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@taka78 taka78 released this 07 May 22:14
· 7 commits to dev-beta since this release
v1
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Release: v1.0.0 – Stable SQLite-Backed Multithreaded Screening

This release marks the first stable and performant version of Ultidock, a fully automated molecular docking pipeline optimized for high-throughput virtual screening. It integrates AutoDock Vina with efficient, real-time SQLite data handling and parallel computation.

Key Features

  • Fully integrated pipeline (setup, docking, parsing, analysis) in run.py
  • Parallel docking using Python multithreading for maximum CPU utilization
  • All results written directly to an SQLite database (ultidock_results.db)
  • Robust and configurable filtering with SQL-powered querying
  • Analysis script outputs results to .csv by default, with optional .xlsx support
  • Configurable behavior and paths via a single config.py file
  • Portable directory structure for reproducible runs on different systems

Test Summary

  • Tested using 16-thread CPU with --cpu 2 per ligand (8 parallel ligands)
  • Completed 52 ligand screenings in approximately 30–40 seconds in multiple runs
  • No permission errors or manual intervention required
  • Stable output, verified insertion into the SQLite database, and consistent parsing

Installation & Use

  1. Clone the repository: 
    git clone https://github.com/taka78/ultidock.git
cd ultidock
  2. Run the pipeline: 
    python3 docking/run.py

Exporting Results

The results will be in the docking/RESULTS/date-docking.csv file. If the file is empty, either the analysis parameters are irrelevant for your molecule or the docking attempt was unsuccessful. You should screen a wide range of ligands to account for your molecule's chemistry.

Optional (Excel):

python3 docking/analyse_docking_results.py --out results.xlsx

Version Information

  • Branch: dev-beta
  • Tag: v1.0.0-beta
  • Status: Stable for small-to-large batch virtual screening workflows
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