A method and system for probe occupancy probability grid construction for molecular dynamics trajectories

By using automated identification and construction techniques, the problem of probe identification difficulties in MixMD has been solved, enabling effective analysis of probe distribution, simplifying the process, improving the efficiency and accuracy of drug discovery, enhancing the ability to identify hidden pockets, and generating files that facilitate drug design and ligand optimization.

CN122392615APending Publication Date: 2026-07-14JINHUA INSTITUTE OF ADVANCED STUDIES IN SCIENCE & TECHNOLOGY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JINHUA INSTITUTE OF ADVANCED STUDIES IN SCIENCE & TECHNOLOGY
Filing Date
2026-04-24
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Existing Mixed Solvent Molecular Dynamics (MixMD) analysis workflows suffer from difficulties in probe identification, complex grid construction, inconsistent statistical methods, and poor visualization of results, leading to low efficiency and high barriers to entry.

Method used

An automated system is provided, including modules for data import, probe identification, grid generation, statistical analysis, and result output. It can automatically identify probe distribution, construct three-dimensional occupied grid points, perform cluster analysis, and generate visualization files.

Benefits of technology

It simplifies the analysis process, improves the efficiency and accuracy of probe distribution analysis, enhances the ability to identify hidden pockets, and generates files that facilitate drug design and ligand optimization.

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Abstract

The application develops a three-dimensional occupation grid construction method and system based on probe distribution statistics, which is suitable for automatic analysis of mixed-solvent molecular dynamics (MixMD) trajectory. The method first receives the protein structure file and the trajectory file, automatically identifies the non-standard probe molecules and analyzes the spatial coordinates; then, according to the grid spacing dx and the maximum distance cutoff set by the user, a three-dimensional grid is constructed, and the number of probe occurrences in each grid point in the trajectory is accumulated frame by frame to obtain the occupation probability matrix. The system further performs spatial clustering based on the probe occupation distribution, automatically identifies potential binding sites and hidden pocket areas, and generates a structured output file containing occupation information, clustering labels and visual coordinates. The system realizes the full-process automation of probe distribution analysis, can significantly improve the MixMID data processing efficiency, improve the accuracy and stability of the binding pocket identification, and is suitable for the fields of structural biology, drug design and protein dynamics research.
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