SciMesh

SciMesh is a scientific-workload framework for molecular datasets. Its public CLI runs exact similarity search and sparse similarity-graph construction locally in one Python process; it creates no dense similarity matrix. The Go/PostgreSQL coordinator and Python worker can run a diagnostic, shard-based similarity-search pipeline locally. Its CSV artifacts are not a global result until CTX-07--09 add planning and reduction; use the local CLI for scientific results today. See STATUS.md.

The ChEMBL TSV database is intentionally not included in this repository. Download it separately and pass its path to the commands below. The expected columns are chembl_id and canonical_smiles.

Installation

SciMesh requires Python 3.10+ and RDKit.

python -m venv .venv
source .venv/bin/activate
pip install -e .

RDKit can alternatively be installed from conda-forge:

conda install -c conda-forge rdkit
pip install -e .

Quick start

Run the built-in help command for copy-paste examples of both workloads:

scimesh help

It includes environment setup, output-directory creation, similarity search by ChEMBL ID or SMILES, and similarity-graph construction. Use the standard help for the complete option reference:

scimesh similarity-search --help
scimesh similarity-graph --help

Similarity search

similarity-search finds the top-k molecules most similar to a query. The query is supplied either by ChEMBL ID or by SMILES. It uses Morgan fingerprints with radius=2 and fpSize=2048, Tanimoto similarity, streaming TSV reads, and a bounded heap. Invalid SMILES and the query molecule are skipped.

scimesh similarity-search chembl_37_chemreps.txt \
  --query-id CHEMBL939 \
  --top-k 20 \
  --output results.csv

Use a SMILES query when it is not identified by ChEMBL ID:

scimesh similarity-search chembl_37_chemreps.txt \
  --query-smiles 'COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1' \
  --top-k 20 \
  --output results.csv

The output CSV contains rank,chembl_id,canonical_smiles,similarity. Search progress and valid/invalid-SMILES statistics are written to the terminal. --max-rows limits the candidate scan for small tests, while --progress-every 0 disables progress reports.

To find the least similar molecules, use --threshold-direction less. This ranks results from the lowest similarity upward; --threshold optionally limits them to values less than or equal to a cutoff:

scimesh similarity-search chembl_37_chemreps.txt \
  --query-id CHEMBL939 \
  --threshold-direction less \
  --threshold 0.1 \
  --top-k 20 \
  --output least_similar.csv

To render the query and retained candidates:

scimesh similarity-search chembl_37_chemreps.txt \
  --query-id CHEMBL939 \
  --images-dir structures

This writes query.png and top_candidates.png into structures.

Similarity graph

similarity-graph constructs an exact sparse undirected graph. Every valid molecule is a vertex; an edge is emitted when Tanimoto similarity satisfies the selected threshold direction (>= by default, or <= with --threshold-direction less). Each fingerprint is calculated once. Comparisons are processed block by block, each pair is tested once (i < j), and no dense N×N matrix is created or stored.

scimesh similarity-graph chembl_37_chemreps.txt \
  --max-rows 10000 \
  --threshold 0.7 \
  --block-size 1000 \
  --output similarity_graph.csv

The deterministic edge-list CSV has source_id,target_id,similarity columns. The command reports valid molecules, checked pairs, emitted edges, rate, and elapsed time. --block-size changes only how comparisons are grouped, not the result.

Development

pip install -e '.[dev]'
pytest

The package separates common dataset parsing and fingerprints from independent workloads. Add future workloads through the workload registry without changing the main CLI.