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Installation

Sicifus requires Python 3.9+.

We strongly recommend using a fresh Conda environment to avoid version conflicts (especially with NumPy/Numba).

# 1. Create a fresh environment
conda create -n sicifus_env python=3.11
conda activate sicifus_env

# 2. Install core numerical stack (prevents binary conflicts)
# Note: We pin numpy<2.0 because Numba is not yet compatible with NumPy 2.0+
# Note: We install llvmlite/numba via conda to avoid build errors on some systems
conda install -c conda-forge "numpy<2.0" scipy matplotlib networkx polars gemmi openmm pdbfixer xtb llvmlite numba

# 3. Install Sicifus
pip install ".[all]"

Fast Installation (uv)

If you prefer uv for lightning-fast package management:

# 1. Create venv
uv venv sicifus_env
source sicifus_env/bin/activate

# 2. Install dependencies
# Note: xtb still needs to be installed via conda or available in PATH
uv pip install "numpy<2.0"
uv pip install ".[all]"

Standard Installation

git clone https://github.com/avenkat/sicifus.git
cd sicifus
pip install .

Dependencies

  • polars: Fast DataFrames.
  • gemmi: Macromolecular structure parsing.
  • numpy & scipy: Numerical computing and alignment algorithms.
  • networkx: Graph/Network analysis.
  • matplotlib: Visualization.
  • rdkit (optional): 2D ligand depiction. Install with pip install sicifus[viz].

Installing with RDKit

For 2D ligand visualization features, you need RDKit.

pip install ".[viz]"

Installing with Energy & Mutation Tools

The [energy] extra installs openmm and pdbfixer, which power both the xTB energy scoring pipeline and the Mutation & Stability Engine (in silico mutagenesis, ddG, alanine scanning, etc.).

# Python dependencies (covers both xTB scoring and mutation engine)
pip install ".[energy]"

# xTB binary (only needed for ligand energy scoring, not for mutations)
conda install -c conda-forge xtb

The mutation engine works entirely through OpenMM and PDBFixer — no external binaries required.

Full Installation

To install everything:

pip install ".[all]"
conda install -c conda-forge xtb