RoseTTAFold

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RoseTTAFold is a research & education tool that predicts accurate protein structures and interactions. It utilizes a 3-track deep learning network for computational biology applications.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is RoseTTAFold?

RoseTTAFold is a deep learning model and script package designed for the accurate prediction of protein structures and interactions. This tool is an official implementation of the RoseTTAFold architecture, which employs a 3-track neural network to achieve its predictions. It is primarily intended for research in computational biology, enabling scientists to model complex protein structures and protein-protein interactions (PPIs). The package includes scripts for installation, dependency management, and running predictions for both monomer structures and complex modeling. It also features a faster 2-track version for PPI screening, making it a versatile tool for advanced biological research.

Best used for

Ideal for computational biologists and researchers who need to accurately predict protein structures, model protein complexes, and screen protein-protein interactions. Especially valuable for academic and non-commercial research in structural biology and drug discovery.

Common actions

predict protein structures

model protein interactions

analyze biological data

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Capabilities

Key features

Predict protein structures
Model protein complexes
Screen protein interactions
3-track deep learning
PyRosetta integration

Target Audience

professorresearcher

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the licensing for RoseTTAFold?

The code for RoseTTAFold is licensed under the MIT License. However, the trained weights and data are made available for non-commercial use only under the terms of the Rosetta-DL Software license. Users should review the specific license details for appropriate usage.

What are the system requirements for RoseTTAFold?

RoseTTAFold requires a Linux environment and NVIDIA GPUs compatible with either CUDA 10.1 or CUDA 11, depending on the chosen conda environment. It also requires significant storage for sequence and structure databases, including UniRef30, BFD, and PDB100.

Can RoseTTAFold be used for protein-protein interaction screening?

Yes, RoseTTAFold includes a faster 2-track version specifically designed for protein-protein interaction (PPI) screening. This version can be used with paired MSA files to predict complex structures and identify potential interactions, with examples provided in the repository.

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This tool also appears in

Wellness & Lifestyle › Pharma & Biotech

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