Marine microorganism-derived antibacterial peptide as well as screening method and application thereof
By using bioinformatics and deep learning models to screen marine microbial antimicrobial peptide M7-2, the problems of low activity and high hemolytic activity of existing antimicrobial peptides have been solved, enabling the development of highly efficient and low-cost antimicrobial drugs.
Patent Information
- Application Number
- CN202610051167.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-15
- Publication Date
- 2026-05-08
AI Technical Summary
Existing antimicrobial peptides have limited antibacterial activity and high hemolytic activity, which limits their application in actual treatment. Furthermore, manual screening is costly and inefficient.
Bioinformatics tools and deep learning models were used to screen antimicrobial peptides derived from marine microorganisms. Antimicrobial peptide M7-2 was prepared by solid-phase synthesis and then capped with N-terminal acetyl and C-terminal amino groups. By combining multi-model synergistic validation and database construction, candidate peptides with high antibacterial activity and low hemolytic activity were screened.
The antimicrobial peptide M7-2, which effectively inhibits a variety of Gram-positive and Gram-negative pathogens, was screened out in a short time and at low cost. It has broad-spectrum antibacterial activity and good safety profile, providing a basis for a new generation of antimicrobial drugs.
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Figure CN121991167A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of polypeptide technology, and in particular to an antimicrobial peptide derived from marine microorganisms, its screening method, and its application. Background Technology
[0002] The global spread of drug-resistant pathogens has drawn widespread attention from the medical and scientific communities. The widespread use of multiple antibiotics has led to bacteria evolving from resistance to single antibiotics to multidrug resistance, and even pan-drug resistance. Antimicrobial peptides primarily exert their antibacterial effects by disrupting bacterial cell membranes, possessing broad-spectrum antibacterial activity and low resistance rates, making them a promising alternative to traditional antibiotics. The emergence and spread of antimicrobial resistance (AMR) is a global public health crisis, placing a heavy burden on healthcare systems and resulting in high mortality rates and exorbitant economic costs. Traditional antibiotics have long development cycles and develop resistance rapidly, thus necessitating novel antimicrobial strategies. Peptide antimicrobial drugs, especially antimicrobial peptides (AMPs), have become a current research hotspot due to their high antimicrobial activity, low resistance rates, and broad biological activity.
[0003] Currently, the antibacterial activity of natural antimicrobial peptides is relatively limited. In actual drug development, antimicrobial peptides with higher activity and stronger targeting are needed to exert their antibacterial effects. The ocean, as the most biodiverse ecosystem on Earth, nurtures a large number of uniquely structured and functionally diverse bioactive substances. Among them, marine-derived antimicrobial peptides have become a research hotspot in the biomedical field in recent years due to their excellent antimicrobial properties and unique mechanisms of action. Compared with traditional antibiotics, marine-derived antimicrobial peptides have broad-spectrum antimicrobial activity, effectively inhibiting not only Gram-positive and Gram-negative bacteria, but also exhibiting significant inhibitory effects on fungi, viruses, and certain tumor cells. Furthermore, marine antimicrobial peptides also possess characteristics such as small molecular weight, good thermal stability, high water solubility, and excellent biocompatibility, demonstrating enormous application potential in clinical infection treatment, food preservation, and aquaculture disease prevention and control.
[0004] Meanwhile, with the rise of artificial intelligence, deep learning models can quickly learn from a large number of known drug samples. Generative models, once trained, can directly sample and produce entirely new drug molecules, while discriminative models can identify new potential drug candidates by predicting the properties of these molecules, effectively accelerating the drug design process. AMPs databases and predictive models have begun to emerge, and utilizing bioinformatics resources and computational tools to assist in peptide design and predict peptide activity to screen for optimal candidate peptides is gradually becoming a trend. However, the widespread application of antimicrobial peptides still faces many challenges, mainly due to their low antibacterial activity and high hemolytic activity, which limit their widespread use in actual treatment. Summary of the Invention
[0005] To address the shortcomings of existing technologies, the first objective of this invention is to provide an antimicrobial peptide derived from marine microorganisms that can effectively inhibit a variety of Gram-positive and Gram-negative pathogens, exhibiting broad-spectrum antibacterial activity and safe use.
