{
  "abstract": "In this paper, we introduce an iterative refinement procedure that substitutes individual amino acid residues in a predicted protein sequence to minimize structural error; substitutions are guided by a weighted composite score of global evaluation metrics including the TM-score, GDT-TS, and RMSD. Starting from an initial sequence prediction produced by a structure-aware graph neural network (GNN) [5], the refinement procedure evaluates candidate amino acid substitutions at each position by folding the modified sequence with ESMFold [9] and accepting substitutions that satisfy both a global structural improvement criterion and a local displacement threshold. Evaluated on a matched sample of 224 proteins, this set of methods reduced mean RMSD from 8.097 [A] to 4.570 [A] relative to the model's initial prediction, a 43.6% reduction, with corresponding reductions of 46.2% relative to ProteinMPNN and 27.2% relative to native ESMFolded sequences; these differences were statistically significant by paired t-test (p < 0.001). Our results show that post-prediction iterative refinement can significantly improve the structural accuracy of de novo protein sequences.",
  "abstract_shown": true,
  "affiliations": [
    "University of Texas at Dallas"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "C. M. Gammill"
    },
    {
      "name": "L. Tamil"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bjcw09dccmw8g.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.27.762198",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762198v1.full",
  "id": "bjcw09dccmw8g",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762198v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genetics"
    ],
    [
      "openalex",
      "1312|Protein Structure and Dynamics"
    ]
  ],
  "openalex": "W7224107583",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762198v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bjcw09dccmw8g.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:05Z",
      "native_id": "10.64898/2026.10.27.762198",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.27.762198v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genetics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Iterative Refinement for Structural Optimization of De Novo Protein Sequences",
  "title_text": "Iterative Refinement for Structural Optimization of De Novo Protein Sequences",
  "type": "preprint",
  "updated_at": "2026-10-30T12:30:05Z",
  "url": "https://research.draconitic.com/paper/bjcw09dccmw8g",
  "venue": "bioRxiv",
  "versions": []
}