Computational Chemistry

Rowan is a comprehensive skill for computational chemistry that provides cloud-based access to quantum chemistry workflows including pKa prediction, geometry optimization, conformer searching, protein-ligand docking, and AI-powered protein cofolding. It wraps the rowan-python and stjames libraries to enable molecular property calculations without requiring local computational resources.

Pymatgen is a comprehensive Python library for materials analysis that enables working with crystal structures, computing phase diagrams, analyzing electronic structure data, and accessing the Materials Project database. It supports 100+ file formats and integrates with major computational chemistry codes like VASP, Gaussian, and Quantum ESPRESSO.

DiffDock is a molecular docking skill for computational drug discovery. It helps predict how small molecule ligands bind to protein targets using diffusion-based deep learning, providing binding pose predictions and confidence scores for structure-based drug design workflows.