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Rowan

Rowan Scientific Corporation v1.0.1

Chemistry & Biology Simulation

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Not specified in the available declarations: capabilities, limitations, pricing & account requirements.

Onboarding example

Propose an analogue of daraxonrasib with a predicted logP ≤ 3 and aqueous solubility ≥ 10 µM.
Sources & dates

Developer declarations; not independently tested. Listing last checked Nov 13, 2026. Package observed Nov 12, 2026.

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Description

From the marketplace listing

Use Rowan in ChatGPT to run and manage computational chemistry and structural biology workflows. Predict molecular properties, search conformers and reaction paths, and calculate energies, structures, spectra, and electronic properties with quantum chemistry. Prepare proteins and run structure prediction, docking, molecular dynamics, and binding affinity workflows. Calculations are saved to Rowan and available in the web app, while existing Rowan work can be viewed and managed from ChatGPT. Track jobs, inspect results, and download supported files.

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Publisher description

Use Rowan in ChatGPT to run and manage computational chemistry and structural biology workflows. Predict molecular properties, search conformers and reaction paths, and calculate energies, structures, spectra, and electronic properties with quantum chemistry. Prepare proteins and run structure prediction, docking, molecular dynamics, and binding affinity workflows. Calculations are saved to Rowan and available in the web app, while existing Rowan work can be viewed and managed from ChatGPT. Track jobs, inspect results, and download supported files.

Package name

app-6a88631af75081918917d89fb00269ad

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Skill instructions
computational-chemistry-and-biology13 KB

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---
name: computational-chemistry-and-biology
description: Run computational chemistry and structural biology calculations on the Rowan platform through Rowan MCP tools or the `rowan` Python package. Use when the user wants to run Rowan workflows, or mentions Rowan, computational chemistry, structural biology, or molecular or protein simulation.
---

# Computational Chemistry and Biology with Rowan

Run simulations on the [Rowan](https://rowansci.com) platform through Rowan MCP tools or the `rowan` Python package. This skill provides shared scientific strategy and workflow guidance for both interfaces.

**Interfaces are for syntax; skill is for strategy.** Use this skill and its workflow references to choose scientifically appropriate methods and settings. Trust `discover_workflow` or the installed package when an exact parameter differs from a reference.

## Choose an interface

Both interfaces are first-class. Use the shared scientific guidance and workflow references below with either one.

- **MCP-connected chat:** when Rowan tools are available, read [MCP execution](reference/mcp_execution.md) before calling them. Do not install Python or request an API key; authentication belongs to the MCP connection. Use `discover_workflow` as the exact parameter contract.
- **Python code, scripts, or notebooks:** when the user requests Python or no Rowan MCP tools are available, read [Python SDK](reference/python_sdk.md) before writing or running code. Trust the installed package when its exact API differs from an example.

For project or folder management, also read [folders and projects](reference/folders_and_projects.md). For callbacks, read [webhooks](reference/webhooks.md).

## Molecule inputs

Structure-based workflows take a `rowan.Molecule`, not a bare SMILES string. Build one from a SMILES with `rowan.Molecule.from_smiles(...)` (RDKit embeds a 3D structure) or from coordinates with `rowan.Molecule.from_xyz(...)` / `from_xyz_file(...)`. A plain SMILES string is accepted only by the SMILES-based (2D) workflows. Each reference file states which case its workflow is:

- **SMILES (2D)**: predicts from the graph, ignores 3D, so a plain SMILES string works (ADMET, solubility, logP, macropKa, the SMILES pKa/permeability methods).
- **3D from a SMILES is fine**: pass `rowan.Molecule.from_smiles(...)`; the embedded structure is built and optimized as needed (basic calculation, NMR, descriptors, redox, BDE, conformer search, and most QM workflows).
- **Real coordinates needed**: pass a structure with meaningful geometry via `rowan.Molecule.from_xyz(...)`, a prior result's `.molecule`, or a docked/crystal pose (electronic properties, interaction-energy decomposition, strain, IRC, double-ended TS, 3D pKa methods).

For higher rigor, start a 3D workflow from the conformer search workflow's lowest-energy conformer.

## Protein inputs

Prepare proteins before docking, MD, or FEP. Use the full protein preparation workflow for comprehensive structure repair and `protein.prepare()` for the faster in-place PDBFixer/OpenMM path. Protein workflows accept either a `rowan.Protein` or `rowan.ProteinUUID`. See [protein preparation](reference/protein_preparation.md) for details.

### Protein–ligand structure boundary

MCP cannot extract a bound non-polymer ligand from a holo PDB as a reusable molecule. For ligand-based workflows, require a separate ligand input (for example SDF, MOL, MOL2, or SMILES); do not infer it from `HETATM` records. Holo proteins remain usable for preparation and workflows that explicitly accept a ligand residue.

## Workflows

Pick the workflow matching the task by reading the descriptions, then open its reference file (linked at the end of each entry) for recommended settings and an example. Python's universal submit arguments live in [Python SDK](reference/python_sdk.md) and aren't repeated per workflow; MCP parameters come from `discover_workflow`.

The list below provides scientific guidance, not an executable registry. MCP

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Referenced files: 45 — file references are metadata, not package contents.

Package details

Publisher declarations from the archived package. These are separate from our research and the live service's terms.

Package author
Rowan Scientific Corporation

Package observed Nov 12, 2026.

Technical details
First seen
Sep 30, 2026 · 22:02 UTC
Last seen
Nov 13, 2026 · 00:00 UTC
Collection status
Collected

plugin_asdk_app_6a88631af75081918917d89fb00269ad

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