Three-dimensional molecular structure generation method, device, equipment and storage medium

Through the deep learning framework of the diffusion denoising probability model, a fully connected adjacency matrix is ​​constructed and three-dimensional equivariant processing is performed, which solves the problems of low efficiency and error accumulation in generating three-dimensional molecular structures in the existing technology, realizes the de novo generation of the atomic type and position information of the molecule, and generates an accurate three-dimensional molecular structure.

CN115206457BActive Publication Date: 2025-10-17TENCENT TECHNOLOGY (SHENZHEN) CO LTD
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Patent Information

Application Number
CN202210871893.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-07-22
Publication Date
2025-10-17
Estimated Expiration
2042-07-22

AI Technical Summary

Technical Problem

Existing molecular generation methods cannot accurately generate effective three-dimensional molecular structures. Especially in drug discovery problems, existing technologies cannot generate the three-dimensional spatial geometric structure of ungiven molecules, and autoregressive methods are prone to accumulated errors.

Method used

A deep learning generation framework based on a diffusion denoising probabilistic model is adopted to obtain atomic type noise and atomic coordinate noise, construct a fully connected adjacency matrix and perform three-dimensional equivariant processing, iteratively generate molecular representations of molecules, and finally construct a three-dimensional molecular structure.

Benefits of technology

It realizes the generation of the atomic type and atomic position information of molecules from scratch, improves the generation efficiency, avoids cumulative errors, and accurately generates effective three-dimensional molecular structures.

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Abstract

Embodiments of the present application provide a three-dimensional molecular structure generation method, device, equipment and storage medium, at least applied to the field of artificial intelligence and the field of drug synthesis, wherein the method comprises: obtaining atomic type noise and atomic coordinate noise at a current time step; constructing a full connection adjacency matrix based on the atomic type noise; performing three-dimensional isometry processing on the atomic type noise, the atomic coordinate noise and the full connection adjacency matrix to obtain a molecular structure distribution average value at the current time step; generating a molecular structure of the molecule iteratively based on the molecular structure distribution average value at the current time step to obtain a molecular representation of the molecule; and constructing the three-dimensional molecular structure through the molecular representation. Through the present application, the efficiency of three-dimensional molecular structure generation can be accelerated and cumulative errors can be avoided, so as to accurately generate a three-dimensional molecular structure of an effective molecule.
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