esm
Category: life-sciences · License: MIT · Version: 1.2
Tags: protein language models, protein design, structure prediction, protein embeddings
When to use it
Covers the EvolutionaryScale/Biohubesm Python SDK: ESM3 generative protein design (sequence, structure and function tracks, chain-of-thought), ESMC embeddings, inverse folding, ESMFold2 structure prediction, and hosted Forge/Biohub inference with ESM_API_KEY. Use when generating or completing proteins with ESM3, extracting ESMC embeddings for classification or similarity, folding a sequence or designing sequences from a structure, or choosing between esm3-open, esmc_300m and Forge-hosted models. Use when batching async Forge or Biohub API calls. Not for other protein models such as AlphaFold or generic Hugging Face transformers usage.
Example requests
Ask your agent in plain language, for example:- “How do I get per-residue embeddings for a protein sequence with ESMC locally?”
- “I have a 3,000-sequence file, kinases.fasta, and I’m trying to classify them as active/inactive with logistic regression. I tried esm.sdk.client(‘esmc-600m-2024-12’) in a loop and keep hitting rate-limit errors (429) after a few hundred calls. How should I restructure this so it finishes reliably?”
- “I have a crystal structure of a de novo binder backbone (binder.pdb) and I want new amino acid sequences that would fold into it. Is there a language-model route for that, and how would I check the designs afterward?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole life-sciences category with /plugin install life-sciences@research-agent-skills.