METHOD AND ELECTRONIC DEVICE FOR GENERATING MOLECULE SET, AND STORAGE MEDIUM THEREOF

    公开(公告)号:US20230019202A1

    公开(公告)日:2023-01-19

    申请号:US17936422

    申请日:2022-09-29

    Abstract: Embodiments of the present disclosure provide a method and electronic device for generating a molecule set and a storage medium thereof. The method obtains the first initialization molecule subset from the initialization molecule set with the pre-screening model; acquires the physical information of at least one initialization molecule in the first initialization molecule subset, and screens at least one initialization molecule based on the physical information to obtain the screened molecule set; acquires the biochemical experimental evaluation value of at least one molecule in the screened molecule set; and obtains the target molecule set based on the biochemical experimental evaluation value of at least one molecule.

    METHOD FOR INFORMATION PROCESSING, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20250104803A1

    公开(公告)日:2025-03-27

    申请号:US18972078

    申请日:2024-12-06

    Abstract: A method for information processing, is performed by an electronic device, and the method includes: obtaining a residue sequence AT that does not carry amino acid information and a first protein backbone structure BT generated by pure noise; and performing iterative denoising on the residue sequence AT and the first protein backbone structure BT; for a tth denoising, obtaining coevolution information of a residue sequence AT+1−t, and obtaining, based on the coevolution information and a first protein backbone structure BT+1−t, a residue sequence AT−t and a first protein backbone structure BT−t after the tth denoising, until the denoising is completed and a target amino acid sequence and a second protein backbone structure are obtained, where t is a positive integer, and 1≤t≤T, and T is a number of denoising times.

    METHOD FOR MOLECULAR REPRESENTING
    4.
    发明公开

    公开(公告)号:US20230245727A1

    公开(公告)日:2023-08-03

    申请号:US18126887

    申请日:2023-03-27

    CPC classification number: G16C20/30 G16C20/50 G16C20/70

    Abstract: A computer-implemented method is provided. The method includes: obtaining feature information of a molecule to be represented, wherein the molecule includes a plurality of atoms; generating a fully connected graph of the plurality of atoms, wherein the fully connected graph includes a plurality of edges; generating, based on the feature information, a plurality of atom vector representations and a plurality of edge vector representations, wherein the plurality of atom vector representations correspond to the plurality of atoms, respectively, and the plurality of edge vector representations correspond to the plurality of edges, respectively; performing, based on the fully connected graph, at least one aggregation on the plurality of atom vector representations and the plurality of edge vector representations to obtain a plurality of updated atom vector representations; and generating, based on the plurality of updated atom vector representations, a molecular vector representation of the molecule.

    TRAINING METHOD AND APPARATUS FOR FULL ATOMIC STRUCTURE PREDICTION MODEL, AND ELECTRONIC DEVICE

    公开(公告)号:US20250104817A1

    公开(公告)日:2025-03-27

    申请号:US18974497

    申请日:2024-12-09

    Abstract: A training method and apparatus for a full atomic structure prediction model. The method includes: obtaining structural information of a biomolecule and a first dynamic trajectory of the biomolecules; in which, the first dynamic trajectory includes position information of atoms in the biomolecule at different time points; adding noise to the first dynamic trajectory to obtain a second dynamic trajectory; encoding the structural information to obtain encoded features; decoding the encoded features and the second dynamic trajectory to obtain a target dynamic trajectory; and training an initial full atomic structure prediction model based on a difference between the target dynamic trajectory and the first dynamic trajectory, to obtain the full atomic structure prediction model.

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