A de novo designed antifungal peptide and uses thereof

Abstract

This invention discloses a method for de novo design of antifungal peptides, the obtained peptides, and their applications. The method includes: S1 peptide library retrieval and amino acid preference analysis; S2 peptide design based on multiple parameters; S3 AI high-throughput screening of the peptide library to obtain candidate antifungal peptides. The amino acid sequences of the mentioned antifungal peptides are also disclosed in this invention as shown in SEQ ID Nos: 1 to 3. The antifungal peptides developed by this invention can specifically target and kill fungi such as Malassezia furfur without inhibiting the growth of other beneficial bacteria such as Propionibacterium acnes, thereby effectively regulating the skin surface microecological balance and maintaining skin health; solving the problem that current antimicrobial peptides, due to their broad-spectrum antibacterial properties, can disrupt the skin microecological balance and cause more serious skin diseases.

Description

Technical Field

[0001] This falls under the field of biotechnology and involves the de novo design of peptide molecules with specific antifungal activities using artificial intelligence and computational chemistry methods, as well as the prediction, screening, and application of peptides. Background Technology

[0002] Fungal skin diseases are a group of infectious diseases caused by pathogenic fungi infecting the skin, mucous membranes, hair, nails, and other skin appendages. When the skin becomes warm and moist, various fungi such as Malassezia, Trichophyton rubrum, Epidermophyton floccosum, Trichophyton verrucous, and Candida albicans will proliferate. Malassezia is the most common pathogenic fungus on animal skin, causing various skin problems such as tinea versicolor (pityriasis versicolor, dandruff), tinea pedis (tinea capitis, tinea manuum, tinea cruris), seborrheic dermatitis, and eczema. Symptoms include spots, scaling, itching, blisters, and erosion. Fungal skin problems often exhibit seasonal recurrence, are highly contagious, and prone to relapse, causing significant inconvenience to patients' normal work and life.

[0003] Current antifungal skin products include several chemical antifungal ingredients: ketoconazole, miconazole nitrate, terbinafine hydrochloride, piroctone olamine (OCT), climbazole, and zinc pyrithione. In addition, there are antimicrobial peptides derived from natural plant and animal proteins. While antifungal skin products offer several advantages in treating fungal skin infections, some issues remain. These products possess broad-spectrum antifungal properties, killing epidermal flora and directly disrupting the skin's microecology, thus causing imbalance. Skin microecological imbalance can lead to: 1. Other skin diseases, such as atopic dermatitis (AD), eczema, urticaria, and other allergic diseases. 2. Inflammation and tissue damage: In diseases like atopic dermatitis, the rampant growth of opportunistic pathogens such as Staphylococcus aureus not only evades the host's immune system to establish chronic infection but also damages the skin barrier and drives pathological inflammatory responses. 3. Reduced Skin Barrier Function: Imbalance in the skin microbiome leads to decreased skin resistance, making it prone to inflammation, infection, abnormal skin sensitivity, and recurring acne, all due to a weakened skin barrier. 4. Skin Aging: Imbalance in the skin microbiome causes skin inflammation, and inflammatory factors further induce cellular senescence, leading to skin aging. 5. Immune Activation or Suppression Issues: Disruption of the microbiome can lead to inappropriate immune activation or suppression, increasing the risk of allergic reactions, autoimmune diseases, and chronic inflammation. In summary, disruption of the skin microbiome has multifaceted effects on skin health, including the occurrence of skin diseases, reduced skin barrier function, skin inflammation, and immune problems. Therefore, maintaining the balance of the skin microbiome is crucial for skin health. There is an urgent need for a targeted antifungal product to specifically kill fungi and maintain the balance of the skin microbiome.

