Method for representing activity relationships of antibacterial proteins or polypeptides

An activity relationship, protein technology, applied in the field of amino acid structure characterization, can solve the problems of difficulty in collecting experimental parameters of non-coding amino acid diversity, difficult, and few research reports.

Inactive Publication Date: 2012-09-12
CHONGQING UNIV OF TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

At present, there are physical and chemical properties and quantitative calculation descriptors. These descriptors mainly characterize coding amino acids. Due to the diversity of non-coding amino acids and the difficulty in collecting experimental parameters, it is extremely difficult to develop a set of efficient descriptor systems for them. Therefore, this class Few research reports

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  • Method for representing activity relationships of antibacterial proteins or polypeptides
  • Method for representing activity relationships of antibacterial proteins or polypeptides
  • Method for representing activity relationships of antibacterial proteins or polypeptides

Examples

Experimental program
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Embodiment 1

[0030] Example 1 QSAR research on 101 cationic antimicrobial peptides

[0031] The selected sample set is from Cherkasov et al. [26] (see Table 4.21 for the sources of 101 peptides and their antibacterial potency values). This group of compounds is derived from the hybrid polypeptide CAMEL0 which is respectively fused with the C and N terminal sequences of natural cecropin and melittin, and is rich in leucine (L) residues. Experiments have proved that CAMEL-s has high activity against various Gram-positive and negative bacterial strains. However, its exact mode of action mechanism is still unclear, so it is worthy of further study on the factors and mechanism affecting its antibacterial activity. Each AMP molecular structure was characterized by VSTPV descriptor. In order to verify the external predictive ability of the model, first sort 101 antimicrobial peptide samples according to the Y value (antibacterial potency) from high to low, then select samples 3, 6, 9... as t...

Embodiment 2

[0044] Example 2 Quantitative structure-activity relationship characterization of antibacterial activity of bovine lactoferrin hydrolyzed peptide

[0045] Bovine Lactoferrin (LFB) is an iron-binding glycoprotein with a relative molecular mass of about 80kD, which mainly exists in various exocrine substances such as milk, tears, and saliva of mammals. LBF has a variety of unique biological functions such as enhancing iron transmission and absorption, broad-spectrum antibacterial properties, immune regulation, anti-oxidation, promoting the balance of intestinal flora, growth factors, anti-inflammation, anti-virus, and anti-cancer effects [27-29] . It has been applied to the development and prevention of human immunodeficiency virus (HIV), macrophage virus (CMV), human herpes simplex virus (HSV), hepatitis C virus (HCV), Helicobacter pylori and other drugs and immune enhancers and baby food [30] .

[0046] Three peptides are obtained after lactoferrin is hydrolyzed, and the ...

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Abstract

The invention discloses a method for representing activity relationships of antibacterial proteins or polypeptides. The method is characterized in that starting from 85 structural parameters and topological indexes of representation molecules, a characteristic descriptor comprising 166 amino acid systems is obtained through principle component analysis (PCA), namely a principle component score vector of structural and topological variable (VSTPV).. The VSTPV is applied to study of the quantitative structure-activity relationships (QSAR) of 101 antibacterial cationic peptides and 28 hydrolyzed bovine lactoferricins (BPPs), the models have better fitting and forecasting capabilities, and the cross validation related coefficients and related coefficients are above 0.70. The study shows that the VSTPV can well represent coded and uncoded amino acids and establish polypeptides with stronger forecasting capabilities and derivative QSAR models thereof.

Description

technical field [0001] The invention relates to the field of amino acid structure characterization. Background technique [0002] Many biological functions of proteins are also closely related to the amino acid sequence of specific peptide chains. Therefore, the study of quantitative structure-activity relationships of peptides is very important for the study of their mechanism of action in vivo, as well as the research and development of new peptide drugs. The study of protein structure and function is of great significance. Peptides have the characteristics of high activity, high selectivity and small side effects, and have become one of the hot spots in drug research. Non-coding amino acids are ubiquitous in nature and play an important role in drug design for amino acid structural modification or polypeptide modification. In recent years, with the development of peptidomimetics, it has been recognized that quantitative structure-activity relationship (QSAR) research on...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/24
Inventor 舒茂林治华张云茹路亚阔
Owner CHONGQING UNIV OF TECH
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