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1.发明申请公开(公告)号：US20250104817A1
公开(公告)日：2025-03-27
申请号：US18974497
申请日：2024-12-09
Inventor： Lihang Liu , Xiaomin Fang , Xiaonan Zhang , Jingzhou He
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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公开(公告)号：US20250149110A1
公开(公告)日：2025-05-08
申请号：US18929408
申请日：2024-10-28
Inventor： Kunrui Zhu , Lihang Liu , Xiaomin Fang , Xiaonan Zhang , Jingzhou He
Abstract: A method for predicting a structure of a protein complex includes: obtaining an initial coordinate of each amino acid residue in a target protein complex, and obtaining a target residue pair feature, a first multiple sequence alignment (MSA) feature and a second MSA feature of each protein monomer in the target protein complex; and inputting the initial coordinate of each amino acid residue, and the target residue pair feature, the first MSA feature and the second MSA feature of each protein monomer into an N-level fold iteration network layer, and obtaining a target coordinate of each amino acid residue by predicting a torsion angle, a position transformation at residue level and a position transformation at monomer chain level of each amino acid residue via the N level fold iteration network layer, to obtain a predicted structure of the protein complex.
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公开(公告)号：US20250104803A1
公开(公告)日：2025-03-27
申请号：US18972078
申请日：2024-12-06
Inventor： Kunrui Zhu , Lihang Liu , Xiaomin Fang , Xiaonan Zhang , Jingzhou He
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.
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公开(公告)号：US20230245727A1
公开(公告)日：2023-08-03
申请号：US18126887
申请日：2023-03-27
Inventor： Donglong HE , Lihang Liu , Dayong Lin , Xiaomin Fang , Fan Wang , Jingzhou He
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.
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