Energy-based multi-objective optimization fitting prediction method for atomic structures and electron density maps

A multi-objective optimization and electron density technology, applied in the field of bioinformatics, can solve problems such as deviation, achieve good fitting performance, and improve the effect of fitting difficulty

A multi-objective optimization and electron density technology, applied in the field of bioinformatics, can solve problems such as deviation, achieve good fitting performance, and improve the effect of fitting difficulty

CN111968707AActive Publication Date: 2020-11-20SHANGHAI JIAO TONG UNIV
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  • Energy-based multi-objective optimization fitting prediction method for atomic structures and electron density maps
  • Energy-based multi-objective optimization fitting prediction method for atomic structures and electron density maps
  • Energy-based multi-objective optimization fitting prediction method for atomic structures and electron density maps

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Embodiment Construction

[0025] Such as figure 1 As shown, this embodiment involves an energy-based multi-objective optimization fitting prediction method for atomic structure and electron density map. The predicted atomic structure is initially moved to the center of the density map, and N initial models are generated; then the Pareto set is selected by the multi-objective particle swarm optimization algorithm, and the optimal model is selected by the Knee algorithm, and the atomic structure is obtained by calculation. Fitting results between and electron density maps.

[0026] The benchmark data set for constructing the predicted structure and electron density map is described, and the statistical results of the obtained data set are as follows figure 2 and image 3 As shown, it specifically includes the following steps:

[0027]S11. First extract all PDBs (1809 in total) containing electron density maps from the PDB database, and then split the 1809 PDB structures into 37952 single-chain PDB st...

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Abstract

The invention discloses an energy-based multi-objective optimization fitting prediction method for atomic structures and electron density maps. The method comprises the following steps: building a reference data set of a predicted structure and an electron density map according to three-dimensional structures and electron density maps of proteins, and generating an initial model; preliminarily moving the predicted atomic structure to the center of the density map by using the information of the electron density map to generate N initial models; selecting a Pareto set through a multi-objectiveparticle swarm optimization algorithm, selecting an optimal model from the Pareto set through a Knee algorithm, and acquiring a fitting result between the atomic structure and the electron density mapthrough calculation. According to the invention, the problem of potential deviation caused by minimizing a single energy function can be solved.

Description

technical field [0001] The invention relates to a technology in the field of biological information, in particular to a multi-objective optimization fitting prediction method for atomic structure and electron density map based on global and local energy. Background technique [0002] High-resolution protein structures are important for understanding the functions of proteins and the mechanisms of related diseases. Several methods such as X-ray crystallography, nuclear magnetic resonance (NMR) and cryo-electron microscopy (Cryo-EM) have been used to obtain macromolecular structures. In recent years, due to the revolutionary development of cryo-EM imaging technology, a large number of cryo-EM density maps have appeared, but these density maps usually have relatively low resolution (eg ). Although most EM-derived density maps are not sufficiently high resolution, they can often provide a description of molecular topology and thus can be applied to the optimization of atomic ...

Claims

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Application Information

Patent Timeline
20 Nov 2020
Publication
CN111968707A
IPC
G16B40/00; G16B45/00; G16B15/20
CPC
G16B40/00; G16B45/00; G16B15/20
Inventors
张彪; 沈红斌