{
  "id": 12526687,
  "title": "RGI-Toolkit: Differentiable Restraints for Controllable Biomolecular Structure Prediction",
  "url": "https://urgent.news/2026/10/06/rgi-toolkit-differentiable-restraints-for-controllable-biomolecular",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-06T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.05.756905v1?rss=1"
  },
  "original_language": "en",
  "account": "Diffusion-based models have significantly improved the prediction of biomolecular structures. Restrain-guided inference (RGI) is a technique used to refine these predictions by incorporating experimental data, stereochemical constraints, or a desired target conformational state into the model's output during each reverse-diffusion process. RGI-Toolkit, a Python library, enables the use of RGI with various structure predictors. This toolkit streamlines the process of defining restraints, selecting atoms, evaluating loss functions, and optimizing coordinates within a single, adaptable engine. Restraints can be applied to distance, angle, and dihedral parameters, as well as deviations from reference structures and user-defined reaction coordinates. Ligand conformer restraints are also supported. The toolkit currently integrates with six predictors, including AlphaFold3. By utilizing restraints, particularly for conformation and stereochemical properties, the toolkit reduces the occurrence of chirality and cis/trans errors in predicted ligands and guides the protein conformations towards the desired target states.",
  "summary": "Diffusion-based models have substantially advanced biomolecular structure prediction. Within this framework, restraint-guided inference (RGI) corrects the denoiser output at each reverse-diffusion step using a differentiable restraint loss, allowing available experimental information, stereochemical requirements, or a specified target conformational state to be incorporated into predictions…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}