Protein-ligand binding site predicting method based on inquiry drive

Abstract

The invention provides a protein-ligand binding site predicting method based on inquiry drive. The method includes the steps of firstly, for an given inquiry input, searching protein sequences with high homology to form a training data set based on inquiry drive; secondly, extracting all the binding residues in the training data set as the positive sample set and extracting all the non-binding residues in the training data set as the negative sample set; thirdly, extracting the feature vector of each sample from evolution information and secondary structure perspective to obtain the feature vector sets of the positive and negative samples; fourthly, using a standard support vector machine algorithm for training to obtain an SVM prediction model based on the inquiry input q; fifthly, for the inquiry input, using the same feature extracting method to extract the feature vector of each residue, inputting the feature vector of each residue into the SVM prediction model, and predicting by using a threshold segmentation method. By the method, prediction precision can be increased, and the possible problems of over-optimization and over-fitting on the fixed training data set can be prevented.

Description

technical field [0001] The invention relates to the field of bioinformatics protein-ligand interaction, in particular to a query-driven dynamic protein-ligand binding site prediction method. Background technique [0002] Protein-ligand interactions are ubiquitous and indispensable in life activities. It is time-consuming and labor-intensive to determine the binding sites between proteins and ligands through biological experiments. With the rapid development of sequencing technology and the advancement of the human structural genome, a large number of protein sequences without binding site mapping have been accumulated. Therefore, there is an urgent need to develop intelligent methods that can predict protein-ligand binding sites directly from protein sequences. In recent years, several sequence-based protein-ligand binding site prediction methods have emerged, for example: (1) Chen, K., Mizianty, M.J. and Kurgan, L. (2011) ATPsite: sequence-based prediction of ATP-binding...

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Problems solved by technology

[0012] In view of the defects or deficiencies in the prior art, the present invention aims to provide a query-driven dynamic protein-ligand binding site prediction method to solve the problems existing in the protein-ligand binding site prediction method in the prior art. Low scalability, overfitting / overoptimization, and low usability issues

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