AMDockVS
AMDockVS exposes a composite runtime on top of MolSuite. The official entry point is:
from amdockvs import AMDockVSRuntime
The active public API is organised by domain:
runtime.loader: ligand and receptor loadingruntime.molecules: scopes, filters, sets and access to the general molecular inventoryruntime.complexes: explicit receptor-ligand relations for redocking and rescoringruntime.chemistry: optional chemical preparation tools for ligands and receptorsruntime.qsar: descriptors, activities, datasets and QSAR modelsruntime.pockets: P2Rank installation and cavity predictionruntime.docking: Meeko preparation, grids, docking and result queries
Installation
Python >= 3.12. The three MolSuite dependencies are not on PyPI yet, so they are installed from git first. PyMOL is required and must be installed from conda-forge because it is not distributed on PyPI:
conda create -n amdockvs -c conda-forge python=3.12 pymol-open-source
conda activate amdockvs
pip install "ms_flow @ git+https://github.com/MolSuite/ms_flow"
pip install "ms_components @ git+https://github.com/MolSuite/ms_components"
pip install "ms_contactmap @ git+https://github.com/MolSuite/ms_contactmap"
pip install "amdock-vs @ git+https://github.com/AMDockVS/AMDockVS"
Start the GUI:
amdockvs
Optional extras
pip install "amdock-vs[all]" # or pick one: bblean, pockets, receptors
| Extra | What it adds |
|---|---|
bblean |
BitBIRCH clustering (GPL, invoked through its CLI, never imported) |
pockets |
the jlink-trimmed JDK that P2Rank runs on |
receptors |
OpenMM/PDBFixer receptor rebuilding and minimisation, ProDy fallbacks |
Non-pip dependencies (optional)
| Tool | What for | Installation |
|---|---|---|
autogrid4 |
ad4 scoring | conda install -c conda-forge autogrid |
reduce |
runtime.chemistry.protonate_receptors(method="reduce") |
conda install -c conda-forge reduce |
pdb2pqr |
runtime.chemistry.protonate_receptors(method="pdb2pqr") |
pip install pdb2pqr |
P2Rank 2.5.1 is installed on demand from Molecule Tools → Pocket Detection.
AMDockVS first reuses ~/Downloads/p2rank_2.5.1.tar.gz if it exists, and
otherwise downloads the official distribution and verifies its checksum. Java 17
is likewise installed on demand into the active Conda environment, after a
dry-run check that the transaction will not replace Python, RDKit, PyMOL,
PySide, NumPy, Vina or Meeko. P2Rank is not redistributed inside the application.
The same operation is available from the backend:
runtime.pockets.install_p2rank()
job_id = runtime.pockets.predict(
receptor_ids=[receptor_id],
profile="default",
threads=1,
)
runtime.wait_for_job(job_id)
sites = runtime.pockets.list_predictions(receptor_id=receptor_id)
Minimal workflow
from pathlib import Path
from amdockvs import AMDockVSRuntime
runtime = AMDockVSRuntime()
try:
runtime.create_project(name="demo", folder=Path("./demo_project"))
load_jobs = [
*runtime.loader.load_ligands(["./ligands.sdf"], executor_name="thread"),
*runtime.loader.load_receptors(["./receptor.pdb"], executor_name="thread"),
]
runtime.wait_for_jobs(load_jobs)
chemistry_job = runtime.chemistry.standardize_ligands(executor_name="thread")
runtime.wait_for_job(chemistry_job)
ligand_scope = runtime.molecules.select(role="ligand")
receptor_scope = runtime.molecules.select(role="receptor", limit=1)
descriptor_job = runtime.qsar.compute_descriptors(molecule_set=ligand_scope, executor_name="thread")
runtime.wait_for_job(descriptor_job)
receptor = next(runtime.molecules.stream(receptor_scope))
runtime.docking.set_grid(
receptor_id=int(receptor.id or 0),
center=(12.0, 13.0, 10.0),
size=(20.0, 20.0, 20.0),
)
prep_jobs = [
runtime.docking.prepare_ligands(executor_name="thread"),
runtime.docking.prepare_receptors(executor_name="thread"),
]
runtime.wait_for_jobs(prep_jobs)
receptor_set = runtime.molecules.create_set(receptor_scope, name="default_receptor_set")
docking_job = runtime.docking.run(
ligand_set=ligand_scope,
receptor_set=receptor_set,
executor_name="thread",
)
runtime.wait_for_job(docking_job)
results = runtime.docking.list_results()
finally:
runtime.shutdown()
Async semantics
loader.*,qsar.compute_descriptors(),docking.prepare_*()anddocking.run()submit jobs and return ajob_idor alist[job_id].chemistry.*also submits jobs by default; usewait=Trueorruntime.wait_for_job(...)to block in notebooks.- Waiting is explicit, through
runtime.wait_for_job(...)orruntime.wait_for_jobs(...). runtime.docking.screen(...)is async by default too. Usewait=Trueonly when you want a blocking composite helper.
Design notes
stored_pathkeeps pointing at the base imported artifact.chemistry.*records a current chemical path in metadata; later steps consume it when present.- Vina preparation is stored on
amdock_molecules, without a separate per-state traceability layer. - Inventory reads go through
molsuite.query.project_rows(...); they do not depend on the privateDataAccesshelper.
Examples
License
MIT — see LICENSE.
Metadata
Release files for AMDockVS 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| amdockvs-0.1.0.tar.gz | 743.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| amdockvs-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.5 MB
Release files / amdockvs-0.1.0.tar.gz
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