Supplementary File 1: AI-Driven Peptide Discovery for IL-6 Signaling Modulation

An integrated AI-assisted discovery pipeline identified peptide P01 as a top-ranked IL-6R antagonist. The workflow incorporated immunoinformatics safety screening, structural modeling, molecular docking, and 100-ns molecular dynamics simulations. Experimental validation confirmed P01 inhibits IL-6/IL-6R binding with an IC50 of approximately 1.6 µM.

Use Cases

• Validate AI-assisted peptide discovery workflows based on the described integrated pipeline.
• Benchmark molecular docking and dynamics simulations against experimental binding assays.
• Study safety-focused peptide design based on immunoinformatics screening for toxicity and allergenicity.
• Develop complementary therapeutic modalities for IL-6-driven inflammatory diseases based on the peptide antagonist foundation.

Strengths

• The study reports a specific IC50 value (≈1.6 µM) for the lead peptide's inhibitory activity.
• The computational pipeline included a 100-ns molecular dynamics simulation for stability assessment.
• Experimental validation was performed using competitive ELISA and cell-based STAT3 phosphorylation assays.
• The dataset is openly available under a CC-BY-4.0 license.

Limitations

• The dataset is a single 909.4 KB DOCX file, indicating a limited scope of supplementary material rather than a large-scale data repository.
• Column-level documentation is absent; field semantics must be inferred from the document text.
• Row count is unknown, which may limit suitability assessment for quantitative analysis.

Provenance

Source

figshare

Collection Method

Integrated AI-assisted discovery pipeline incorporating immunoinformatics, structural modeling, docking, and molecular dynamics.

Freshness

Last updated 2026-04-29 05:57:06; freshness should be verified.