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A low-complexity prediction method for naturally disordered proteins

A low-complexity, prediction method technology, applied in the field of bioinformatics, can solve the problems of high computational complexity and low accuracy, achieve high computing speed and robustness, reduce the number of features and computational complexity.

Active Publication Date: 2020-05-08
NANKAI UNIV
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Problems solved by technology

Among them, the first type of method is very simple but the accuracy is not high
The second type of method is mainly based on artificial neural network and support vector machine, which can obtain high prediction accuracy, but requires the calculation of a series of features with high computational complexity

Method used

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  • A low-complexity prediction method for naturally disordered proteins
  • A low-complexity prediction method for naturally disordered proteins
  • A low-complexity prediction method for naturally disordered proteins

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Experimental program
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Embodiment 1

[0036] The specific steps of the method for predicting natural disordered proteins provided by the invention are as follows:

[0037] For a protein sequence w in an undetermined disordered region (taking a protein sequence labeled 1g4m in the R80 data set as an example), the specific steps for prediction using the disordered protein prediction scheme provided by the present invention are as follows:

[0038] Step 1: The length of the sequence is 393, and the sequence is intercepted with a sliding window of N=35. The values ​​of five features are calculated for each window interval.

[0039] Sequence w = MGDKGTRVFKKASPNGKLTVYLGKRDFVDHIDLVEPV

[0040] For the first window with a length of N, according to the formula (1)(3)(4), calculate the values ​​​​of the five features of the sequence fragments intercepted by the window, and assign these five values ​​​​to each of the fragments Residues; after that, sliding window, calculate the value of the five features of the sequence fr...

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Abstract

The invention provides a low computational complexity prediction method for natural disordered proteins. In the method, aimed at each residue of a protein sequence, Shannon entropy, topological entropy, and weighted average of tendency of three kinds of amino acids are calculated, and using Rayleigh-entropy maximization, a natural disordered protein region is predicted. The scheme just uses five characteristic and a linear classifier, and the method has relatively high computation speed and robustness. A simulation result shows that under similar predicted accuracy degree, compared with an existing prediction scheme in the same type, the designed natural disordered protein prediction scheme greatly reduces characteristic number and computational complexity.

Description

technical field [0001] The invention belongs to the field of bioinformatics, and relates to a high-efficiency, low-computation-complexity prediction scheme for natural disordered proteins. Background technique [0002] A natural disordered protein refers to a protein that has at least one region that lacks a unique three-dimensional structure and has a dynamic conformation. It plays an important role in drug design, protein expression, and functional annotation. Because studies have found that some naturally disordered proteins are involved in important regulatory functions in cells, which have an important impact on diseases such as Alzheimer's disease, Parkinson's disease and certain cancers. Due to difficulties in purification and crystallization of disordered protein domains, experimental determination is expensive and time consuming. Therefore, the study of determining disordered regions from protein sequences by computational methods is very important. [0003] In th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B40/20G16B20/00
CPCG16B20/00G16B40/00
Inventor 赵加祥何昊徐微
Owner NANKAI UNIV
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