[0006] The second objective of this invention is to provide a method for screening antimicrobial peptides derived from marine microorganisms, which solves the problems of high cost, low antimicrobial efficiency, and high hemolysis associated with existing manual screening methods for antimicrobial peptides.
[0007] The third objective of this invention is to provide an application of an antimicrobial peptide derived from marine microorganisms, which can effectively inhibit a variety of Gram-positive and Gram-negative pathogens, and has broad-spectrum antibacterial activity and safe use.
[0008] To achieve the first objective mentioned above, the present invention provides the following technical solution:
[0009] An antimicrobial peptide derived from marine microorganisms, selected from compounds represented by formula (I), or from stereoisomers, prodrugs, crystal forms, pharmaceutically acceptable salts, pharmaceutically acceptable esters, or pharmaceutically acceptable solvates of said compounds;
[0010] .
[0011] Specifically, in the "antimicrobial peptide" of the present invention, the sequence is Ac-RWWCRWR-NH2. It is synthesized by solid-phase synthesis and reacted with acetic anhydride and pyridine to perform N-terminal acetyl capping and C-terminal amino capping (amidation modification). The obtained polypeptide is identified by mass spectrometry and high performance liquid chromatography and named antimicrobial peptide M7-2 with a molecular weight of 1189.42.
[0012] The specific meaning of "stereoisomer" is that when it is specifically designated by chemical name as (R)- or (S)- isomer, it should be understood as having a predominant configuration of (R)- or (S)- isomer, respectively; any asymmetric carbon atom may exist in (R)-, (S)- or (R, S)- configurations, preferably in (R)- or (S)- configuration;
[0013] The specific meaning of "crystal form" refers to the crystal structure of a substance. During crystallization, various factors can affect the bonding patterns within or between molecules, causing molecules or atoms to arrange themselves differently in the crystal lattice, thus forming different crystal structures. The compounds of this invention can exist in one crystal structure or multiple crystal structures, i.e., they have "polymorphism". The compounds of this invention can exist in different crystal forms.
[0014] The term "pharmaceutically acceptable salt" specifically refers to a salt formed by an acidic functional group (e.g., a carboxyl group) present in the compounds provided by the present invention and a suitable inorganic or organic cation (base), or a salt formed by a basic functional group (e.g., an amino group) present in the compounds provided by the present invention and a suitable inorganic or organic anion (acid); non-limiting examples include quaternary ammonium salts, acetates, adipic acid salts, camphorates, alginates, citrates, aspartate salts, benzoates, benzenesulfonates, maleates, and hydrogen sulfates. Butyrate, camphor sulfonate, diglucuronate, glyceryl phosphate, hemisulfate, heptaate, hexanoate, fumarate, hydrochloride, hydrobromide, 2-hydroxyethanesulfonate (isothiosulfate), lactate, methanesulfonate, hydroiodate, nicotinate, 2-naphthalenesulfonate, oxalate, palmitate, pectate, persulfate, picrate, neopentanoate, propionate, succinate, tartrate, thiocyanate, phosphate, 3-phenylpropionate, glutamate, bicarbonate, p-toluenesulfonate, and undecanoate;
[0015] The quaternary ammonium salt is composed of C1-C6 alkyl halides, dialkyl sulfate esters, and C6 alkyl halides. 12 ~C 18 Alkyl halides and C6~C 10 One of the aryl halides is obtained by quaternization; the alkyl group of the C1-C6 alkyl halide is one of methyl, ethyl, n-propyl, isopropyl, n-butyl, sec-butyl, tert-butyl, and isobutyl, and the halide is one of chloride, bromide, and iodide; the dialkyl sulfate is one of dimethyl sulfate, diethyl sulfate, dibutyl sulfate, and dipentyl sulfate; the C 12 ~C 18 The alkyl group of the alkyl halide is one of dodecyl, decyl, tetradecyl, and octadecyl, and the halide is one of chloride, bromide, and iodide; the C6~C 10 The aryl halide is one of benzyl bromide and phenethyl bromide;
[0016] Meanwhile, the acid in the salt is one of hydrochloric acid, hydrobromic acid, sulfuric acid, phosphoric acid, oxalic acid, maleic acid, succinic acid, and citric acid;
[0017] The term "pharmaceutically acceptable ester" specifically refers to an ester formed by the carboxyl group present in the compound provided by the present invention and a suitable alcohol; non-limiting examples include formate, acetate, propionate, butyrate, acrylate, ethyl succinate, stearic acid ester, or palmitate; the ester can undergo hydrolysis in the presence of acid or base to produce the corresponding acid or alcohol.
