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Discover novel small-molecule binders for protein targets using structure-based and ligand-based screening. Covers druggability assessment, known-ligand mining (ChEMBL, BindingDB), similarity expansion, ADMET filtering, and synthesis feasibility.
Passed 10 of 15 test cases with the skill, and 8 of 15 without it.
and 1 more in the full report
4 fixed10 passed either way6 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
When passing a SMILES string to the ADMETAI prediction tool to evaluate bioavailability and toxicity, standard tools take a single string argument like `smiles="c1ccccc1"`. What data type does the ADMETAI tool require for its `smiles` argument?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies that the smiles parameter must be passed as a Python list. | Missed | Passed |
The instructions your model reads when the skill loads.
Systematic discovery of novel small molecule binders using 60+ ToolUniverse tools across druggability assessment, known ligand mining, similarity expansion, ADMET filtering, and synthesis feasibility.
LOOK UP DON'T GUESS - Always retrieve actual data from tools before drawing conclusions. Do not assume druggability, binding sites, or compound properties based on target class alone.
KEY PRINCIPLES:
Before any tool call, reason about the target's structural biology:
Is the binding site a well-defined pocket (small molecule accessible) or a flat protein-protein interface (needs peptide/macrocycle)? This determines your screening strategy.
MolGlueDB_search_compounds/MolGlueDB_get_compound for known glue chemotypes before declaring the target undruggable by small molecules.MolGlueDB_search_compounds in case the target is a documented molecular-glue neosubstrate.Use this reasoning to select phases and warn the user about challenges before executing a full workflow.
DO NOT show search process or tool outputs to the user. Instead:
test cases passed, vs 8 / 15 without
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