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Protein-protein interaction prediction method using multivariate mutual information and residue binding energy

A prediction method and mutual information technology, applied in proteomics, informatics, bioinformatics, etc., can solve problems such as differences in prediction results, and achieve the effect of excellent accuracy

Inactive Publication Date: 2019-05-24
TIANJIN UNIV
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Problems solved by technology

These methods abstract the amino acid sequence from different aspects, and their prediction results are very different.

Method used

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  • Protein-protein interaction prediction method using multivariate mutual information and residue binding energy
  • Protein-protein interaction prediction method using multivariate mutual information and residue binding energy
  • Protein-protein interaction prediction method using multivariate mutual information and residue binding energy

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Embodiment Construction

[0048]The purpose of the present invention is to provide a method for accurately and efficiently predicting the interaction between proteins. The feature extraction function used in the method can improve the role of useful information in the amino acid sequence in predicting operations, while effectively reducing the impact of useless noise information.

[0049] The present invention is characterized in that it contains the following steps successively:

[0050] Step (1): Amino acid category grouping. The 20 standard amino acids were divided into 7 functional groups according to their dipolarity and volume. These seven functional groups are denoted as C 0 , C 1 , C 2 ,...,C 6 . The original amino acid sequence is converted into a group category sequence according to the functional group category of each amino acid.

[0051] Step (2): Define different types of 3-tuple and 2-tuple feature representations. The feature of the 3-tuple is expressed as "C 0 C 0 C 0 ","C ...

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Abstract

The invention relates to a biological information technology, and provides a method for accurately and efficiently predicting the interaction between a protein and a protein, capable of improving theeffect of useful information in an amino acid sequence in the prediction operation, and at the same time effectively reducing the influence of useless noise information. The protein-protein interaction prediction method using multivariate mutual information and residue binding energy includes the steps: (1) grouping amino acid categories; (2) defining feature representation; (3) establishing a feature frequency table; (4) calculating mutual information features; (5) calculating 3-element group mutual information features; (6) calculating amino acid physicochemical property features; (7) calculating an amino acid contact matrix AAC; (8) extracting amino acid sequence features; (9): performing singular value decomposition; and (10) obtaining an interaction between two proteins. The protein-protein interaction prediction method using multivariate mutual information and residue binding energy is mainly applied to the field of prediction of interactions between proteins.

Description

technical field [0001] The invention relates to a method for predicting the interaction between proteins based on amino acid sequence information in biological information technology, and belongs to the field of macromolecular structure prediction algorithms in proteomics. Specifically, it involves multivariate mutual information and residue binding energy protein interaction prediction methods. Background technique [0002] Protein-protein interactions are at the heart of many biological processes. Identifying protein-protein interactions is important for elucidating protein function and identifying biological processes in cells. Interaction information between proteins can help people better understand the mechanism of disease occurrence, so as to design drugs more efficiently and accurately. Over the past few years, a host of computational techniques have advanced to the stage where large-scale analysis is possible. In general, there are three main categories of comput...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B5/00G16B20/00
Inventor 郭菲邹权丁漪杰潘高峰唐继军
Owner TIANJIN UNIV
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