A molecular design and simulation platform for scientists

Rowan is a modern computational platform that provides a suite of design and simulation tools for chemical R&D. We help scientists in drug discovery and material science accelerate their research and find better molecules faster.

What scientists are saying

Arda Göreci · Founder & CTO, Ligo Biosciences
Enzyme design
Rowan's tools for modeling and predicting chemical reactivity have significantly accelerated our computational pipeline and have been a big asset to our team.

Trusted by

6,000+

scientists

Over

1.4 million

calculations run

Property prediction at the boundary of physics and ML

The microstate population by pH of Xeljanz, an autoimmune-disease-targeting prescription medication
A painting of a starling

Macroscopic pKa

Predict macroscopic pKa values, microstate populations, isoelectric points, and logD values with Rowan's macroscopic pKa workflow. This is made possible by Starling, a physics-informed machine learning model that runs in minutes. Read the preprint.

Quick conformer searching

Quickly explore conformational space using fast low-level methods for conformer generation and more accurate final methods for conformer ranking.

Regioselectivity and reactivity

Predict where a molecule will react with nucleophiles, electrophiles, and radicals and quantify an electrophile's ability to promote covalent reactions with Fukui index and global electrophilicity index calculations.

Blood–brain-barrier permeability

Predict the likelihood of blood–brain-barrier penetrance in silico by computing the free energy of neutralization and energy of solvation.

More property predictions

Predict bond-dissociation energies (BDE), solid organic solubility, hydrogen-bond-acceptor strength, redox potentials, and more. Read more about our platform.

Molecular simulation millions of times faster

The structure of lovenox, an anticoagulant medication, optimized with the Egret-1 neural network potential
A painting of an egret

Egret-1

Egret-1 is a family of open-source neural network potentials that match or exceed the accuracy of quantum-mechanics-based simulations while running orders-of-magnitude faster. With Egret-1, scientists can quickly get trustworthy results from computation to guide their work. Read the preprint.

AIMNet2

AIMNet2 is a generally applicable, accurate, and incredibly fast neural network potential that powers organic-focused computational chemistry simulations in Rowan.

OMol25 eSEN

OMol25's eSEN Conserving Small from Meta FAIR is a model trained on Open Molecules 2025, a high-quality dataset of unprecedented scale spanning small molecules, biomolecules, metal complexes, and electrolytes, including 83 elements, charged systems, and open-shell species.

Orb-v3

Orb-v3 from Orbital Materials can scale to simulations of 100,000 atoms while performing an energy and force evaluation in under 1 second.

Traditional physics-based methods

Run density-functional theory (DFT) and xTB methods with a unified interface, deployment environment, and database for calculation submission, management, and analysis.

Deep learning and physics for protein–ligand complex modeling

Compounds redocked into a protein with Rowan's strain-corrected docking worfklow

Strain-corrected docking with Vina

Test binding, generate bound poses, and search through chemical libraries with ligand-strain-corrected docking powered by AutoDock Vina.

The barnase–barnstar complex predicted from protein sequences by Boltz-2

Co-folding with Boltz-2 and Chai-1r

Predict the 3D structures and binding affinities of protein–ligand complexes from sequence information with state-of-the-art models Boltz-2, Chai-1r, and Boltz-1.

Secure infrastructure

We offer single-tenant and customer-managed virtual-private-cloud (VPC) deployments for enterprise accounts. Read more about our security and deployment options.

Python and RDKit APIs

Run calculations and workflows programmatically with a Python- or RDKit-native API that returns structured data, perfect for high-throughput screening or complex workflows. Read more about our API.

Web-native platform

Our no-code web-based platform makes it easy to submit, view, and analyze complex calculations. All workflows automatically generate publication-quality visuals, and Rowan makes it easy to securely share and collaborate within organizations.

How would computation change your R&D?

Gilles Ouvry · VP of Chemistry, NRG Therapeutics
Neurotherapeutics
The game-changer for me this past year has been Rowan Scientific's platform which allows easy and quick access to hydrogen-bond basicity predictions. Read more.

Our blog

Structure-Based Drug Design Updates

Structure-Based Drug Design Updates

enforcing stereochemistry; refining co-folding poses; running PoseBusters everywhere; computing strain for co-folding; PDB sequence input; 3D visualization of 2D scans
Oct 14, 2025 · Ari Wagen and Corin Wagen
Using Implicit Solvent With Neural Network Potentials

Using Implicit Solvent With Neural Network Potentials

Modeling polar two-electron reactivity accurately with neural network potentials trained on gas-phase DFT.
Oct 7, 2025 · Corin Wagen
Preparing SMILES for Downstream Applications

Preparing SMILES for Downstream Applications

How to quickly use Rowan to predict the correct protomer and tautomer for a given SMILES.
Oct 3, 2025 · Corin Wagen
Better Search and Filtering

Better Search and Filtering

the problem of too many calculations; new ways to search, filter, and sort; how to access these tools; future directions
Sep 30, 2025 · Ari Wagen and Spencer Schneider
Boltz-2 Constraints, Implicit Solvent for NNPs, and More

Boltz-2 Constraints, Implicit Solvent for NNPs, and More

new terms of service; comparing IRCs and conformer searches; contact and pocket constraints for Boltz-2; MOL2 download; implicit-solvent NNPs; draft workflows; optimizing docking efficiency
Sep 22, 2025 · Corin Wagen, Ari Wagen, Jonathon Vandezande, Eli Mann, and Spencer Schneider
Controlling the Speed of Rowan's Docking

Controlling the Speed of Rowan's Docking

Some notes on how docking can be tuned for different applications.
Sep 22, 2025 · Corin Wagen
Studying Scaling in Electron-Affinity Predictions

Studying Scaling in Electron-Affinity Predictions

Testing low-cost computational methods to see if they get the expected scaling effects right.
Sep 10, 2025 · Corin Wagen
Open-Source Projects We Wish Existed

Open-Source Projects We Wish Existed

The lacunæ we've identified in computational chemistry and suggestions for future work.
Sep 9, 2025 · Corin Wagen, Jonathon Vandezande, Ari Wagen, and Eli Mann
How to Make a Great Open-Source Scientific Project

How to Make a Great Open-Source Scientific Project

Guidelines for building great open-source scientific-software projects.
Sep 9, 2025 · Jonathon Vandezande
ML Models for Aqueous Solubility, NNP-Predicted Redox Potentials, and More

ML Models for Aqueous Solubility, NNP-Predicted Redox Potentials, and More

the promise & peril of solubility prediction; our approach and models; pH-dependent solubility; testing NNPs for redox potentials; benchmarking opt. methods + NNPs; an FSM case study; intern farewell
Sep 5, 2025 · Eli Mann, Corin Wagen, and Ari Wagen

Partners & friends

ReSync Bio (acquired by Benchling)
Accelerating drug discovery with AI
Rowan partnered with ReSync to add powerful simulation tooling to the ReSync platform, which gave scientists no-code access to advanced AI tools. ReSync was acquired by Benchling in August 2025. Read more.
Banner background image

Get started today

Create an account to get started today or contact us to find a solution for your business.