Abstract: A ligand screening model construction method, a ligand screening model construction device, and a drug ligand screening method for drug screening, comprising that obtain a drug ligand training set, and the drug ligand training set includes a drug ligand chemical formula and a classification label; a ligand graph network is drawn, in which atoms are nodes and chemical bonds are edges connecting nodes; use a random initialization vector to identify the weight vector of each node in the ligand graph network; reconstruct each node of the ligand graph network to obtain a reconstruction network, and repeat the reconstruction steps to obtain at least two layers of reconstruction networks; perform deep learning on the ligand graph network and the at least two-layer reconstruction graph network according to the classification labels, and construct a ligand screening model.

Abstract: A drug screening model construction method and device, a screening method, apparatus and a medium, in the field of drug screening that includes obtaining a drug training set, where the set comprises a chemical formula of a drug protein, a chemical formula of a small molecule and a classification label; drawing an initial graph network of drug protein and small molecule, in which atoms are nodes and chemical bonds are edges connecting nodes; using a random initialization vector to identify the weight vector of each node; reconstructing each node of the initial graph network according to the connection relationship of the initial graph network to obtain a reconstruction network, and repeating the reconstruction steps to obtain at least two layers of reconstruction networks; performing deep learning on the initial graph network and the reconstruction graph network according to the classification labels, and constructing a drug screening model.

Abstract: A PROTAC target molecule generation method, system, and storage medium where the method includes obtaining parameters; extract the target protein ligand structure corresponding to the first parameter in the target protein ligand database to form a first subset, extract the degradation agent fragment structure corresponding to the parameter in the degradation agent fragment database to form a second subset, and extract the linker fragment structure corresponding to the parameter in the linker fragment database to form a third subset; permute and combine each fragment structure in the subsets to generate PROTAC target molecules. The extract required fragment structures from various databases, then permute and combine the three groups of fragment structure, and use big data and computational processing to be used for experiments, avoids the omission of the combination of structural fragments, improves the accuracy of molecular design and speeds up drug research and development processes.

Abstract: The present application provides a method, a device, and a system for compound clustering and a storage medium, including acquiring samples of compounds to be identified, and segmenting the samples of the compounds into a subset of samples including an initial identification tag; obtaining a sample legend according to the sample subset; and obtaining target identification tag results corresponding to the samples of the compounds according to the sample legend and the identification tag, wherein the identification tag includes the initial identification tag. The present invention provides an efficient, rapid and accurate method for small molecule compound clustering based on statistical compound clustering, improving the accuracy of small molecule compound clustering, reducing the processing space of clustering and breaking through the limitations of small molecule clustering, thereby making the processing of small molecule compound clustering more efficient and accurate.