Artificial intelligence designed antibacterial peptide and application thereof

Abstract

The invention discloses an artificial intelligence designed antibacterial peptide and application thereof, and belongs to the field of biological medicine. According to the invention, seven times of mutation are carried out step by step based on a random initial sequence DGWTMVKARYIERFMRGLRGFHIKAA through an independently researched and developed artificial intelligence model, so that a series of seven antibacterial peptides are obtained. Tests prove that the seven brand-new antibacterial peptides can effectively inhibit the growth of bacteria, especially gram-positive bacteria staphylococcus aureus and bacillus subtilis, one of the seven brand-new antibacterial peptides has an excellent inhibition effect on gram-negative bacteria and gram-positive bacteria, and the average minimum inhibitory concentration is less than 3 mu M. The antibacterial peptides can provide a basis and a foundation for developing a new generation of antibacterial drugs and antibacterial products.

Description

Technical Field

[0001] The present invention relates to antimicrobial peptides designed by artificial intelligence and applications thereof, and specifically to antimicrobial peptides designed by artificial intelligence and applications thereof in drug preparation, and belongs to the field of biomedicine. Background Art

[0002] In the "post-antibiotic era", more than 700,000 people die each year from drug-resistant bacterial infections, and this number is growing at a rate of 100,000 people per year. Antimicrobial peptides are a class of short peptides that have a broad-spectrum inhibitory effect on bacteria and other pathogens. They mainly exert their antibacterial effects by destroying bacterial cell membranes. Compared with small molecule antibiotics, they have the characteristics of rapid bactericidal activity and are not easy to cause pathogen resistance. Although the number of antimicrobial peptides included in the existing database has reached 30,000, compared with the theoretically vast sequence space, known antimicrobial peptides are still very rare, and not all of them have high antibacterial activity. Summary of the invention

[0003] In order to efficiently obtain more antimicrobial peptides with higher antibacterial activity, the present invention uses an independently developed artificial intelligence model to gradually perform 7 mutations based on the random starting sequence DGWTMVKARYIERFMRGLRGFHIKAA (SEQ ID No: 1) to obtain a series of 7 antimicrobial peptides.

[0004] The names and sequences of a series of antimicrobial peptides provided by the present invention are as follows:

[0005] Perceptide24-1:DGWTMVKARYIKRFMRGLRGFHIKAA (SEQ ID No: 2)

[0006] Perceptide24-2: RGWTMVKARYIKRFMRGLRGFHIKAA (SEQ ID No: 3)

[0007] Perceptide24-4:RGWFMVKARYIKRFMRGLRGFHIKAA (SEQ ID No: 4)

[0008] Perceptide24-5: RGWFKVKARYIKRFMRGLRGFHIKAA (SEQ ID No: 5)

[0009] Perceptide24-6: RGWFKVKMRYIKRFMRGLRGFHIKAA (SEQ ID No: 6)

[0010] Perceptide24-7: RGWFKVKERYIKRFMRGLRGFHIKAA (SEQ ID No: 7)

[0011] Perceptide24: RGWFKVKRRYIKRFMRGLRGFHIKAA (SEQ ID No: 8)

[0012] These antimicrobial peptides can be synthesized by chemical methods such as peptide solid phase synthesis and used in antimicrobial drugs and other antimicrobial products (such as disinfectants, detergents, and feed additives).

[0013] The 7 new antimicrobial peptides provided by the present invention can effectively inhibit bacterial growth, especially Gram-positive bacteria Staphylococcus aureus and Bacillus subtilis. Among them, Perceptide24 has excellent inhibitory effects on both Gram-negative and Gram-positive bacteria, with an average minimum inhibitory concentration of less than 3 μM. These antimicrobial peptides can provide a basis and foundation for the development of a new generation of antimicrobial drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The mutation process of 7 antimicrobial peptides was obtained for the present invention. DETAILED DESCRIPTION

[0015] The present invention is further described below by way of examples, but it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.

[0016] Example 1 Source and physicochemical properties of antimicrobial peptides

[0017] The present invention uses an independently developed artificial intelligence model to gradually perform 7 mutations based on the random starting sequence DGWTMVKARYIERFMRGLRGFHIKAA to obtain 7 antimicrobial peptides. The mutation process is as follows Figure 1 As shown, the sequence wheel diagram of each antimicrobial peptide was drawn using modlAMP. In the sequence wheel diagram, white text on a black background is non-polar amino acids, and black text on a white background is polar amino acids. The artificial intelligence model gradually introduced E12K, D1R, T4F, M5K, A8M, M8E, and E8R mutations into the starting sequence. The introduction of arginine (R) and lysine (K) increased the net charge of the antimicrobial peptide, which is consistent with the characteristics of the antimicrobial peptide being mostly positively charged. Table 1 shows the physicochemical properties of each antimicrobial peptide, including molecular weight, net charge, isoelectric point, proportion of aromatic amino acids, hydrophobic moment, and proportion of hydrophobic amino acids. With the introduction of mutations, the hydrophobic moment of the antimicrobial peptide gradually increased, showing a more amphiphilic characteristic.

[0018] Table 1. Physicochemical properties of 7 antimicrobial peptides

[0019]

[0020] Example 2 Determination of Minimum Inhibitory Concentration of Antimicrobial Peptides

[0021] The bacterial species used in the minimum inhibitory concentration determination experiment include two standard strains of Gram-negative bacteria and two standard strains of Gram-positive bacteria, namely Escherichia coli ATCC25922, Pseudomonas aeruginosa PAO1, Staphylococcus aureus ATCC6538, and Bacillus subtilis ATCC6633.

