{
  "abstract": "Intrinsically disordered proteins, topologically complex protein surfaces, and biomolecular condensates regulate essential cellular processes but remain difficult to drug with conventional small molecules. Here, we present PepSpace, a physics-driven directed-evolution platform coupling residue-resolution coarse-grained molecular dynamics with a multi-objective genetic algorithm. PepSpace designs peptide binders by rewarding target engagement while penalizing peptide self-association and off-target binding. Evaluated alongside deep-learning generative models across multiple targets, PepSpace-designed peptides achieve predicted interaction strengths up to two orders of magnitude greater than machine-learning designs, while reproducing experimentally observed binding hierarchies and revealing distinct binding modes. For PIEZO1, PepSpace designs 25-mer peptides that preferentially engage a defined 30-residue intracellular beam epitope while suppressing interactions with the remainder 2,547-residues of the protein. For CHERP biomolecular condensates, dual-action peptides weaken native intermolecular contacts and destabilize the condensed phase. PepSpace provides a physically grounded framework for de novo peptide design against dynamic protein targets and biomolecular condensates, with explicit control over specificity, solubility, and collective interactions.",
  "abstract_shown": true,
  "affiliations": [
    "University of Cambridge"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "name": "J. Oller Iscar"
    },
    {
      "name": "A. R. Tejedor"
    },
    {
      "name": "A. Feito"
    },
    {
      "name": "M. Velasco-Estevez"
    },
    {
      "name": "A. Ocana"
    },
    {
      "name": "R. Collepardo-Guevara"
    },
    {
      "affs": [
        0
      ],
      "name": "J. Rene Espinosa"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/40ffxpznqz45r.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.18.752684",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752684v1.full",
  "id": "40ffxpznqz45r",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752684v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "biophysics"
    ],
    [
      "openalex",
      "1312|Protein Structure and Dynamics"
    ]
  ],
  "openalex": "W7214159631",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752684v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/40ffxpznqz45r.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:20Z",
      "native_id": "10.64898/2026.09.18.752684",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752684v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "biorxiv:biophysics",
      "subfield": "biophysics"
    }
  ],
  "title": "PepSpace: An Automated, Physics-Driven Directed Evolution Platform for the De Novo Design of Specific Peptide Binders and Condensate Modulators",
  "title_text": "PepSpace: An Automated, Physics-Driven Directed Evolution Platform for the De Novo Design of Specific Peptide Binders and Condensate Modulators",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:20Z",
  "url": "https://research.draconitic.com/paper/40ffxpznqz45r",
  "venue": "bioRxiv",
  "versions": []
}