firesimulations/autodocking repository overview

⁠Molecular Docking Base

Autodocking, build upon miniconda3, is a set of tools for helping molecular docking.

⁠Versions

• conda: 22.11.1
• mamba: 1.1.0
• python: 3.10.8

⁠Libraries included

⁠Binaries

• ledock: LeDock is designed for fast and accurate flexible docking of small molecules into a protein. It achieves a pose-prediction accuracy of greater than 90% on the Astex diversity set and takes about 3 seconds per run for a drug-like molecule.
• lefrag: LeFrag is designed for in silico FBDD, with a pharmacophore oriented fragmentation algorithm. Its functions include automatic fragmentation of a compound library, similarity search, fragment-based core scaffold hopping, pharmacophore filtering, and substructure search.
• lepro: LePro is designed to automatically add hydrogen atoms to proteins and/or nucleic acids by explicitly considering the protonation state of histidine. All crystal water, ions, small ligands and cofactors except HEM were removed.
• lewater: LeWater is designed to detect unfavorable polar interactions, constrained crystal water and hydrogen bonding penalty at the protein-ligand interface.
• prepare_ligand: ADFRsuite 1.0 ligand preparation using python 2.7
• prepare_receptor: ADFRsuite 1.0 receptor preparation using python 2.7
• qvina2.1: Quick Vina 2 is a fast and accurate molecular docking tool, attained at accurately accelerating AutoDock Vina.
• qvina-w: QVina-W a new docking tool particularly useful for wide search space, especially for blind docking. QVina-W utilizes the powerful scoring function of AutoDock Vina, the accelerated search of QVina 2, and adds thorough search for wide search space.
• smina: Smina is fork of AutoDock Vina that is customized to better support scoring function development and high-performance energy minimization. smina is maintained by David Koes at the University of Pittsburgh and is not directly affiliated with the AutoDock project.

⁠Django project

python -m django --version

django-admin startproject myproject

python manage.py startapp myapp

⁠Docker use

FROM firesimulations/autodocking:2023.1.3

# Set environment variables
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

# The deprecation for the aliases np.object, np.bool, np.float, np.complex, np.str,
# and np.int is expired (introduces NumPy 1.20).
# So, numpy is downgraded to 1.21.5
RUN python3 -m pip install --force-reinstall numpy==1.21.5

# Copy project
COPY . .

# Run django server
CMD [ "python3", "manage.py", "runserver", "0.0.0.0:8000" ]

⁠Links

• Github⁠
• Dockerfile⁠
• Specs File⁠
• Specs File (json)⁠