[0004] Among numerous antifungal products, antifungal peptides are becoming a future trend in antifungal treatment due to their unique antibacterial mechanisms and low likelihood of inducing drug resistance. The development of antifungal peptides generally involves discovering natural antimicrobial peptides and performing single-factor modification of natural antimicrobial peptides. Discovering natural antimicrobial peptides is a complex and time-consuming process, requiring significant human and material resources and presenting significant screening challenges. Antimicrobial peptides obtained through this method often exhibit poor targeting, low bioactivity, and a generalized broad-spectrum antibacterial effect, directly disrupting the skin's microecology by indiscriminately killing skin flora. While single-factor modification techniques can optimize the performance of antimicrobial peptides, their optimization has limitations. They cannot consider modifying multiple key parameters, and while improving bioactivity, single-factor modified antimicrobial peptides often come with increased cytotoxicity. These disadvantages limit the widespread application of these antimicrobial peptides in the pharmaceutical and food industries. Therefore, a de novo molecular design strategy is needed to overcome these difficulties and challenges, ultimately achieving sterilization while protecting the skin's microecological balance and maintaining overall health.

[0005] Existing technologies for discovering natural antimicrobial peptides are cumbersome and complex, requiring significant human and material resources, making screening difficult. Antimicrobial peptides obtained through this technology exhibit poor selectivity for fungi, possess broad-spectrum antimicrobial properties, and generally kill off skin flora, directly disrupting the skin's microecology and causing skin diseases. Furthermore, these antimicrobial peptides have relatively weak biological activity, requiring artificial modification to improve their efficiency. While single-factor modification techniques can optimize the performance of antimicrobial peptides, their optimization has limitations, failing to consider multiple key parameters for modification. Therefore, while single-factor modified antimicrobial peptides may improve biological activity, they often come with greater cytotoxicity. Summary of the Invention

[0006] This invention addresses the shortcomings of naturally sourced antimicrobial peptides. The technology aims to efficiently and rapidly design antifungal peptides de novo with AI assistance, resulting in highly targeted antifungal peptides that specifically kill harmful skin fungi such as Malassezia while exhibiting low inhibition of beneficial skin bacteria such as Propionibacterium acnes, thereby regulating the abundance of skin flora and achieving skin microecological stability. Furthermore, addressing the limitations of single-factor modification techniques for antimicrobial peptides, this invention overcomes the limitations of single-factor optimization by fully considering multiple key parameters during the de novo design process. The resulting antifungal peptides not only possess high targeting and high bioactivity but also exhibit lower cytotoxicity.

[0007] This invention first provides a method for de novo design of antifungal peptides, which includes the following steps: S1 peptide library retrieval and amino acid preference analysis: By comparing antifungal peptide libraries with antibacterial peptide libraries with AI-assisted analysis, it was found that aromatic amino acids (such as tryptophan W, phenylalanine F, and tyrosine Y) have a significant preference in antifungal peptides; basic amino acids (such as lysine K and arginine R) have a high frequency of occurrence in both types of peptides. S2 is based on multi-parameter peptide design: 1) Arrangement of hydrophobic and basic amino acids: Hydrophobic amino acids such as F and W are arranged alternately with basic amino acids in a ratio of 3:7 or 4:6, and the N-terminus is a basic amino acid K or R, in order to enhance the affinity and penetration of the negatively charged fungal cell membrane. 2) Targeting effect of aromatic amino acids: W, F, and Y aromatic amino acids are interspersed in the sequence to enhance the targeting of fungal cell wall β-glucan; 3) Precise distribution of aromatic amino acids: Ensure that there are at least two aromatic amino acids in the sequence, with an interval of one or more KR (RK, representing two consecutive amino acid KR or RK) between them, so as to maintain a certain distance between benzene rings in the peptide chain, effectively avoid intramolecular interactions, and instead promote intermolecular π-π stacking to form transmembrane polymers and enhance penetration. 4) Fine control of pI value: Adjust the position of amino acids of the same type to achieve a specific isoelectric point pI value, and optimize the stability and activity of peptides under different pH environments.

[0008] Specifically, the designed peptides are 8-peptides, 9-peptides, and 10-peptides; Further steps include the following: S3 and AI high-throughput screening of peptide libraries 1) The above peptide library was screened using AI algorithms, and the antibacterial strength and score of the above peptides were obtained by prediction and comparison; 2) Select peptides with a threshold <4 based on the AFP score predicted in step (1).

[0009] Furthermore, the present invention also provides a de novo designed antifungal peptide, the amino acid sequence of which is shown in any one of SEQ ID No: 1 to 12.