[0018] The specific meaning of "pharmaceutically acceptable solvate" refers to a compound existing in combination with a solvent molecule; the terms "solvent" and "solvent" are used interchangeably. This combination may include a stoichiometric amount of a solvent, such as a monohydrate or dihydrate, or may include any amount of water; for example, methanol or ethanol can form an "alcohol," which may be stoichiometric or non-stoichiometric. As used herein, the term "solvent" refers to a solid form, that is, a compound in solution of a solvent that, while solvable, is not a solvate as used herein.
[0019] To achieve the second objective mentioned above, the present invention provides the following technical solution:
[0020] A method for screening antimicrobial peptides derived from marine microorganisms includes the following steps: First, based on the genomic resources of *Bacillus* genus from the marine environment, short open reading frame (smORF) sequences are obtained to ensure that the target sequence conforms to the core structural features and length range of the antimicrobial peptide precursor molecule. Then, through sequence redundancy optimization, multi-model collaborative validation, and database construction, non-redundant antimicrobial peptide sequences are obtained. Then, the polypeptide RWWCRWR is synthesized using a solid-phase synthesis method and reacted with acetic anhydride and pyridine to perform N-terminal acetyl capping and C-terminal amino capping to obtain the antimicrobial peptide Ac-RWWCRWR-NH2 shown in formula (I).
[0021] Furthermore, in the process of obtaining short open reading frame sequences, the bioinformatics tool EMBOSS was used to perform a whole-genome scan of the *Bacillus* genus resources, specifically identifying and predicting short open reading frame sequences. The screening criteria were set as a sequence length of 18-150 base pairs to ensure that the target sequence conforms to the core structural characteristics and length range of antimicrobial peptide precursor molecules.
[0022] Furthermore, during the sequence redundancy optimization process, the predicted short open reading frame sequences are batch-merged, and the Seqkit tool is used to perform efficient sequence deduplication. By accurately comparing and filtering, 100% similar redundant sequences are removed, effectively avoiding resource consumption and result deviations caused by repeated analysis, and ensuring the efficiency and accuracy of subsequent predictive analysis.
[0023] Furthermore, during the multi-model collaborative validation process, the redundancy-removed smORF sequence is input into eight deep learning prediction models from three open-source projects: c_AMPs-prediction, SMEP, and AMP-potency-prediction-EvoGradient (corresponding open-source repository addresses: https: / / github.com / mayuefine / c_AMPs-prediction, https: / / github.com / BioGavin / SMEP, and https: / / github.com / MicroResearchLab / AMP-potency-prediction-EvoGradient, respectively). Collaborative prediction and cross-validation of antimicrobial activity are conducted, with strict judgment criteria set. Only when all eight deep learning prediction models unanimously determine that the sequence possesses antimicrobial activity can it be included in the candidate antimicrobial peptide category. Multi-model cross-validation significantly improves the reliability and credibility of the prediction results.
[0024] Furthermore, during the database construction process, non-redundant candidate antimicrobial peptides were finally obtained through screening, and a comprehensive database of antimicrobial peptides from the genus Idiomarina was constructed. Based on core indicators such as multi-model prediction confidence and sequence physicochemical properties, a comprehensive evaluation was conducted, and the antimicrobial peptide Ac-RWWCRWR-NH2 was finally selected.
[0025] To achieve the third objective mentioned above, the present invention provides the following technical solution:
[0026] Application of an antimicrobial peptide derived from marine microorganisms in the preparation of antimicrobial drugs.
