Inherent irregular protein structure forecasting method based on kernel canonical correlation analysis

Abstract

The invention provides an inherent irregular protein structure forecasting method based on kernel canonical correlation analysis. The method includes: (1) extracting architectural features and biochemical features of protein to be forecasted to serve as recognition features, wherein the architectural features are combination frequencies of amino acid on the periphery of forecasting sites of protein and obtained in a window method, and the biochemical features are Russell / Linding value, hydrophobicity, polarity and electrification of amino acid at the forecasting sites of protein; (2) performing mapping and integrating for the extracted feature data in the kernel canonical correlation analysis method to obtain feature data favorable for protein structure recognition, wherein a kernel function used in the kernel canonical correlation analysis method is a radial basis function; and (3) recognizing and forecasting protein structure on the basis of the feature data favorable for protein structure recognition. The feature data favorable for protein structure recognition is effectively improved in forecasting accuracy, is favorable for supplying early-period basis to finding and verification of inherent irregular protein, and supplies foundation to development of biological pharmacy.

Description

technical field [0001] The invention relates to a method for dealing with biological problems by using the nuclear canonical correlation analysis method commonly used in information science. Specifically, it is a method for inherently irregular protein structure prediction using the nuclear canonical correlation analysis method commonly used in information science. Background technique [0002] It has long been believed that the specific regular structure of proteins is the basis for protein functions, and proteins lacking specific regular structures are inactive. The discovery of proteins with inherently irregular structures shatters this view. Not only are proteins with inherently irregular structures not useless, they precisely perform important functions in cells. Many cancers are associated with irregular proteins. Since the discovery of inherently irregular proteins is difficult, the research on methods for predicting the structure of inherently irregular proteins c...

AI Technical Summary

Problems solved by technology

[0003] Since the research on the prediction of inherently irregular protein structures is less than ten years old, there are not many corresponding prediction methods

Images