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rowan

Run molecular modeling and drug design workflows through the Rowan cloud API.

2|Updated Jun 4, 2026
Search Tags:#drug discovery#molecular docking#cloud computing#cheminformatics#chemistry
One-click install
npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill rowan-lord1egypt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rowan
Source: https://github.com/Lord1Egypt/scientific-agent-toolkit/tree/main/scientific-skills/rowan
Command: npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill rowan-lord1egypt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rowan-python.

What problem does it solve?

Rowan eliminates the need for maintaining local HPC or GPU infrastructure by providing a unified, cloud-native Python API for complex medicinal chemistry and molecular modeling workflows.

Core Features & Use Cases

  • Molecular Modeling: Perform quantum chemistry, conformer ensemble generation, and tautomer searches at scale.
  • Drug Discovery Pipelines: Execute multi-step workflows including docking, protein-ligand cofolding, and ADMET property prediction.
  • Use Case: A researcher can programmatically screen a library of 100+ compounds against a protein target, managing the entire docking and pose refinement process through a single Python script without managing local compute resources.

Quick Start

Use the rowan skill to submit a descriptors workflow for the SMILES string CC(=O)Oc1ccccc1C(=O)O to calculate molecular properties.

Frequently Asked Questions about rowan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run molecular docking and ADMET prediction without local GPU or HPC infrastructure?▼

You can use a cloud-native molecular modeling API to run protein-ligand docking and ADMET prediction, offloading scalable compute infrastructure to the cloud instead of maintaining local HPC or GPU hardware.

What is cloud-native drug discovery and how does it handle batch property prediction?▼

Cloud-native drug discovery uses a Python API to execute multi-step medicinal chemistry workflows. It processes batch property prediction by submitting molecular inputs like SMILES strings to scalable compute infrastructure.

How do I submit a SMILES string for cheminformatics property calculation?▼

You submit a SMILES string like CC(=O)Oc1ccccc1C(=O)O through the Python interface to initiate a descriptors workflow, calculating molecular properties using the platform's scalable compute infrastructure.

Do I need an API key and the rowan-python library to perform protein-ligand cofolding?▼

Yes, an active API key and the rowan-python library are required to interface with the platform's scalable compute infrastructure for AI-driven structure prediction and protein-ligand cofolding tasks.

Can I screen a library of 100+ compounds against a protein target programmatically?▼

Yes, you can programmatically screen 100+ compounds against a protein target, managing the entire docking and pose refinement process through a single Python script without managing local compute resources.

Does this approach support quantum chemistry and conformer ensemble generation at scale?▼

Yes, the platform supports molecular modeling at scale, executing quantum chemistry calculations, conformer ensemble generation, and tautomer searches entirely through its cloud-native Python interface.

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