[0010] The present invention further provides a nucleic acid encoding the aforementioned polypeptide.

[0011] The present invention also provides the use of the described polypeptide in the preparation of antifungal products.

[0012] Specifically, the fungus is selected from Malassezia.

[0013] More specifically, the product is food, medicine, health product, or food additive, or health product additive.

[0014] This invention provides the use of the aforementioned polypeptide in the preparation of medicines for the prevention or treatment of skin diseases.

[0015] Specifically, the skin disease is selected from dandruff, folliculitis, and tinea versicolor. More preferably, the skin disease is caused by Malassezia.

[0016] This invention also provides the application of the aforementioned polypeptide in the preparation of skin care products.

[0017] Specifically, the skin care product is used to prevent or improve skin conditions selected from dandruff, folliculitis, or tinea versicolor.

[0018] More specifically, the skincare product is a cosmetic or cosmetic additive.

[0019] This invention presents a de novo antifungal peptide design technology, characterized by multi-factor optimization, improved targeting, enhanced antibacterial activity, and reduced cytotoxicity. It addresses the challenges of existing natural antifungal peptide discovery technologies, such as difficulties, low efficiency, and limitations in single-factor optimization for antifungal peptide modification design. The antifungal peptides developed based on this invention can specifically target and kill fungi such as Malassezia furfur, Candida albicans, Candida krusei, Cryptococcus neoformans, and Candida parapsilosis, without inhibiting the growth of other beneficial bacteria such as Propionibacterium acnes. This effectively regulates the skin's surface microecological balance and maintains skin health. It also solves the problem that current antimicrobial peptides, due to their broad-spectrum antibacterial properties, can disrupt the skin's microecological balance and cause more serious skin diseases. Detailed Implementation

[0020] The features and exemplary embodiments of various aspects of the present invention will now be described in detail. The specific embodiments listed herein are merely examples, and the present invention is not limited to the specific embodiments described below.

[0021] Example 1: Design and Synthesis of Antifungal Peptides

[0022] I. Designing and building a peptide library from scratch 1. Peptide Library Search and Amino Acid Preference Analysis: AI-assisted comparison of antifungal and antibacterial peptide libraries revealed a significant preference for aromatic amino acids (such as tryptophan W, phenylalanine F, and tyrosine Y) in antifungal peptides. Basic amino acids (such as lysine K and arginine R) showed high frequencies in both types of peptides. These findings provide crucial amino acid composition information for designing novel peptides.

[0023] 2. Peptide design based on multiple parameters: 1) Arrangement of hydrophobic and basic amino acids: Hydrophobic amino acids such as F and W are arranged alternately with basic amino acids in a ratio of 3:7 or 4:6, and the N-terminus is generally a basic amino acid K or R, in order to enhance the affinity and penetration of the negatively charged fungal cell membrane.

[0024] 2) Targeting effect of aromatic amino acids: Aromatic amino acids such as W, F, and Y are interspersed in the sequence to enhance the targeting of fungal cell wall β-glucan.

[0025] 3) Precise distribution of aromatic amino acids: Ensure that there are at least two aromatic amino acids in the sequence, with a spacing of one or more KR (RK) between them, so as to maintain a certain distance between benzene rings in the peptide chain, effectively avoid intramolecular interactions, and promote intermolecular π-π stacking to form transmembrane polymers and enhance penetration.

[0026] 4) Fine control of pI value: Adjust the position of amino acids of the same type according to the needs of different application scenarios to achieve a specific isoelectric point (pI value) and optimize the stability and activity of peptides under different pH environments.

[0027] Based on the above parameters, we designed a series of peptides of different lengths, including octapeptides, 9-peptides, and 10-peptides, and incorporated a certain proportion of aromatic amino acids and basic amino acids into the sequences to simulate the structural features of known effective peptides. A total of 9126 peptide sequences were obtained.

[0028] II. AI-based high-throughput screening of peptide libraries (1) The above peptide library was screened by AI algorithm, and the antibacterial strength and score of the above peptides were obtained by prediction and comparison.

