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Method for predicting binding free energy of protein and ligand based on progressive neural network

A neural network and neural network training technology, which is applied in the field of predicting the binding free energy of proteins and ligands based on progressive neural networks, can solve problems such as poor correlation of calculation results, low accuracy, and large calculation time, and achieve The effect of avoiding over-fitting problems, good generalization ability, and speeding up calculation speed

Active Publication Date: 2020-03-24
JIANGSU UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0007] To sum up, the current general molecular docking method is not accurate enough, and the free energy calculation method based on physical models has time-consuming calculations and poor correlation of calculation results in the calculation of binding free energy between proteins and ligand molecules. question

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  • Method for predicting binding free energy of protein and ligand based on progressive neural network
  • Method for predicting binding free energy of protein and ligand based on progressive neural network
  • Method for predicting binding free energy of protein and ligand based on progressive neural network

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Embodiment Construction

[0036] Such as Figure 1-Figure 4 A method for predicting protein-ligand binding free energy based on a progressive neural network is shown, comprising the following steps:

[0037] Step 1: Establish a database server, a structural information processing server and a neural network training server, and the database server, structural information processing server and neural network training server all communicate with each other through the Internet;

[0038] Based on the crystal structure data in the PDB database and PDBbind database, after data preprocessing, the PDBLig database is established in the local database server to store the pdb files of proteins and ligand molecules.

[0039] The process of data preprocessing includes downloading data from PDB and PDBbind databases, deleting files with incomplete structures or no ligand molecules or no experimental binding constants.

[0040] In this embodiment, the analysis accuracy of each pdb file is classified in the PDBbind da...

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Abstract

The invention discloses a method for predicting the binding free energy of protein and ligand based on a progressive neural network, and belongs to the technical field of computer-aided drug design. The method comprises the steps: obtaining a pdb file from a PDBbind database, establishing local database, acquiring an amino acid molecule within 4.5 angstroms in the protein binding pocket by takingthe ligand molecule as a center, performing extended connectivity fingerprint calculation, carrying out SPLIF fingerprint calculation, searching for the number of salt bridges and hydrogen bonds between protein and ligand molecules, converting the structural information of the protein and the ligand into a one-dimensional tensor, and establishing a training set, a verification set and a test set;training the progressive neural network by using the training set; optimizing and searching hyper-parameters for prediction; through comparison with a molecular docking result, obtaining a higher Pearson correlation coefficient. According to the invention, the technical problem of how to convert a three-dimensional structure of protein and ligand molecules into tensors which are easy to calculateby a computer and input the tensors into the progressive neural network for training and optimization is solved, and the calculation rate and the prediction accuracy are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of computer-aided drug design, and relates to a method for predicting the binding free energy of a protein and a ligand based on a progressive neural network. Background technique [0002] The free energy calculation method is related to the key field of drug design and is the core technology to realize high-throughput drug screening. The traditional experimental method based on random screening has problems such as long development cycle, high cost and blindness in the selection of massive drug molecules. How to screen tens of millions of molecules to obtain the final drug molecule is a problem that must be faced in drug screening. With the rapid development of computer technology and computational theoretical methods, a new drug development method, computer-aided drug design, has emerged. The method utilizes the fast calculation of the computer, combined with the physical model of the interaction between...

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Application Information

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IPC IPC(8): G16B20/00
CPCG16B20/00Y02A90/10
Inventor 谢良旭孟黎
Owner JIANGSU UNIV OF TECH
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