tksamc 1.0.1

TKSA - Electrostatic Free Energy calculation for each ionizable residue

TKSA-MC (Python 3)

Tanford-Kirkwood Surface Accessibility - Monte Carlo

This software calculates protein charge-charge interactions via the Tanford-Kirkwood Surface Accessibility model, using either an Exact method (for small systems) or Monte Carlo sampling (for larger systems) to determine protonation states and electrostatic free energies.

Description

This is a Python 3 port of the original TKSA-MC code. It uses mdtraj for structure parsing and SASA calculation, and numpy/numba for efficient computation of electrostatic energies.

The method calculates the electrostatic free energy contribution ($\Delta G_{qq}$) for each ionizable residue.

Requirements

• Python 3.x
• numpy
• scipy
• matplotlib
• mdtraj
• numba (for performance optimization of MC solver)

Install dependencies:

pip install numpy scipy matplotlib mdtraj numba

Installation

You can install the package using pip:

pip install .

This will make the tksamc command available in your terminal.

Usage

Method 1: Installed Package

Run the tksamc command:

tksamc -f sample_pdb_1ubq.pdb -ph 7.0 -T 300.0 -s MC

Method 2: Running Locally (No Install)

If you prefer not to install the package (e.g., for development or testing), you can use the run_local.py script provided in the root directory:

python3 run_local.py -f sample_pdb_1ubq.pdb -ph 7.0 -T 300.0 -s MC

Alternatively, run as a module:

python3 -m tksamc.cli -f sample_pdb_1ubq.pdb -ph 7.0 -T 300.0 -s MC

Arguments

• -f: Input PDB file.
• -ph: pH value (default: 7.0).
• -T: Temperature in Kelvin (default: 300.0).
• -s: Solver method. Choices: EX (Exact) or MC (Monte Carlo). Default: MC.
• -e: Electrostatic method. Default: TK.
• -plot: Generate plot (yes or no). Default: yes.
• -aref: Reference Max SASA set (header or mdtraj). header uses legacy values. mdtraj uses theoretical values for Bondi radii (Tien et al. 2013). Default: header.

Output

• CSV File: A CSV file (e.g., Output_MC_sample_pdb_1ubq_pH_7.0_T_300.0.csv) containing detailed results for each charged residue, including coordinates, pKa, SASA, Charge, and $\Delta G_{qq}$.
• Plot: A JPG plot (e.g., Fig_MC_sample_pdb_1ubq_pH_7.0_T_300.0.jpg) showing the electrostatic free energy per residue. Red bars indicate positive values (unfavorable), and blue bars indicate negative values (favorable).

References

"TKSA-MC: A Web Server for rational mutation through the optimization of protein charge interactions - Vinícius G Contessoto, Vinícius M de Oliveira, Bruno R Fernandes, Gabriel G Slade, Vitor B. P. Leite, bioRxiv 221556; doi: https://doi.org/10.1101/221556"