pyLiBELa is our first attempt to expose all the existing LiBELa functions to a Python environment. We want to bring ligand docking to everyone through easy-to-use platforms such as Jupyter Notebook or Google Colab.
The code is currently being converted using Boost Python functions, allowing C++ code to be executed integrated in the Python environment.
Some new functions are also under develoment, including some GPU-based function to speed-up interaction energy calculations and interaction grid generation.
The project is under active development. Stay tuned to more info!!!
LiBELa as a Ligand Docking Engine: Ligand- and receptor-based docking with LiBELa
Desolvation Function Used in LiBELa: Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking
Electrostatic Models Used in LiBELa: Comparative Analysis of Electrostatic Models for Ligand Docking
Monte Carlo Simulations with LiBELa: Ligand binding free energy evaluation by Monte Carlo Recursion
Some Application of LiBELa for the Discovery of New Binders: The β-lactam ticarcillin is a Staphylococcus aureus UDP-N-acetylglucosamine 2-epimerase binder, Tetrazoles as PPARγ ligands: A structural and computational investigation.