[0027] Specifically, in the "medicine" of this invention,
[0028] The drug can be introduced into the body, such as into muscles, intradermal tissues, subcutaneous tissues, veins, or mucous membranes, through injection, spray, nasal drops, eye drops, penetration, absorption, or physical or chemical mediated methods; or it can be introduced into the body after being mixed with or encapsulated by other substances.
[0029] When necessary, one or more pharmaceutically acceptable carriers may be added to the drug. These carriers include diluents, excipients, fillers, binders, wetting agents, disintegrants, absorption enhancers, surfactants, adsorbents, lubricants, etc., commonly used in the pharmaceutical field. The drug can be formulated into various forms such as injections, suspensions, powders, tablets, and granules. All of the above dosage forms can be prepared according to conventional methods in the pharmaceutical field.
[0030] Furthermore, the bacteria in the antibacterial drug are Escherichia coli, Vibrio parahaemolyticus, Acinetobacter baumannii, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, and Bacillus anthracis, and the minimum inhibitory concentrations against Escherichia coli, Vibrio parahaemolyticus, Acinetobacter baumannii, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, and Bacillus anthracis are 8 μM, 16 μM, 16 μM, 32 μM, 4 μM, 16 μM, and 32 μM, respectively.
[0031] Furthermore, the active ingredient of the antibacterial drug is a compound represented by formula (I) above, or selected from stereoisomers, prodrugs, crystal forms, pharmaceutically acceptable salts, pharmaceutically acceptable esters, or pharmaceutically acceptable solvates of the compound.
[0032] In summary, the beneficial technical effects of this invention are as follows: This invention utilizes bioinformatics resources and computational tools to assist in peptide design and database prediction models to predict peptide activity, enabling the screening of optimal candidate peptide sequences under short-term and low-cost conditions. The antimicrobial peptide M7-2 of this invention has a stable structure. Antimicrobial, hemolytic, and time-dependent killing activities of the synthesized antimicrobial peptide were tested, revealing that antimicrobial peptide M7-2 exhibits high inhibitory activity against *Escherichia coli*, *Vibrio parahaemolyticus*, *Staphylococcus aureus*, *Bacillus subtilis*, *Bacillus anthracis*, *Acinetobacter baumannii*, and *Pseudomonas aeruginosa*, and possesses extremely low hemolytic activity. Therefore, antimicrobial peptide M7-2 is an antimicrobial peptide with high application value, providing a basis for the development of next-generation antimicrobial drugs. Attached Figure Description
[0033] Figure 1 This is a flowchart of the method provided in Embodiment 1 of the present invention.
[0034] Figure 2 This is a schematic diagram of the three-dimensional structure of the antimicrobial peptide obtained in Example 1 of the present invention.
[0035] Figure 3 This is a high-performance liquid chromatogram of the antimicrobial peptide prepared in Example 1 of the present invention.
[0036] Figure 4 This is the mass spectrum of the antimicrobial peptide prepared in Example 1 of this invention.
[0037] Figure 5 This is a graph showing the MIC determination results of the antimicrobial peptide of Example 3 of the present invention against 7 pathogens.
[0038] Figure 6 This is a time-kill curve of the antimicrobial peptide of Example 3 of the present invention co-incubated with Escherichia coli MG1655.
[0039] Figure 7 This is a graph showing the hemolytic activity assay results of the antimicrobial peptide in Example 3 of the present invention. Detailed Implementation
[0040] To make the technical means, creative features, objectives and effects of this invention clearer and easier to understand, the invention will be further described below in conjunction with the accompanying drawings and specific embodiments.