[0029] (2) Based on the AFP score threshold predicted in step (1) <4, 12 peptide sequences were selected and the results are shown in Table 1.

[0030] Table 1. Related information about peptides

[0031] (3) Polypeptide synthesis Based on the 12 antifungal peptide sequences screened in step 1, they were synthesized using a solid-phase chemical synthesis method.

[0032] III. Antibacterial mechanism of the obtained antifungal peptides: 1) Membrane damage and potential disturbance: Peptides use their cationic charge and amphiphilic properties to bind to fungal cell membranes through electrostatic and hydrophobic interactions, causing membrane damage and potential disturbance, and reducing membrane integrity.

[0033] 2) Pore induction and increased permeability: Peptides induce the formation of cell membrane pores, increase membrane permeability, and cause leakage of fungal cell contents, thereby inhibiting fungal growth.

[0034] 3) Self-assembly and membrane damage: Specific amino acids in the mutate_3_K sequence, such as F, W, Y, and H, promote polypeptide self-assembly through π-π interactions, forming a network structure, which further aggravates membrane damage.

[0035] 4) Targeting and selectivity: Due to the specific arrangement of basic and hydrophobic amino acids in the polypeptide sequence and its targeting effect on β-glucan, mutate_3_K can specifically kill fungi while having little effect on bacteria such as Propionibacterium acnes, demonstrating its high selectivity.

[0036] Example 2: Qualitative Experiment on Targeted Antibacterial Activity

[0037] Experimental materials and reagents in the embodiments of this invention: Strains used in the experiment: Candida albicans, Candida krusei, Cryptococcus neoformans, Candida parapsilosis, Malassezia furfur, Propionibacterium acnes Main reagents and instruments: peptone, beef extract, NaCl, agar and other nutrients, and 96-well plates were purchased from Sangon Biotech (Shanghai) Co., Ltd.

[0038] Preparation of culture media and routine reagents used in the experiment: 1) MF medium: Weigh 10g peptone, 40g glucose, and 2g Tween 80, add about 500ml of distilled water to dissolve them completely, and then use a graduated cylinder to bring the volume to 1L to obtain liquid MF medium. For solid MF medium, add 4g agar to every 200ml of liquid medium.

[0039] 2) 2*MF liquid medium: Weigh 20g of peptone, 80g of glucose and 4g of Tween 80, add about 500ml of distilled water to dissolve them completely, and then use a graduated cylinder to make up to 1L to obtain 2*MF liquid medium. Sterilize at 115℃ for 20min and store in a sealed container.

[0040] 3) BHI medium: Weigh 38.5g of Qingdao Haibo Brain and Heart Infusion Broth and bring the volume to 1L using a graduated cylinder to obtain liquid BHI medium. For solid MRS medium, add 4g of agar to every 200ml of liquid medium.

[0041] 4) 2*BHI liquid culture medium: Weigh 77g of Qingdao Haibo brain and heart extract broth and make up to 1L with a graduated cylinder to obtain liquid BHI culture medium.

[0042] 5) YM medium: Weigh 5.0g of peptone, 3.0g of yeast extract, 3.0g of malt extract, and 10.0g of glucose, add them to 1000mL of distilled water, stir and heat until completely dissolved.

[0043] 6) 2*YM medium: Weigh 10.0g of peptone, 6.0g of yeast extract, 6.0g of malt extract, and 20.0g of glucose, add them to 1000mL of distilled water, stir and heat until completely dissolved.

[0044] Finally, all items must be sterilized at 115℃ / 121℃ for 20 minutes using an autoclave and then sealed for storage.

