Structural Proteomics for Drug Target Validation

Comprehensive structural data integration using ToolUniverse tools across PDB, AlphaFold, GPCRdb, SAbDab, and proteomics databases for drug target validation.

LOOK UP DON'T GUESS

• PDB structures/resolutions: PDBeSIFTS_get_best_structures and RCSBGraphQL_get_structure_summary
• AlphaFold confidence: alphafold_get_summary
• Ligands/affinities: PDBe_get_structure_ligands and BindingDB_get_ligands_by_uniprot
• Protein-protein binding mutations (ddG): SKEMPI_search_by_structure/SKEMPI_search_by_protein/SKEMPI_get_mutation -- BindingDB's protein-protein equivalent, for interface-mutation affinity effects rather than small-molecule ligands
• Druggability: ProteinsPlus_predict_binding_sites

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Domain Reasoning

Resolution determines valid conclusions: <2A = atom positions visible; 2-3A = side chains reliable, drug design supported; >3A = backbone only, binding site unreliable. Do not over-interpret low-resolution structures.