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Prokaryotic protein acetylation site prediction method

A prediction method and acetylation technology, applied in proteomics, special data processing applications, instruments, etc., can solve the problems of incomplete information on the characteristics of acetylation sites, prediction of acetylation sites of unprokaryotic proteins, etc., and achieve improved prediction Accuracy, effect of dimensionality reduction

Inactive Publication Date: 2017-12-12
NANCHANG UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These prediction methods predict lysine acetylation, but do not predict prokaryotic protein acetylation sites; and most of the prediction methods only use a certain feature algorithm, and the extracted acetylation site feature information is incomplete ;Among all acetylation prediction methods, only two methods optimize features based on the consideration of two-step feature selection

Method used

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  • Prokaryotic protein acetylation site prediction method
  • Prokaryotic protein acetylation site prediction method
  • Prokaryotic protein acetylation site prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0064] a kind of like figure 1 The prediction method of the prokaryotic protein acetylation site shown, the specific steps are as follows:

[0065] 1) Collect data

[0066] Collect prokaryotic protein acetylation data from protein databases such as UniProt, CPLM and NCBI and related literature;

[0067] 2) Data processing

[0068] Archaea, Vibrio parahaemolyticus, Escherichia coli, Corynebacterium glutamicum, Mycobacterium tuberculosis, Bacillus subtilis, Geobacillus thermophile, Lemoniasis et al. A total of nine prokaryotic protein acetylation positive sample data sets and negative sample data sets of Salmonella typhimurium;

[0069] The positive sample is the acetylation site marked by experimental verification, and the negative sample is the unlabeled lysine (K) sequence randomly selected from the same protein as the positive sample with the same number as the positive sample. Data processing includes the following sub-steps:

[0070] 2 ▪1) According to structural bio...

Embodiment 2

[0105] The prediction software platform ProAcePred was applied to predict the acetylation site of the protein named "P00448".

[0106] The prediction software is the prediction software platform ProAcePred using MATLAB software and C# programming language. The prediction software platform ProAcePred, when the user submits at least one prokaryotic protein sequence, for example, to predict the acetylation site of the protein named "P00448" in the UniProt database, only needs to input the FASTA format of the protein on the prediction interface, select the predicted model and the appropriate Threshold, click the "Submit" button, the ProAcePred tool will predict the "P00448" protein, and automatically give the potential acetylation site information of the protein, and the results will be displayed in the designated area, realizing the acetylation site of prokaryotic proteins High-throughput forecasting.

[0107] image 3 It is the predicted result of lysine acetylation of the seque...

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Abstract

The present invention discloses a prokaryotic protein acetylation site prediction method. The method comprises the steps of: collecting data; processing the data; performing feature coding: feature training; and constructing a prediction model. The present invention further discloses an application of the prokaryotic protein acetylation site prediction method. The method disclosed by the present invention comprises: based on multi-dimensional feature coding of protein primary structure information, physicochemical information and evolutionary information, extracting a feature of prokaryotic protein acetylation sequence; optimizing and selecting an optimal eigenvector by using an Elastic Net; and by combining a support vector machine (SVM), constructing a prediction model of a prokaryotic acetylation site, which significantly improves prediction performance of the prediction model for the prokaryotic acetylation site. A developed prediction software platform ProAcePred realizes high-throughput prediction of the prokaryotic protein acetylation site, provides an accurate, simple and rapid researching tool for study on protein acetylation, and offers valuable reference information to further experimental researches.

Description

technical field [0001] The present invention relates to digital calculation or data processing equipment or data processing method specially used for specific applications, in particular to a method for predicting prokaryotic protein acetylation sites. Background technique [0002] Acetylation, a highly regulated protein post-translational modification necessary for protein activity, occurs in core histones, nearly 40 transcription factors, and more than 30 other protein targets. From bacteria to humans, protein acetylation not only plays a key role in nuclear function, but also plays an important role in the regulation of various cytoplasmic metabolism, including cytoskeleton dynamics, energy metabolism, endocytosis, autophagy, and even transmembrane signal conduction. The identification of acetylation sites will be the basis for understanding the molecular mechanism of acetylation. Acetylation sites can be identified by experimental techniques such as mass spectrometry, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/28G06F19/18G06K9/62
CPCG16B20/00G16B50/00G06F18/2411
Inventor 施绍萍陈国东曹曼
Owner NANCHANG UNIV
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