ZWINT Interactome: Protein Binding Scores for 10 Candidate Interactions

Seven candidate proteins, plus three negative controls, were tested for binding potential to the ZWINT protein using a novel AI-integrated workflow. The dataset includes computational results from AlphaFold, RoseTTAFold, TM-Align, and HADDOCK, serving as proof-of-concept evidence for a PPI prioritization methodology. It was authored by Nora Abdelfattah and last updated in April 2026.

Use Cases

• Prioritizing protein-protein interaction candidates for experimental validation based on computational binding scores.
• Benchmarking AI protein folding tools (AlphaFold, RoseTTAFold) against known interactors like SNAP25 and CAMK2A.
• Developing hypothesis generation pipelines for neuropathic pain pathway research using proteins like BLOC1S2.

Strengths

• Includes three known positive control interactors (SNAP25, CAMK2A, UBC) and three negative controls for method validation.
• Results from multiple established computational tools (AlphaFold, RoseTTAFold, TM-Align, HADDOCK) are combined.
• Dataset is 54.5 MB and available in multiple formats (PDF, DOCX, XLSX, PDB) for different analysis needs.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The exploratory candidate interactions have not been validated with real-world experimentation.

Provenance

Source

figshare

Collection Method

Computational workflow using AlphaFold, RoseTTAFold, TM-Align, and HADDOCK to score protein binding.

Freshness

Last updated 2026-04-22 17:42:10; freshness should be verified.