{
  "patent_number": "US 12437843",
  "country": "US",
  "title": "Using AI to Predict Protein Shapes for Drug Discovery",
  "original_title": "Predicting protein structures using geometry neural networks that estimate similarity between predicted protein structures and actual protein structures",
  "summary": "This patent describes an AI-driven method for iteratively predicting protein 3D structures using a geometry neural network, then using those predictions to find and synthesize new drug molecules.",
  "what_it_does": "The patent details a method for predicting the 3D shape (structure) of a protein, which is then used to identify and create new drug molecules, called ligands. The core process involves an iterative refinement loop (Claim 1). At each step, the system maintains a \"current predicted structure\" and generates an \"alternative predicted structure.\" A \"geometry neural network\" then processes the protein's amino acid sequence and the alternative structure's parameters to produce a \"geometry score\" (Claim 1). This score estimates how similar the alternative structure is to the protein's actual shape. Based on this score, the system decides whether to update its current prediction. Once a sufficiently high-quality predicted structure is determined, the method evaluates how well various \"candidate ligands\" (potential drugs) might interact with this predicted protein shape. It selects candidates predicted to bind effectively and then proceeds to synthesize them (Claim 1).",
  "what_it_does_not_cover": [
    "Does not cover protein structure prediction methods that do not use a geometry neural network to estimate similarity to an actual structure (Claim 1).",
    "Does not cover methods for predicting protein structures that do not involve an iterative update process (Claim 1).",
    "Does not cover protein structure prediction that isn't ultimately used for evaluating and selecting candidate drug ligands (Claim 1).",
    "Does not cover methods that predict protein structures but do not include the step of synthesizing the selected ligands (Claim 1).",
    "Does not cover protein structure prediction without considering the sequence of amino acid residues (Claim 1)."
  ],
  "filed": "2019-09-16",
  "granted": "2025-10-07",
  "expires": "2039-09-16",
  "status": "active",
  "holder": "GDM Holding",
  "holder_url": "https://patentbrief.org/company/gdm-holding",
  "inventors": [
    {
      "name": "John Jumper",
      "url": "https://patentbrief.org/inventor/john-jumper"
    },
    {
      "name": "Hugo Penedones",
      "url": "https://patentbrief.org/inventor/hugo-penedones"
    },
    {
      "name": "Andrew W. Senior",
      "url": "https://patentbrief.org/inventor/andrew-w-senior"
    },
    {
      "name": "Chongli Qin",
      "url": "https://patentbrief.org/inventor/chongli-qin"
    },
    {
      "name": "Karen Simonyan",
      "url": "https://patentbrief.org/inventor/karen-simonyan"
    },
    {
      "name": "Richard Andrew Evans",
      "url": "https://patentbrief.org/inventor/richard-andrew-evans"
    },
    {
      "name": "James Kirkpatrick",
      "url": "https://patentbrief.org/inventor/james-kirkpatrick"
    },
    {
      "name": "Laurent Sifre",
      "url": "https://patentbrief.org/inventor/laurent-sifre"
    },
    {
      "name": "Ruoxi Sun",
      "url": "https://patentbrief.org/inventor/ruoxi-sun"
    }
  ],
  "times_cited": 0,
  "tags": [
    "biotech",
    "pharmaceutical",
    "ai_ml",
    "software"
  ],
  "abstract": "Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing protein structure prediction. In one aspect, a method comprises, at each of one or more iterations: determining an alternative predicted structure of a given protein defined by alternative values of structure parameters; processing, using a geometry neural network, a network input comprising: (i) a representation of a sequence of amino acid residues in the given protein, and (ii) the alternative values of the structure parameters, to generate an output characterizing an alternative geometry score that is an estimate of a similarity measure between the alternative predicted structure and the actual structure of the given protein.",
  "url": "https://patentbrief.org/patent/us/12437843/predicting-protein-structures-using-geometry-neural-networks-that-estimate-simil",
  "markdown_url": "https://patentbrief.org/patent/us/12437843/predicting-protein-structures-using-geometry-neural-networks-that-estimate-simil/md",
  "google_patents_url": "https://patents.google.com/patent/US12437843",
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}