ezscreen 1.14.0

GPU-accelerated virtual screening CLI — powered by Kaggle GPUs

ezscreen

GPU-accelerated virtual screening powered by Kaggle GPUs.

ezscreen is a CLI tool that runs molecular docking campaigns on Kaggle's free GPUs. It handles receptor preparation, ligand prep, ADMET filtering, Kaggle kernel submission, result download, and hit visualisation — all from an interactive full-screen TUI or a classic CLI.

Prerequisites

• Python 3.11+
• A Kaggle account with GPU quota and an API token (kaggle.json)
• (Optional) NVIDIA NIM API key for Stage 2 validation with DiffDock-L

Installation

pip install ezscreen

Optional: scrubber for enhanced ligand prep

forlilab/scrubber provides tautomer enumeration and pH-driven protonation. Not on PyPI — install separately:

pip install git+https://github.com/forlilab/scrubber.git

Without it, ezscreen falls back to RDKit-only preparation (still fully functional).

Setup

ezscreen auth

Prompts for your Kaggle kaggle.json path and optionally an NVIDIA NIM API key.

Quickstart — TUI

Launch the full-screen interface:

ezscreen

This opens the home dashboard. From there:

• Press r to open the Run Wizard (5-step guided docking pipeline)
• Press s to open the Status Monitor (live run tracking)
• Press ? for the full keybindings reference

Run Wizard walkthrough

1. Receptor — enter a PDB ID (downloaded automatically from RCSB) or a local .pdb path. Select chains.
2. Binding site — choose from co-crystal ligand, residue list, P2Rank prediction, or blind whole-protein.
3. Ligand library — path to a .smi, .smiles, or .sdf file.
4. Options — toggle ADMET pre-filter and set search depth (Fast / Balanced / Thorough).
5. Summary + submit — review all parameters including box coordinates, then submit to Kaggle.

Results appear in the TUI Results screen when the Kaggle kernel completes.

Quickstart — CLI

ezscreen auth          # set up credentials once
ezscreen run           # guided CLI wizard
ezscreen status        # track running jobs
ezscreen view <run_id> # show results table and open 3D viewer

See examples/1hsg_quickstart.md for a full end-to-end walkthrough against HIV-1 protease.

Commands

Command	Description
ezscreen	Launch full-screen TUI (default when no subcommand given)
ezscreen tui	Alias for the above
ezscreen auth	Configure Kaggle and NIM credentials
ezscreen status	List all runs with status (auto-refreshes)
ezscreen view <run_id>	Show results table and open 3D viewer
ezscreen admet <file>	Standalone ADMET filtering on any SDF or SMILES file
ezscreen validate <receptor> <hits>	Stage 2 re-docking via NVIDIA NIM DiffDock-L
ezscreen clean <run_id>	Delete Kaggle dataset and kernel artifacts

Features

• Full-screen TUI — Textual-based interface with dashboard, run wizard, live status monitor, and results viewer
• UniDock GPU docking — builds UniDock from source on Kaggle to match the installed CUDA toolkit
• Tiered binding site detection — co-crystal, residue Cα box, P2Rank top-3, or blind fallback
• ADMET filtering — Lipinski, Veber, PAINS, Brenk toxicophores applied locally before submitting to reduce wasted GPU time
• Compound identity — results include the original name and SMILES alongside docking scores
• Artifact filtering — unphysical scores (below −15 kcal/mol) removed automatically
• Resilient download — exponential backoff retry; local score recovery from PDBQTs if download fails
• 3D viewer — self-contained py3Dmol HTML viewer for top poses
• DiffDock-L validation — NVIDIA NIM integration for high-accuracy re-docking of top hits
• Checkpoint resume — SQLite-backed run state; interrupted runs can be resumed mid-shard
• Desktop notifications — optional toast on run completion via plyer

Screenshots

License

Apache-2.0