Biohub/esm

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2927 stars · 381 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library and model release providing ESMC protein language models, ESMFold2 structure prediction, and the ESM Atlas of 6.8 billion proteins. It enables protein representation, structure prediction, and de novo protein/binder design from sequences.

Use cases

• predict protein 3D structure from a single amino acid sequence
• generate protein sequence embeddings for downstream ML tasks
• design de novo minibinders or antibody-derived scFvs against a target
• predict protein-protein and antibody-antigen complex structures
• explore interpretable features of protein biology via sparse autoencoders
• run fast single-sequence protein folding

When to choose

• you need state-of-the-art protein structure prediction or folding throughput
• you want embeddings from a frontier protein language model
• you are doing computational protein design or binder discovery

When to avoid

• you need a lightweight model for CPU-only or low-resource environments
• your task is unrelated to protein sequences or structures
• you require a permissive open-source license (license is non-standard)

Facets

library · maturity active

machine-learning deep-learning llm-inference bioinformatics machine-learning deep-learning python protein-language-model protein-structure-prediction protein-design esm computational-biology binder-design sparse-autoencoders natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Biohub/esm")