Compound Collections

The ivybloom CLI is the scriptable surface for the platform, and compound collections are how you create, search, import, and export molecular libraries from the command line. Reach for them when a scripted pipeline needs a managed set of molecules — a screening library to feed batch ADMET or docking, a hit list, a lead series, or a reference set. They give your automation a durable, reusable input surface; for the full command surface, see the CLI overview.

Compound Collections (since v0.8.10)

Create, search, import, and export molecular compound libraries from the command line.

Overview

Compound collections are sets of molecules stored together for analysis. Common use cases:

• Screening libraries — Import compound sets for batch ADMET or docking
• Hit lists — Collect compounds that pass screening criteria
• Lead series — Track optimized compounds through the pipeline
• Reference sets — Maintain known drug or fragment libraries

Creating Collections

ivybloom compounds create "ADMET Hits" --description "Filtered drug candidates" --project proj_abc123

Importing Compounds

Submit a file to import compounds from CSV, SDF, or SMILES formats:

ivybloom compounds import COLLECTION_ID compounds.csv
ivybloom compounds import COLLECTION_ID library.sdf --tag "round1"
ivybloom compounds import COLLECTION_ID compounds.csv --skip-duplicates --wait=false

Supported Formats

Import Parameters

Status

The import endpoint accepts requests and returns status: "pending" with a note, but compounds are not imported yet. The feature is under development. Contact support for ETA.

Searching

Search compounds using four search types: substructure, similarity, text and property. The query goes in a flag, not a positional argument.

Substructure Search

Find all molecules containing a specific substructure (e.g., benzene ring):

ivybloom compounds search COLL_ID --type substructure --smarts "c1ccccc1"

Similarity Search

Find molecules similar to a query (Tanimoto coefficient):

ivybloom compounds search COLL_ID --type similarity --smiles "CC(=O)Oc1ccccc1C(=O)O" --threshold 0.8

Text Search

Search by compound name or metadata:

ivybloom compounds search COLL_ID --query "aspirin" --limit 20

Property Filter

Filter by computed properties:

ivybloom compounds search COLL_ID --type property --filter "mw<500" --filter "logp<5"

Output Examples

NAME          SMILES                              SCORE
aspirin       CC(=O)Oc1ccccc1C(=O)O              1.000
salicylic     OC(=O)c1ccccc1O                    0.823
diflunisal    OC(=O)c1cc(F)c(-c2ccc(F)cc2O)cc1   0.714

Exporting

Export a collection to a file:

ivybloom compounds export COLL_ID --format sdf --output library.sdf

Listing and Deleting

List Collections

ivybloom compounds list
ivybloom compounds list --project proj_abc123 --limit 10 --json

Delete a Collection

ivybloom compounds delete COLLECTION_ID

Workflow Integration

Pipe to Batch ADMET Screening

Export a collection, then screen through ADMET:

# Export as CSV
ivybloom compounds export COLL_ID --format csv --output library.csv

# Create batch file from the library and submit
ivybloom batch submit admet-screen.yaml --wait
ivybloom batch collect BATCH_ID --format csv --output admet-results.csv

Docking Library Preparation

Combine with protein preparation for a complete docking workflow:

# Prepare the protein
ivybloom proteinprep run receptor.pdb --detect-sites --wait

# Export compounds for docking
ivybloom compounds export COLL_ID --format sdf --output ligands.sdf

Read next

• Batch Processing — Screen compound libraries at scale
• Protein Preparation — Prepare targets for docking
• Job Management — Monitor individual analysis jobs
• Recipes — End-to-end drug discovery workflows