[0045] The experimental methods for qualitative and quantitative analysis of fungal and bacterial antibacterial activity in the embodiments of the present invention are as follows: (1) Preparation of polypeptide stock solution: Dissolve the target polypeptide in ddH2O at a concentration of 0.2 mg / ml for later use; (2) Culture the bacterial solution in MF / BHI / YM at 30℃ / 37℃ for later use; (3) Take the polypeptide stock solution and dilute it with buffer to different concentration gradients; (4) Add 150 μl of culture system to the microplate, including 75 μl polypeptide solution (0.1 mg / ml) + 75 μl bacterial solution; wherein the bacterial count in the 150 μl system is 5*10^5 CFU / ml, and at least 3 parallel groups are set for each polypeptide; (5) Incubate the microplate in an incubator at 30℃ and 900 rpm; (6) Take 3 μl of the above incubated liquid for plate spotting, and then place it in an incubator at 30℃ / 37℃ and inverted for 48 h; (7) Evaluate the growth of bacteria in the plate after the culture is completed. Compared with the negative control, the colony growth on the culture plates was compared, and the results are shown in Table 2. Qualitative evaluation was indicated by relevant symbols based on the antibacterial effect (- indicates no effect, + indicates weak antibacterial effect, ++ indicates moderate antibacterial effect, and +++ indicates strong antibacterial effect).

[0046] Table 2. Qualitative results of peptide antibacterial activity

[0047] Note: - indicates no effect, + indicates weak antibacterial effect, ++ indicates moderate antibacterial effect, and +++ indicates strong antibacterial effect.

[0048] The above results indicate that the screened antifungal peptides all have strong inhibitory effects on fungi, have targeted bactericidal effects on Malassezia, but have no bactericidal effect on Propionibacterium acnes.

[0049] Example 3 Targeted Antibacterial Quantitative Experiment

[0050] The experimental materials and reagents used in Example 3 are the same as those in Example 3.

[0051] Microplate coating method: (1) Prepare the peptide stock solution: Dissolve the target peptide in ddH2O to a concentration of 2 mg / ml for later use; (2) Culture Malassezia / Propionibacterium acnes using MF / BHI at 30℃ / 37℃ for later use; (3) Take the peptide stock solution and dilute it with buffer to different concentration gradients; (4) Add 150 μl of culture system to the microplate, including 75 μl of peptide solution (1 mg / ml) + 75 μl of bacterial culture; wherein the number of bacteria in the 150 μl system is 5*10^5. CFU / ml, each polypeptide has at least 3 parallel groups; (5) the microplate is incubated in an incubator at 30℃ and 900rpm; (6) take 100ul of the above incubated liquid, dilute it to the appropriate dilution factor, take 200ul for spreading, and then place it in an incubator at 30℃ / 37℃ and inverted for 48h; (7) after the culture is completed, calculate the number of bacteria on the plate, and calculate the inhibition rate according to the following formula: inhibition rate (%) = (number of colonies in the control group - number of colonies in the experimental group) / number of colonies in the control group * 100.

[0052] The antifungal peptides Mut-1-F, Mut-9-K, Mut-3-K, and Mut-3-F were selected and their antibacterial and antifungal effects against Malassezia and Propionibacterium acnes at different concentrations were determined. The results are shown in Tables 3 and 4.

[0053] Table 3. Quantitative detection results of antifungal peptides against Propionibacterium acnes

[0054] Table 4. Quantitative detection results of antifungal peptides against Malassezia

[0055] The above results indicate that the antifungal peptides have significant antibacterial and bacteriostatic properties against Malassezia and weak bacteriostatic effects against Propionibacterium acnes: the MIC difference between the selected antifungal peptides and Malassezia and Propionibacterium acnes is 8-76 times.

[0056] Example 4: Verification of the non-toxic and non-irritating nature of the antifungal peptide using a cell model. Preparation of relevant reagents:

[0057] 1) Cells: Human keratinocytes (HaCaT) 2) Preparation of antifungal peptide stock solution: Using sterile distilled water as a solvent, prepare an antifungal peptide stock solution with a concentration of 3 mg / ml, then aliquot and store at -20℃. This invention is derived from any of the following amino acid sequences of polypeptides: SEQ.ID NO:1-SEQ.ID NO:12.

[0058] 3) Cell lysis buffer: 1M NaOH: Weigh 4.0g of sodium hydroxide solid and make up to 100mL of sodium hydroxide solution.

