Audience
Protein science researchers who need transformer-based sequence representations for structure prediction, function annotation, mutation analysis, and protein design
About ESMC
ESMC is the latest in the ESM family of protein language models, establishing a new frontier in representation learning for protein biology. Trained on billions of evolutionary sequences, it learns representations that reflect a mechanistic reduction of protein structure and function. The model is built on a transformer architecture, supports sequences as its core modality, and is trained on up to 6 billion proteins. ESMC is designed for protein science research, including structure prediction, function annotation, protein design, and understanding evolutionary relationships between proteins. It can generate novel proteins from partial sequence, structure, or functional constraints, helping researchers explore new possibilities in protein design and biological discovery. The Biohub Platform provides access to ESMC through the API and the ESM Python package, with quickstart resources for installing the package, creating an API key, connecting to the platform.
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Biohub
Biohub is an open platform for building on the world model of protein biology. It provides access to the ESM family of models, including ESMC, ESMFold2, and ESM3, along with interactive tools and developer resources for protein science research. ESMC is a state-of-the-art protein language model trained on billions of evolutionary sequences, building representations that capture fundamental mechanisms of protein structure and function. It powers functional analysis, structure prediction, protein design, and the exploration of evolutionary relationships between proteins. ESMFold2 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. ESM3 jointly models sequence, structure, and function, enabling controllable generation of novel proteins by conditioning on any combination of these modalities.
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Evo 2
Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.
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ESMFold2
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.
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Claude Mythos 5.1
Claude Mythos 5.1 is Anthropic’s newest Mythos-class model, designed for advanced cybersecurity, biology, scientific research, coding, and long-running knowledge work. It is the same underlying model as Claude Fable 5.1 but uses different safeguards: Fable 5.1 is generally available, while Mythos 5.1 is restricted to trusted access programs with safeguards specifically designed for cybersecurity and life sciences research. The model sets a new performance frontier for agentic coding and demonstrates the strongest cyber capabilities of any Anthropic model released to date. In scientific research, Mythos 5.1 can work with specialized tools and complex workflows across molecular design, computational biology, and other technical domains. In Anthropic’s experiments, it designed high-affinity protein binders across multiple targets and achieved its strongest measured hit rate to date. It also optimized seven open-source protein and genomics deep learning models.
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Pricing
Starting Price:
Free
Free Version:
Free Version available.
Company Information
Biohub
Founded: 2016
United States
biohub.ai/models/esmc
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Product Details
Platforms Supported
Cloud
Training
Documentation
Support
Online
ESMC Frequently Asked Questions
Q: What kinds of users and organization types does ESMC work with?
ESMC works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does ESMC support in their product?
ESMC supports these languages: English.
Q: What kind of support options does ESMC offer?
ESMC offers support via online.
Q: What other applications or services does ESMC integrate with?
ESMC integrates with: Biohub and Python.
Q: Does ESMC have an API?
Yes, ESMC has an API.
Q: What type of training does ESMC provide?
ESMC provides training in the form of documentation.
Q: How much does ESMC cost?
Pricing for ESMC starts at Free.
