Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-liga…
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name: rowan
description: Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
license: Proprietary (API key required)
compatibility: Python 3.12+, API key required
required_environment_variables: [{"name": "ROWAN_API_KEY", "prompt": "Rowan computational chemistry API key.", "required_for": "full functionality"}]
metadata: {"version": "1.2", "skill-author": "Rowan Science", "trigger-keywords": "pKa prediction, molecular docking, conformer search, chemistry workflow, drug discovery, SMILES, protein structure, batch molecular modeling, cloud chemistry", "openclaw": {"primaryEnv": "ROWAN_API_KEY", "envVars": [{"name": "ROWAN_API_KEY", "required": true, "description": "Rowan computational chemistry API key."}]}}
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# Rowan: Cloud-Native Molecular-Modeling and Drug-Design Workflows
## Overview
Rowan is a cloud-native workflow platform for molecular simulation, medicinal chemistry, and structure-based design. Its Python API exposes a unified interface for small-molecule modeling, property prediction, docking, molecular dynamics, and AI structure workflows.
Use Rowan when you want to run medicinal-chemistry or molecular-design workflows programmatically without maintaining local HPC infrastructure, GPU provisioning, or a collection of separate modeling tools. Rowan handles all infrastructure, result management, and computation scaling.
## When to use Rowan
**Rowan is a good fit for:**
- Quantum chemistry, semiempirical methods, or neural network potentials
- Batch property prediction (pKa, descriptors, permeability, solubility)
- Conformer and tautomer ensemble generation
- Docking workflows (single-ligand, analogue series, pose refinement)… load the full skill through Skill Me