ESMFold2

ESMFold2

Biohub
ModelScope

ModelScope

Alibaba Cloud
+
+

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About

ESMFold2 is the successor to ESMFold, setting a new state of the art for single-sequence structure prediction and enabling the generation of new functional proteins through searching the ESMC model’s latent space. The model predicts high-resolution, all-atom 3D structures of biomolecular complexes directly from sequence, with optional multiple sequence alignment input for enhanced accuracy on challenging targets. It is designed for structure prediction using sequence and structure modalities, with ESM representations powering a series of looped folding layers and a diffusion model projecting pairwise representations to atomic-resolution predictions. ESMFold2 predicts protein structures directly from amino acid sequences and outputs comprehensive structural information, including all-atom coordinates for backbone and side chains, confidence metrics, and optional distogram predictions for detailed structural analysis.

About

This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported. This model is based on a multi-stage text-to-video generation diffusion model, which inputs a description text and returns a video that matches the text description. Only English input is supported. The text-to-video generation diffusion model consists of three sub-networks: text feature extraction, text feature-to-video latent space diffusion model, and video latent space to video visual space. The overall model parameters are about 1.7 billion. Support English input. The diffusion model adopts the Unet3D structure, and realizes the function of video generation through the iterative denoising process from the pure Gaussian noise video.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Structural biology researchers who need fast, high-resolution protein structure prediction from sequence for analysis, exploration, and experimental planning

Audience

Users interested in an open source text-to-video AI video generation model

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Biohub
Founded: 2016
United States
biohub.ai/models/esmfold2

Company Information

Alibaba Cloud
China
modelscope.cn/

Alternatives

Alternatives

Kaggle

Kaggle

Google
ESMC

ESMC

Biohub
Evo 2

Evo 2

Arc Institute
Evo Designer

Evo Designer

Arc Institute

Categories

Categories

Integrations

01.AI
Biohub
CodeQwen
GLM-4.5
Python
Qwen
Qwen-Image
Qwen2
Qwen2-VL
Qwen2.5
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen3
Qwen3.6
Qwen3.6-27B
Qwen3.6-35B-A3B
Qwen3.6-Max-Preview
Step 3.5 Flash
Yi-Large

Integrations

01.AI
Biohub
CodeQwen
GLM-4.5
Python
Qwen
Qwen-Image
Qwen2
Qwen2-VL
Qwen2.5
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen3
Qwen3.6
Qwen3.6-27B
Qwen3.6-35B-A3B
Qwen3.6-Max-Preview
Step 3.5 Flash
Yi-Large
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