[0059] Experimental plan: Cytotoxicity detection

[0060] HaCaT cells were seeded in 96-well plates at a density of 1.0 × 10⁵ cells / well. After 24 hours of stable cell culture, different concentrations of antifungal peptides SEQ.ID NO:1-SEQ.ID NO:12 (5 μM, 10 μM, 20 μM, 50 μM, 100 μM, 200 μM) were added to the cells. The cells were then cultured at 37°C and 5% CO₂ for 24 hours. The culture medium was then discarded, and 90 μL of basal medium and 10 μL of CCK8 were added to each well. The mixture was incubated at 37°C for 40 minutes, and the absorbance was measured at 450 nm after incubation. Cell viability (%) = (OD of experimental group - OD of blank well) / (OD of blank control group - OD of blank well) * 100%. Cell viability <70% indicates that the antifungal peptides are cytotoxic.

[0061] Experimental results:

[0062] The cytotoxicity test results of the antifungal peptides are shown in Table 5. The results show that the antifungal peptides (SEQ.ID NO:1-SEQ.ID NO:12) are non-toxic to HaCaT cells within the tested concentration range.

[0063] Table 5. Results of antifungal peptide cytotoxicity

[0064] In this context, + indicates cytotoxicity, and - indicates no cytotoxicity.

Claims

1. A method of de novo design of an antifungal polypeptide, characterized in that, Includes the following steps: S1 peptide library retrieval and amino acid preference analysis: By comparing antifungal peptide libraries with antibacterial peptide libraries with AI-assisted analysis, it was found that aromatic amino acids (such as tryptophan W, phenylalanine F, and tyrosine Y) have a significant preference in antifungal peptides; basic amino acids (such as lysine K and arginine R) have a high frequency of occurrence in both types of peptides. S2 is based on multi-parameter peptide design: 1) Arrangement of hydrophobic and basic amino acids: Hydrophobic amino acids such as F and W are arranged alternately with basic amino acids in a ratio of 3:7 or 4:6, and the N-terminus is a basic amino acid K or R, in order to enhance the affinity and penetration of the negatively charged fungal cell membrane. 2) Targeting effect of aromatic amino acids: W, F, and Y aromatic amino acids are interspersed in the sequence to enhance the targeting of fungal cell wall β-glucan; 3) Precise distribution of aromatic amino acids: Ensure that there are at least two aromatic amino acids in the sequence, with an interval of one or more KR (RK) between them, so as to maintain a certain distance between benzene rings in the peptide chain, effectively avoid intramolecular interactions, and promote intermolecular π-π stacking to form transmembrane polymers and enhance penetration. 4) Fine control of pI value: Adjust the position of amino acids of the same type to achieve a specific isoelectric point pI value, and optimize the stability and activity of peptides under different pH environments.

2. The method for de novo design of antifungal peptides as described in claim 1, characterized in that, The designed peptides are 8-peptide, 9-peptide, and 10-peptide; Further steps include the following: S3 and AI high-throughput screening of peptide libraries 1) The above peptide library was screened using AI algorithms, and the antibacterial strength and score of the above peptides were obtained by prediction and comparison; 2) Select peptides with a threshold <4 based on the AFP score predicted in step (1).

3. A de novo designed antifungal peptide, characterized in that, Its amino acid sequence is shown in any of SEQ ID No: 1 to 12.

4. A nucleic acid encoding the polypeptide as described in claim 3.

5. The application of the polypeptide as described in claim 3 in the preparation of antifungal products; Preferably, the fungus is selected from Malassezia; The product in question is food, medicine, health product, or food additive or health product additive.

6. The use of the polypeptide as described in claim 1 in the preparation of a medicament for the prevention or treatment of skin diseases; The skin diseases mentioned are selected from dandruff, folliculitis, and tinea versicolor.

7. The application as described in claim 6, characterized in that, The skin diseases mentioned are caused by Malassezia, Candida albicans, Candida krusei, Cryptococcus neoformans, and Candida parapsilosis.

8. The application of the polypeptide as described in claim 3 in the preparation of skin care products.

9. The application as described in claim 8, characterized in that, The skin care products are used to prevent or improve skin conditions selected from dandruff, folliculitis, or tinea versicolor.

10. The application as described in claim 9, characterized in that, The skincare product in question is a cosmetic or a cosmetic additive.

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