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Explore five spotlight prompts and use your AI agent to find uncharacterized protein candidates, explore molecular interactions, map mutation constraints, or interpret protein features. See the Quickstart to connect your AI agent. Interactive structures appear in clients that support the structure viewer.
Folding and ESMC prompts are billed to your Biohub account. Results and scores can vary between runs or when the Atlas is updated. Treat all results as hypotheses, not as established biological facts.
Each spotlight video includes a 30-second edited chat replay using Biohub MCP results and structure images, with processing time compressed.

Find uncharacterized protein candidates

Use the ESM Atlas: Start from a protein you study and shortlist candidates using learned protein features, annotations, and structures.

I want to identify new protein candidates worth investigating. Starting from Csm3 from Streptococcus thermophilus (UniProt A0A0A7HIF0), search ESM Atlas for uncharacterized relatives and show the most promising candidates.

What this shows: ESM Atlas searches cluster representatives using SAE feature similarity. The agent compares candidates from clusters without characterized Pfam annotations using their lengths, shared features, and predicted structures. The 222-residue lead is close to Csm3’s length; the highest-scoring hit is only 69 residues. These observations support follow-up, without establishing completeness or function.

Explore a GLP-1 peptide and GLP-1R complex

Use ESMFold2: Predict a defined receptor and unmodified peptide to examine their possible interaction.

Model how unmodified human GLP-1(7–37) engages human GLP-1R, then show me the predicted complex.

What this shows: ESMFold2 Fast predicts a complex of full-length human GLP-1R (UniProt P43220, 463 residues) and unmodified GLP-1(7–37), the 31-residue peptide from proglucagon positions 98–128 (UniProt P01275). No lipid linker, membrane, or G protein is included. Inspecting the pose and confidence estimates provides a structural hypothesis; confidence scores do not measure binding affinity or receptor activation.

Map PETase mutation constraints

Use ESMC: Explore which positions appear constrained or tolerant in a protein’s possible mutations.

Map the mutational landscape of this CaPETase sequence and show me where it is most constrained or tolerant. AADNPYQRGPDPTNASIEAATGPFAVGTQPIVGASGFGGGQIYYPTDTSQTYGAVVIVPGFISVWAQLNWLGPRLASQGFVVIGIETSVITDLPDPRGDQALAALDWATTRSPVASRIDRTRLAAAGWSMGGGGLRRAALQRPSLKAIVGMAPWNGERNWSAVTVPTLFFGGSSDAVASPNDHAKPFYNSITRAEKDYIELRNADHFFPTSANTTMAKYFISWLKRWVDNDTRYTQFLCPGPSTGLFAPVSASMNTCPF

What this shows: ESMC 6B scans all 259 positions in the supplied CaPETase sequence, masking each position in turn to score substitutions. The agent maps constrained and higher-entropy positions onto the structure. These scores describe model preferences, not measured enzyme activity or stability; higher entropy alone does not imply favorable substitutions.

Interpret ATP synthase features

Use ESMC and SAEs. Explore what the model recognizes in a familiar protein and where selected features activate on its structure.

Show me what ESMC has learned about ATP synthase and map the strongest features onto its structure.

What this shows: The agent retrieves ESMC SAE feature summaries for the ATP synthase F1 alpha subunit and highlights one reported residue-region peak for each of three strong features. Their descriptions suggest nucleotide-associated and coupling patterns. Broad feature labels do not establish catalytic activity in this alpha subunit or functional roles for individual highlighted residues.

What the agent does

  1. Identify the protein. This example uses the 492-residue bovine mitochondrial ATP synthase F1 alpha subunit sequence from PDB 2XND, chain A. The PDB record supplies the sequence; the viewer uses a predicted structure for that sequence.
  2. Retrieve its features. Ask ESM Atlas for the sequence’s ESMC SAE feature summaries, then retrieve descriptions of the strongest reported features. The MCP can compute a missing feature profile; an existing profile can be retrieved directly.
  3. Map the result. Open the Biohub structure viewer for the same sequence and highlight reported feature-region peaks, checking that sequence positions match the displayed residues. This demo marks A425, S317, and L267 for the three strongest features, using positions in the analyzed sequence.

What is happening under the hood

ESMC builds a representation of the protein from its amino acid sequence. A sparse autoencoder, or SAE, separates that representation into features that can be examined individually. Some features are associated with patterns such as structural motifs or nucleotide-binding regions.This workflow uses feature summaries returned by the MCP. Each highlighted residue marks a reported feature-region peak. Its location and feature description provide clues about what the model recognizes. These are starting points for investigation and should be treated as hypotheses only.Displaying a structure does not necessarily mean running ESMFold2: the agent may retrieve an existing prediction. The feature analysis and the source of the displayed structure are separate steps.

Explore the result

Compare where the features activate and ask what evidence supports their interpretations.

For the strongest SAE feature, highlight its reported residue-region peaks. What structural regions do they occupy, and what supports the feature's interpretation?

Go deeper

Reconstruct a protein function hypothesis

Use ESMC and the ESM Atlas: Revisit a characterized protein as a retrospective example, treating its sequence as uncharacterized to develop a function hypothesis.

Treat this protein sequence from an Icelandic hot spring metagenome as uncharacterized. Use ESMC SAE features and similar proteins in ESM Atlas to propose its most likely function. Show the strongest supporting evidence and highlight the relevant residues on its structure. MSYNKVVLVGRLTRDPETRQTLDGNLITTFTLAVNRGNNGDDVDFIRIVAFRKLAELAHNYLQKGRMVLVDGKLRINKWKTNDGQPRSTVEIWADNIVFVDSKKGDREIPDEIPYEEVFGQDVETDEDIPNDDEPPFRSHHHHHH

What this shows: SSB-associated SAE features and annotated Atlas neighbors support a single-stranded DNA-binding hypothesis. The agent maps reported feature-region peaks onto a predicted structure of the exact 145-residue tagged construct. This retrospective demo reconstructs a hypothesis for a protein with published experimental characterization; the highlighted residues are model-associated peaks, not measured DNA contacts.