[0041] Example 1: A method for screening antimicrobial peptides derived from marine microorganisms, as disclosed in this invention, includes the following steps:
[0042] S1 first systematically collected 66 high-quality assembled genomes of *Idiomarina* from global marine environments. (Note: *Idiomarina* is a Gram-negative bacterium endemic to the ocean, belonging to the family Alternariaceae. It is widely distributed in various marine habitats such as nearshore sediments, deep waters, and polar oceans, and possesses unique physiological characteristics such as salt tolerance and tolerance to extreme environments. Its genome contains rich potential for encoding novel bioactive substances.) Based on the *Idiomarina* genome resources from the marine environment, the bioinformatics tool EMBOSS was used to perform a whole-genome scan of the *Idiomarina* genome resources, specifically identifying and predicting short open reading frame (smORF) sequences. The screening criteria were set at a sequence length of 18-150 base pairs to ensure that the target sequences conformed to the core structural characteristics and length range of antimicrobial peptide precursor molecules.
[0043] S2 sequence redundancy optimization involves batch merging of 1,510,092 short open reading frame sequences obtained from prediction, and using the Seqkit tool for efficient sequence deduplication. By accurately comparing and filtering, 100% similar redundant sequences are removed, effectively avoiding resource consumption and result bias caused by repeated analysis, and ensuring the efficiency and accuracy of subsequent prediction analysis.
[0044] S3 multi-model collaborative validation inputs the redundancy-removed smORF sequence into eight deep learning prediction models from three open-source projects: c_AMPs-prediction, SMEP, and AMP-potency-prediction-EvoGradient (corresponding open-source repository addresses: https: / / github.com / mayuefine / c_AMPs-prediction, https: / / github.com / BioGavin / SMEP, and https: / / github.com / MicroResearchLab / AMP-potency-prediction-EvoGradient, respectively). This allows for collaborative prediction and cross-validation of antimicrobial activity. Strict criteria are set; only when all eight deep learning prediction models unanimously determine that the sequence possesses antimicrobial activity can it be included in the candidate antimicrobial peptide category. Multi-model cross-validation significantly improves the reliability and credibility of the prediction results.
[0045] The S4 database was constructed, and after screening, 32,007 non-redundant candidate antimicrobial peptides were finally obtained. A comprehensive database of antimicrobial peptides from the genus Idiomarina was constructed. Based on the multi-model prediction confidence, sequence physicochemical properties and other core indicators, a comprehensive evaluation was carried out, and the antimicrobial peptide Ac-RWWCRWR-NH2 was finally selected.
[0046] S5 synthesized the peptide RWWCRWR using a solid-phase synthesis method through a commercial company, and reacted it with acetic anhydride and pyridine to achieve N-terminal acetyl capping and C-terminal amino capping, obtaining the antimicrobial peptide Ac-RWWCRWR-NH2 shown in formula (I). The purity of the synthesized antimicrobial peptide is over 95%, and the molecular weight of the peptides has been identified by mass spectrometry, making them suitable for various biological detections.
[0047] Example 2: An antimicrobial peptide derived from marine microorganisms disclosed in this invention is selected from compounds represented by formula (I), or from stereoisomers, prodrugs, crystal forms, pharmaceutically acceptable salts, pharmaceutically acceptable esters, or pharmaceutically acceptable solvates of the compounds.
[0048] .
[0049] Example 3: This invention discloses the application of an antimicrobial peptide derived from marine microorganisms in the preparation of an antimicrobial drug. The bacteria used in the antimicrobial drug are *Escherichia coli*, *Vibrio parahaemolyticus*, *Acinetobacter baumannii*, *Pseudomonas aeruginosa*, *Bacillus subtilis*, *Staphylococcus aureus*, and *Bacillus anthracis*. The active ingredient of the antimicrobial drug is a compound represented by formula (I) above, or selected from stereoisomers, prodrugs, crystal forms, pharmaceutically acceptable salts, pharmaceutically acceptable esters, or pharmaceutically acceptable solvates of the compound.
[0050] 1. Determination of the minimum inhibitory concentration of antimicrobial peptides
[0051] The bacterial strains used in the minimum inhibitory concentration (MIC) determination experiment included four Gram-negative bacteria and three Gram-positive bacteria, namely Escherichia coli MG1655, Vibrio parahaemolyticus VP8, Acinetobacter baumannii ATCC19606, Pseudomonas aeruginosa PA01, Staphylococcus aureus ATCC25923, Bacillus subtilis 168, and Bacillus anthracis.
