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

A Conversation With Navvye Anand (Bindwell)

A Conversation With Navvye Anand (Bindwell)

Corin interviews Navvye about pesticide discovery, the advantages that ML gives them, and what areas of research he's most excited about.
Nov 18, 2025 · Corin Wagen
Ion Mobility, Batch Docking, Strain, Flow-Matching Conformer Generation, and MSA

Ion Mobility, Batch Docking, Strain, Flow-Matching Conformer Generation, and MSA

a diverse litany of new features: ion-mobility mass spectrometry; high-throughput docking with QVina; a standalone strain workflow; Lyrebird, a new conformer-generation model; and standalone MSAs
Nov 5, 2025 · Corin Wagen, Ari Wagen, Eli Mann, and Spencer Schneider
Using Securely Generated MSAs to Run Boltz-2 and Chai-1

Using Securely Generated MSAs to Run Boltz-2 and Chai-1

Example scripts showing how Boltz-2 and Chai-1 can be run using MSA data from Rowan's MSA workflow.
Nov 5, 2025 · Spencer Schneider and Ari Wagen
Lyrebird: Molecular Conformer Ensemble Generation

Lyrebird: Molecular Conformer Ensemble Generation

Rowan's new flow-matching conformer-generation model, with benchmarks.
Nov 5, 2025 · Eli Mann
Predicting Ion-Mobility Mass Spectra Through Rowan

Predicting Ion-Mobility Mass Spectra Through Rowan

An introduction to the field, how Rowan's approach works, and where it might be useful.
Nov 5, 2025 · Corin Wagen
BREAKING: BoltzGen Now Live on Rowan

BREAKING: BoltzGen Now Live on Rowan

a new foray into generative protein-binder design; what makes BoltzGen different; experimental validation; democratizing tools; running BoltzGen on Rowan
Oct 27, 2025 · Corin Wagen, Ari Wagen, and Spencer Schneider
The "Charlotte's Web" of Density-Functional Theory

The "Charlotte's Web" of Density-Functional Theory

A layman's guide to cutting your way through the web of DFT functionals, explaining GGAs, mGGAs, hybrids, range-separated hybrids, double hybrids, and dispersion corrections.
Oct 27, 2025 · Jonathon Vandezande
How to Design Protein Binders with BoltzGen

How to Design Protein Binders with BoltzGen

Step-by-step guides on how to run the BoltzGen model locally and through Rowan's computational-chemistry platform.
Oct 27, 2025 · Corin Wagen and Ari Wagen
Pose-Analysis Molecular Dynamics and Non-Aqueous pKa

Pose-Analysis Molecular Dynamics and Non-Aqueous pKa

what to do after docking/co-folding; Rowan's approach to short MD simulations; what's next for SBDD and MD; new ML microscopic pKa models
Oct 23, 2025 · Corin Wagen, Ari Wagen, Eli Mann, and Spencer Schneider
How to Predict pKa

How to Predict pKa

Five different theoretical approaches for acidity modeling and when you should use each one.
Oct 16, 2025 · Corin 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.
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