PepMimic

Peptide binder design through binding interface mimicry with a latent diffusion model

Input

Reference protein complex

A protein complex containing the target protein bound to a known binder (e.g. an antibody, nanobody, or receptor). PepMimic mimics the binder side of this interface.

Target protein chain(s)

Reference binder chain(s)

60 credits

Output

Configure inputs to begin

Set options on the left, then click “Submit job” — or start from an example.

Source example (CD38 / SAR650984 Fab)

Quick screen (fewer candidates)

PepMimic

PepMimic designs short peptides that mimic the binding interface of a known protein binder (such as an antibody, nanobody, or natural receptor) on its target protein. A latent diffusion model co-designs each peptide's sequence and all-atom structure to reproduce the reference interface, enabling high-affinity target binding in a small peptide format.

The method is validated across multiple drug targets (PD-L1, CD38, HER2, BCMA, CD4, TROP2) in Kong et al., Nature Biomedical Engineering (2025).

When to use PepMimic

Use PepMimic when you already have at least one structure of your target bound to a binder (an antibody, nanobody, receptor, or any protein partner), and you want to convert that binding interface into a short therapeutic-style peptide.

If you only have an apo target structure, design a binder first (for example with RFdiffusion) and then run PepMimic on the resulting complex.

Inputs

Reference protein complex (PDB) — a structure containing both the target protein and a binder. You can upload a PDB or fetch an RCSB entry by ID.
Target protein chain(s) — the chain IDs in the reference that belong to the target PepMimic should bind. For a multi-chain target such as an antibody heavy + light chain receptor region, list all chains separated by commas (for example A,B).
Reference binder chain(s) — the chain IDs of the binder PepMimic will mimic. Separate multiple chains with commas (for example B,C for an antibody heavy + light chain).

Design parameters

Candidates per complex — how many peptide candidates to generate from the reference interface. The source example uses 20 for a quick tour; the authors recommend generating many more (tens of thousands) for final wet-lab candidate selection.
Minimum / Maximum peptide length — designed peptide length bounds, inclusive. PepMimic is trained on peptides of 25 residues or fewer, so the maximum is capped at 25.
Batch size (advanced) — the generation batch size. Lower this if the hosted GPU reports an out-of-memory error. Default 32.
OpenMM-relax top candidates (advanced) — how many of the top interface-mimicry candidates to energy-minimize with OpenMM (PDBFixer + CHARMM36) before returning. 0 returns unminimized generated complexes.

Outputs

Each generated candidate is returned as a complete protein–peptide complex PDB (the target receptor chains plus the designed peptide), together with:

Sequence — the designed peptide amino-acid sequence.
Length — designed peptide length in residues.
Interface hits — the number of residue pairs on the designed peptide that reproduce the reference binder's interface contacts, computed by PepMimic's interface-mimicry scorer (BLOSUM62 similarity with optimal Hungarian pairing). Higher is better.
Perplexity — the autoencoder's native likelihood proxy for the designed peptide. Lower indicates a more model-confident design.
results.jsonl — the source's native per-candidate record stream, preserving every field PepMimic emits (chain IDs, model metric, references).

Candidates are ranked by interface hits (descending), matching the source's native interface_hit.txt sort order.

How PepMimic runs

PepMimic runs through its documented generation entry point (mimic_design.py) and scores candidates with its documented interface-mimicry scorer (evaluation.runner.interface_hit). No scientific logic is reimplemented.

The source's full selection pipeline additionally runs Rosetta and FoldX interface free-energy scoring and a final top-K selection. Those steps require proprietary academic licenses (PyRosetta via Salilab, FoldX via the CRG license with manual yearly renewal) and are therefore not part of the hosted run. Use the returned interface-hit ranking and perplexity to narrow candidates, and run licensed scoring locally if needed for final synthesis decisions.

Source

Repository: PepMimic GitHub repository
Paper: Peptide design through binding interface mimicry with PepMimic, Kong et al., Nature Biomedical Engineering (2025) — DOI 10.1038/s41551-025-01507-4

If you use PepMimic results in published work, please cite the source paper.

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PepMimic

The method is validated across multiple drug targets (PD-L1, CD38, HER2, BCMA, CD4, TROP2) in Kong et al., Nature Biomedical Engineering (2025).

When to use PepMimic

If you only have an apo target structure, design a binder first (for example with RFdiffusion) and then run PepMimic on the resulting complex.