Calculation method for predicting multi-polar expansion attribute of dipeptide model through BP neural network

Abstract

The invention relates to a calculation method for predicting the multi-polar expansion attribute of a dipeptide model through a BP neural network. The calculation method for predicting the multi-polar expansion attribute of the dipeptide model through the BP neural network comprises the following steps that the structures of different dipeptide conformations are optimized through quantum mechanics calculation software Gaussian, and physicochemical parameters of the dipeptide conformations and the distance between atoms are calculated; the physicochemical parameters of part of the atoms of the dipeptide conformations and the distance between the atoms are selected for training the BP neural network, so that the physicochemical parameter of the BP neural network is obtained; the other dipeptide conformations serve as a testing set to verify a prediction result based on the BP neural network. According to the calculation method for predicting the multi-polar expansion attribute of the dipeptide model through the BP neural network, quantum mechanics calculation is conducted through the BP neural network instead of quantum mechanics calculation Gaussian software, the physicochemical parameter information such as the energy and the multi-polar distance of dipeptide can be quickly provided according to different conformations on the basis of molecular mechanics simulation based on force field information. Calculation time is greatly shortened and calculation quantity is greatly reduced within the acceptable error range, and the precision in the dynamic simulation process is greatly improved.

Description

technical field [0001] The invention belongs to the field of combining quantum mechanics and molecular mechanics calculations, calculation methods and artificial intelligence, and specifically relates to a calculation method for predicting the multi-pole expansion properties of a dipeptide model through a BP neural network. Background technique [0002] Molecular Simulation is a computer-based simulation method developed in the late 20th century. With the improvement of the theory of quantum mechanics, the update of the empirical force field, and the improvement of computing speed and capacity driven by the development of computer hardware, the theory and method of molecular simulation have developed rapidly, and have played a key role in many disciplines and application fields. effect. From the principle of simulation, molecular simulation can be divided into two categories: theoretical calculation of quantum mechanics simulation QM (Quantum Mechanics) and empirical calcul...

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Problems solved by technology

AMOEBA considers this phenomenon, but it is still a synthesis of various conformational physical and chemical parameters, which cannot reach the level of specific physical and chemical parameters for a specific conformation to describe the atomic state

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