{
  "abstract": "Cyclic-peptide discovery requires molecular topology, atomic structure, receptor-associated evidence and computational decisions to remain consistent across a multistage workflow. We present CP-GFM-SGX, an all-atom generative AI model for cyclic-peptide design that integrates a topology-aware generative core with a Unified Evidence State Machine (UESM) to track candidate identity, chemical validity, provenance, typed failures and bounded computation. We evaluated three distinct aspects of the system. In Track A, a frozen five-complex known-ligand benchmark with 100 scheduled poses per complex, the native-free FULL route selected a ligand-backbone pose with root-mean-square deviation (RMSD) below 2 Å in four of five systems; retrospective best-of-100 evaluation found a sub-2-Å pose in all five (median selected RMSD, 1.72 Å). In Track B, matched true-pocket versus shuffled-pocket comparisons favored the specified pocket in all seven main targets (median of target medians, +172.6 Rosetta energy units; weakest margin, +3.9 for MCL-1–9CDT). An exploratory post-protocol assessor admitted 42/42, 42/42 and 40/42 selected top-K slots in the full, condition-masked and post hoc head-to-tail arms, respectively. In Track C, FULL UESM produced the specified protective outcomes for six deterministic synthetic fault fixtures and one additional missing-evidence case; targeted ablations isolated the roles of provenance and failure propagation. In a separate KRAS G12D–GDP experimental-feedback series, synthesis and SPR/BLI testing of cyclic-peptide analogues guided position-2 basic-side-chain selection and dual-basic-group placement, advancing the reported SPR affinity from approximately 60 µM for CRO-748 to approximately 6 µM for 748-R1 and approximately 1 µM for 748-RK. Comparisons using the 31-dimension Structured Capability and Evidence Grid (SCEG-31D) demonstrate that CP-GFM-SGX exhibits certain superiority over other design platforms in multiple aspects. Together, we evaluate a topology-aware generative artificial intelligence workflow for receptor-focused cyclic-peptide design and show, in a KRAS feedback series, how binding measurements guide iterative chemical optimization.",
  "abstract_shown": true,
  "affiliations": [
    "Yizhuang Economic and Technological Development Zone",
    "Beijing Yuli Technology Co.,",
    "University of Oxford"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Zhiyuan Hu",
      "orcid": "0009-0000-9058-1053"
    },
    {
      "affs": [
        2
      ],
      "name": "Russell Dillworth"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/82eqan7zn3gyd.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010253/v1",
  "fulltext_url": null,
  "id": "82eqan7zn3gyd",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010253/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Chemical Synthesis and Analysis"
    ]
  ],
  "openalex": "W7221548523",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010253/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-12",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/82eqan7zn3gyd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15010253",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010253/v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Chemical Synthesis and Analysis",
      "subfield": "molecular-biology"
    }
  ],
  "title": "CP-GFM-SGX: Topology-Aware Cyclic Peptide Generation and Design with Receptor-Conditioned Structural Evaluation and Experimental KRAS Affinity Optimization",
  "title_text": "CP-GFM-SGX: Topology-Aware Cyclic Peptide Generation and Design with Receptor-Conditioned Structural Evaluation and Experimental KRAS Affinity Optimization",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/82eqan7zn3gyd",
  "venue": "ChemRxiv",
  "versions": []
}