[0022] The minimum inhibitory concentration of antimicrobial peptides was determined using the Hancock broth microdilution method. The experimental steps are as follows.

[0023] (1) Preparation of bacterial solution. Resuscitate the freeze-dried strains of the four standard strains, activate them by overnight culture, and streak them onto LB plates without resistance (Haibo Biotech, #HB0129-2). Pick four single colonies with similar morphology and add them to 5 mL LB medium (Haibo Biotech, #HB0218). Culture them in a shaker at 37°C at 220 rpm for about 3 hours, then dilute them to a concentration of OD 625 The values ​​are in the range of 0.08-0.13.

[0024] (2) Preparation of antimicrobial peptide solution. The antimicrobial peptide powder was synthesized by Wuhan Dangang Biotechnology Co., Ltd. through solid phase chemical synthesis. The molecular weight was correct by mass spectrometry. The antimicrobial peptide samples were purified by high performance liquid chromatography, and the purity was above 95%. 0.1 mg of antimicrobial peptide powder was dissolved in sterile PBS buffer (pH 7.4) to prepare an antimicrobial peptide stock solution with a concentration of 512 μM.

[0025] (3) Antibacterial test. A sterilized polypropylene 96-well culture plate (Greiner, #655201) was used for the assay. Three rows of parallel controls were set for each antimicrobial peptide. Columns 1-10 were the bacterial solution and the antimicrobial peptide solution after gradient dilution, column 11 was the growth control, i.e., no antimicrobial peptide solution was added, and column 12 was the sterile control, i.e., only the culture medium was added. First, 100 μL of LB culture medium was added to each of columns 1-11, and 200 μL of LB culture medium was added to column 12. After the antimicrobial peptide stock solution was diluted 8 times with LB medium, 100 μL was added to each well in the first column, 100 μL was transferred to the second column and mixed, and 100 μL was transferred from the second column to the third column and mixed. This step was repeated in sequence to complete the double gradient dilution (concentrations were 128, 64, 32, 16, 8, 4, 2, 1, 0.5, and 0.25 μM, respectively). After mixing in the tenth column, 100 μL was discarded. 400 μL of the adjusted bacterial solution was diluted 100 times in 39.6 mL LB medium, and 100 μL of the bacterial solution was added to each well in columns 1-11. The bacterial solution used as a growth control was diluted 1:100 again, and 100 μL was taken to coat the non-antibiotic LB plate for checking the bacterial growth density. The 96-well culture plate and the plate were placed in a 37°C incubator and cultured for 16 hours.

[0026] (4) Observation of results. The bacterial growth in each well of the cell culture plate was directly observed. The lowest antimicrobial peptide solution concentration value at which no obvious bacterial growth was observed by naked eye was the minimum inhibitory concentration of the antimicrobial peptide under this condition. The results are shown in Table 2. The random starting sequence had no antibacterial activity against the four strains. With the introduction of mutations, the antibacterial activity of the antimicrobial peptides increased overall.

[0027] Table 2. Minimum inhibitory concentration of 7 antimicrobial peptides against four strains (unit: μM)

[0028]

Claims

1. An antimicrobial peptide, which is a series of antimicrobial peptides obtained by stepwise mutation based on a random starting sequence DGWTMVKARYIERFMRGLRGFHIKAA, characterized in that: The antimicrobial peptide is selected from one or more antimicrobial peptides having the following amino acid sequences: Perceptide24-1:DGWTMVKARYIKRFMRGLRGFHIKAA; Perceptide24-2:RGWTMVKARYIKRFMRGLRGFHIKAA; Perceptide24-4:RGWFMVKARYIKRFMRGLRGFHIKAA; Perceptide24-5:RGWFKVKARYIKRFMRGLRGFHIKAA; Perceptide24-6:RGWFKVKMRYIKRFMRGLRGFHIKAA; Perceptide24-7:RGWFKVKERYIKRFMRGLRGFHIKAA; Perceptide24: RGWFKVKRRYIKRFMRGLRGFHIKAA.

2. Use of the antimicrobial peptide according to claim 1 in the preparation of antimicrobial drugs.

3. The use according to claim 2, characterized in that The bacteria targeted by the antibacterial drug include Gram-positive bacteria and Gram-negative bacteria.

4. The use according to claim 3, characterized in that The bacteria targeted by the antibacterial drug are one or more of the following bacteria: Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Bacillus subtilis.

5. The use according to claim 2, characterized in that The effective concentration of the antimicrobial peptide in the antimicrobial drug is greater than or equal to 0.5 μM.

6. The use according to claim 5, characterized in that The antimicrobial peptide is Perceptide 24, and its effective concentration in the antimicrobial drug is greater than or equal to 3 μM.

7. An antibacterial drug, characterized in that: The invention comprises the antimicrobial peptide as claimed in claim 1.

8. The antibacterial drug according to claim 7, characterized in that The antibacterial drug contains the antibacterial peptide Perceptide 24 with an effective concentration greater than or equal to 3 μM.

9. Use of the antimicrobial peptide according to claim 1 in the preparation of antimicrobial products.

10. The use according to claim 8, characterized in that The antimicrobial product is a disinfectant, a detergent or a feed additive.

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