signal transduction cascade beginning with insulin binding to its receptor and progressing through a series of kinase activities leading to MAPK activation. The model appears to be sourced from Reactome pathways R-HSA-74751 and R-HSA-74752.

Model Structure and Content

The model consists of 11 activities connected by causal relationships, forming a coherent pathway:

  1. Insulin ligands (Ins1 and Ins2) with receptor ligand activity in the extracellular space
  2. Insulin receptor (Insr) with both insulin receptor activity and protein tyrosine kinase activity
  3. Adaptor proteins (Shc1) with transmembrane receptor protein tyrosine kinase adaptor activity
  4. Scaffolding proteins (Grb2) with guanyl-nucleotide exchange factor adaptor activity
  5. Guanine nucleotide exchange factors (Sos1) with guanyl-nucleotide exchange factor activity
  6. Small GTPases (Hras) with protein-membrane adaptor activity
  7. MAP kinase cascade proteins (Raf1, Map2k1, Mapk1, Mapk3) with various kinase activities

The pathway shows the flow of signal from insulin binding to its receptor, through adapter proteins and small GTPases, and finally to the MAPK pathway.

Strengths of the Model

  1. Comprehensive signaling pathway representation: The model captures the core elements of insulin receptor signaling from ligand binding through MAPK activation.

  2. Well-annotated activities: Each activity in the model is properly annotated with relevant molecular functions and is appropriately part of the insulin receptor signaling pathway biological process (GO:0008286).

  3. Appropriate causal relationships: The model uses the correct causal relation predicates, primarily RO:0002629 (directly positively regulates), which is appropriate for direct signal transduction events.

  4. Cellular context: The model appropriately localizes proteins to their correct cellular compartments (e.g., insulin in extracellular space, receptor in plasma membrane).

  5. Evidence support: Each activity and relationship is backed by experimental evidence from published literature with appropriate ECO codes.

Areas for Improvement

  1. Missing relationships: The causal relationship between Sos1 and Hras lacks evidence annotations, even though this is a well-established interaction in the literature. Evidence should be added to strengthen this connection.

  2. Limited representation of pathway branches: The insulin receptor signaling pathway typically branches to activate both MAPK and PI3K/AKT pathways. This model focuses primarily on the MAPK branch. The PI3K/AKT branch, which is critical for metabolic effects of insulin, is missing.

  3. Missing post-translational modifications: The model doesn't explicitly represent phosphorylation events that are crucial for signaling propagation, though they are implied by the kinase activities.

  4. Missing protein complexes: Some interactions, particularly between adaptor proteins like Grb2, Shc, and SOS, typically involve complex formation. This is not explicitly represented in the model.

Consistency with GO-CAM Best Practices

According to the "Signaling receptor activity annotation guidelines", this model follows the best practices for representing receptor-ligand interactions:

  1. The insulin ligands (Ins1 and Ins2) are correctly annotated with receptor ligand activity (GO:0048018) and occur in the extracellular space (GO:0005615).

  2. The insulin receptor (Insr) is correctly annotated with both insulin receptor activity (GO:0005009) and is located in the plasma membrane (GO:0005886).

  3. The causal relation between ligand and receptor activities is correctly represented using the "directly positively regulates" predicate.

  4. The model correctly shows the receptor activating downstream adaptor proteins and signaling cascades.

Scientific Accuracy

The model accurately represents the well-established insulin signaling pathway as described in the literature. The relationships between insulin binding to its receptor, activation of the receptor's tyrosine kinase activity, recruitment of adaptor proteins (Shc1), engagement of the Grb2-Sos complex, activation of Ras, and subsequent activation of the Raf-MEK-ERK cascade are all scientifically accurate.

The literature supports the critical role of Raf1 in insulin signaling (PMID:20056832), which is appropriately represented in this model. The evidence cited in the model (e.g., PMID:18202127, PMID:20889126) supports the connections between insulin receptor activation and MAPK signaling.

Completeness Assessment

While the model captures the core MAPK branch of insulin signaling, it is missing several important aspects of the complete insulin signaling network:

  1. PI3K/AKT pathway: This parallel branch of insulin signaling is crucial for metabolic effects and is not represented.

  2. IRS proteins: Insulin receptor substrate proteins (IRS1-4) are major substrates of the insulin receptor and crucial for signaling, especially to the PI3K pathway.

  3. Negative regulators: The model does not include feedback inhibition or negative regulators of insulin signaling.

  4. Metabolic effectors: Downstream targets of insulin signaling that mediate effects on glucose metabolism are not represented.

Recommendations for Improvement

  1. Add evidence for all causal relationships: Complete the evidence annotations for all relationships, particularly the Sos1 to Hras connection.

  2. Extend the model to include the PI3K/AKT pathway: This would provide a more complete representation of insulin signaling.

  3. Include IRS proteins: Add IRS1 and/or IRS2 as direct targets of the insulin receptor tyrosine kinase activity.

  4. Add negative feedback mechanisms: Include protein phosphatases or other negative regulators that modulate insulin signaling.

  5. Consider representing key complexes: Some interactions in this pathway involve complex formation (e.g., Grb2-Sos1), which could be explicitly represented.

Conclusion

Overall, this GO-CAM model (gomodel:62b4ffe300004795) provides a scientifically accurate representation of the MAPK branch of insulin receptor signaling in mouse. The model follows GO-CAM best practices for representing signaling receptor pathways and has good evidence support. While the model could be expanded to include additional branches and regulatory mechanisms, it effectively captures the core signaling events from insulin binding to MAPK activation.

The model is suitable for production use and provides valuable information about insulin receptor signaling. With the suggested improvements, it could become an even more comprehensive resource for understanding insulin signaling pathways.