drug-target-interaction
Computational drug-target interaction prediction and virtual screening
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill drug-target-interaction --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Drug-Target Interaction Prediction A skill for computational prediction of drug-target interactions (DTI), covering molecular docking, machine learning-based binding affinity prediction, compound library screening, and target identification using cheminformatics and structural biology tools. ## Drug-Target Interaction Databases ### Key Data Resources | Database | Content | Access | |----------|---------|--------| | ChEMBL | 2.4M compounds, 15M bioactivities | REST API, SQL dump | | BindingDB | 2.8M binding data points | Bulk download, REST API | | DrugBank | 15,000+ drug entries with targets | Academic license | | PDB (Protein Data Bank) | 220,000+ 3D structures | Free download, REST API | | UniProt | 250M+ protein sequences | Free, REST API | | STITCH | Chemical-protein interactions | Free academic access | ### Fetching Bioactivity Data ```python from chembl_webresource_client.new_client import new_client def get_target_bioactivities(target_chembl_id: str, activity_type: str = "IC50", max_nm: float = 10000) -> list[dict]: """ Retrieve bioactivity data for a protein target from ChEMBL. Returns compounds with measured binding/inhibition values. """ activity = new_client.activity r
- Drug-Target Interaction Databases
- Key Data Resources
- Fetching Bioactivity Data
- Molecular Fingerprints and Descriptors
- Computing Molecular Representations
- Machine Learning for DTI Prediction
- Binary Classification Model
- Deep Learning Approaches
- Molecular Docking
- Structure-Based Virtual Screening
- Validation and Benchmarking
- Tools and Libraries
What does the drug-target-interaction skill do?
Computational drug-target interaction prediction and virtual screening
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill drug-target-interaction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.