rowan

Overview

Rowan is a cloud quantum chemistry platform that exposes DFT and semiempirical calculations through a Python SDK (rowan). Submit calculations (geometry optimization, conformer generation, torsional scans, single-point energies) from Python scripts or Jupyter notebooks, and retrieve results — energies, geometries, partial charges, frontier orbital energies — without managing Gaussian, ORCA, or Psi4 installations. Rowan handles job queuing, execution, and storage. A free tier is available for academic and exploratory use.

When to Use

• Geometry optimization of small molecules: Getting accurate equilibrium geometries for drug candidates, fragments, or building blocks using DFT.
• Conformer generation with energy ranking: Generating and optimizing multiple conformers to identify the lowest-energy conformation for docking or property prediction.
• Torsional potential scans: Mapping the energy profile along a rotatable bond to understand conformational preferences.
• Quantum mechanical property calculation: Computing dipole moments, partial charges (Mulliken, ESP), HOMO/LUMO energies, and electrostatic potential surfaces.
• Energy minimization before docking: Refining ligand geometries before input to structure-based docking tools (DiffDock, AutoDock Vina).
• Comparing isomer stability: Calculating relative energies of tautomers, stereoisomers, or constitutional isomers.
• For large-scale conformer screening (>1000 molecules), use RDKit's ETKDGv3 + MMFF (force field level, no cloud cost).
• For protein-scale quantum mechanics/molecular mechanics (QM/MM), specialized packages like ORCA + CP2K are needed.

Prerequisites