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A Method for Identifying Protein Folding Type Based on Amino Acid Sequence

A protein folding and type recognition technology, applied in the field of bioinformatics, can solve the problem that the accuracy of recognition is not particularly high

Active Publication Date: 2020-09-25
BEIJING UNIV OF TECH
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  • Application Information

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Problems solved by technology

And the accuracy of recognition is not particularly high, most of them remain between 70% and 90%, and more than 90% will be considered to have a high recognition accuracy. The types of proteins are huge, and it is impossible to study only a small number of folding types. Satisfy requirements, need to expand the scope of the study

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  • A Method for Identifying Protein Folding Type Based on Amino Acid Sequence
  • A Method for Identifying Protein Folding Type Based on Amino Acid Sequence
  • A Method for Identifying Protein Folding Type Based on Amino Acid Sequence

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Embodiment Construction

[0024] An embodiment of the present invention provides a protein folding type identification method based on amino acid sequence, comprising the following steps:

[0025] Step 1. Establish hidden Markov models for α, β, α / β, and α+β four types of proteins in units of family and superfamily respectively, and a set of folding type recognition models represented by family and superfamily respectively, used for Identify the folding type of the protein to be tested, and expand the two model sets respectively to form an extended family model set and an expanded superfamily model set. All four model sets can be used for protein folding type identification, which can expand the identification range of samples.

[0026] The present invention takes the four types of proteins α, β, α / β, and α+β in the SCOPe database as the research objects. The data of SCOPe-2.05 version were selected for modeling. Previous studies have shown that the Hidden Markov Model has a remarkable recognition eff...

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Abstract

The invention discloses an amino acid sequence-based protein folding type identification method. The method comprises: step 1, for four types of proteins of alpha, beta, alpha / beta and alpha+beta, respectively using families and superfamilies as units to establish hidden Markov models, respectively using the families and the superfamilies as representatives to establish folding type identification model sets, and respectively extending the two model sets at the same time to form an extended family model set and an extended superfamily model set; and step 2, carrying out automatic protein folding type identification according to the folding type identification model sets. By adopting the method, a sample coverage range of identification can be enlarged, an accuracy rate of folding type identification can be increased, automatic operations of folding type identification are realized at the same time, and phenomena of poor identification effect caused by human factors are reduced.

Description

technical field [0001] The invention belongs to the field of bioinformatics, in particular to a protein folding type identification method based on amino acid sequence. Background technique [0002] Due to the complexity of the protein itself and the complexity of its living environment, the study of proteins has always been the focus and difficulty. The identification of protein folding type has always been the focus of research in the field of life sciences, and it is one of the main methods for the prediction of protein three-dimensional structure. [0003] Protein folding type recognition is a method based on structure or model information. The main methods are divided into two categories: machine learning and sequence-sequence alignment (multiple sequence alignment). Machine learning mainly includes methods such as artificial neural networks, random forests, and support vector machines. Multiple sequence alignment methods are mainly based on two sequence models for id...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B15/20
CPCG16B15/00
Inventor 李晓琴景娅楠
Owner BEIJING UNIV OF TECH