{
  "annotation_id": "bef9cd60-c010-479e-8d53-a6ea6f69fb78",
  "date_created": "2026-03-02T18:01:31.854000Z",
  "date_modified": "2026-03-02T18:01:31.854000Z",
  "file_hash": "c9b898afb2eb81b5fde7945112ab9ddfcea0b510c9fdfa4dc1c9c71c7b19416a",
  "private": false,
  "record": {
    "abstract": "A newly developed statistical pair potential based on Distance-scaled Finite\nIdeal-gas REference (DFIRE) state is applied to unbound protein-protein docking\nstructure selections. The performance of the DFIRE energy function is compared\nto those of the well-established ZDOCK energy scores and RosettaDock energy\nfunction using the comprehensive decoy sets generated by ZDOCK and RosettaDock.\nDespite significant difference in the functional forms and complexities of the\nthree energy scores, the differences in overall performance for docking\nstructure selections are small between DFIRE and ZDOCK2.3 and between DFIRE and\nRosettaDock. This result is remarkable considering that a single-term DFIRE\nenergy function was originally designed for monomer proteins while\nmultiple-term energy functions of ZDOCK and RosettaDock were specifically\noptimized for docking. This provides hope that the accuracy of the existing\nenergy functions for docking can be improved.",
    "arxiv_id": "q-bio/0406025",
    "authors": [
      "Song Liu",
      "Chi Zhang",
      "Yaoqi Zhou"
    ],
    "categories": [
      "q-bio.BM",
      "q-bio.QM"
    ],
    "title": "Unbound Protein-Protein Docking Selections by the DFIRE-based   Statistical Pair Potential",
    "url": "https://arxiv.org/abs/q-bio/0406025"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "4989b725-1aac-4f96-85d2-e6a91299cc1f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}