[0052] The minimum inhibitory concentration (MIC) of antimicrobial peptides was determined using the Hancock microbroth dilution method. The experimental procedure is as follows:
[0053] (1) Preparation of antimicrobial peptide solution
[0054] The synthesized antimicrobial peptide powder was dissolved in dimethyl sulfoxide (DMSO) to prepare an antimicrobial peptide stock solution with a concentration of 10 mM.
[0055] (2) Bacterial culture and preparation of bacterial solution.
[0056] Single colonies of *Escherichia coli*, *Vibrio parahaemolyticus*, *Acinetobacter baumannii*, *Pseudomonas aeruginosa*, *Staphylococcus aureus*, *Bacillus subtilis*, and *Bacillus anthracis* were picked from fresh plates and inoculated into LB broth. The culture was incubated on a shaker at 37°C and 180 rpm for 16 hours. The culture was then diluted 10,000 times to obtain a working suspension of 10... 5 CFU / mL.
[0057] (3) Antibacterial activity test
[0058] The assay was performed using sterilized polypropylene 96-well plates. Antimicrobial peptide solutions were prepared using a double-dilution method. Three parallel rows were set up for each antimicrobial peptide. Columns 1-9 contained bacterial culture and serially diluted antimicrobial peptide solutions, while column 10 was the growth control (no antimicrobial peptide solution was added). First, 5 μL of the stock antimicrobial peptide solution and 195 μL of MHB medium were added to column 1. Then, 100 μL of MHB medium was added to each of columns 2-10. Next, the antimicrobial peptide solutions were serially diluted twofold. 100 μL was transferred from the wells in column 1 to column 2 and mixed. Then, 100 μL was transferred from the wells in column 2 to column 3 and mixed. This process was repeated to complete the serial dilution (concentrations of 128, 64, 32, 16, 8, 4, 2, 1, and 0.5 μM). After mixing in column 9, 100 μL was discarded. Finally, 100 μL of a 10% concentration was added to each well in columns 1-10.5 CFU / mL bacterial culture. 96-well plates were incubated at 37°C for 16 hours. MIC refers to the lowest drug concentration that can inhibit the visible growth of microorganisms (bacteria, fungi, etc.) under specific culture conditions.
[0059] (4) Observation of results
[0060] The absorbance (OD 600nm) of each well was measured using a multi-functional microplate reader to determine the inhibitory effect on bacterial growth.
[0061] Antimicrobial peptide M7-2 exhibits significant inhibitory effects against Bacillus subtilis, Escherichia coli, Staphylococcus aureus, Acinetobacter baumannii, Vibrio parahaemolyticus, Pseudomonas aeruginosa, and Bacillus anthracis. Furthermore, the minimum inhibitory concentrations (MICs) against these bacteria are 8 μM, 16 μM, 16 μM, 32 μM, 4 μM, 16 μM, and 32 μM, respectively.
[0062] 2. Determination of the bactericidal activity of antimicrobial peptides
[0063] (1) Preparation of antimicrobial peptide solution
[0064] The synthesized antimicrobial peptide powder was dissolved in dimethyl sulfoxide (DMSO) to prepare an antimicrobial peptide stock solution with a concentration of 10 mM.
[0065] (2) Bacterial culture and preparation of bacterial solution.
[0066] Single colonies of *E. coli* were picked from fresh plates and inoculated into LB broth liquid medium. The medium was then incubated on a shaker at 37°C and 180 rpm for 16 hours. The culture was then diluted 1000 times to make a working suspension of 10... 6 CFU / mL.
[0067] (3) Bactericidal activity test
[0068] Take the bacterial solution at the working concentration and add it to 4 sterile centrifuge tubes of 5 mL each using a pipette. Set the working volume to 3 mL. Add different groups of drugs to the bacterial solution and divide them into 4 groups: (1) Growth control group: bacterial solution + 3 μL LDMSO (2) Antimicrobial peptide group: bacterial solution + antimicrobial peptide (the final concentrations of antimicrobial peptides are 4 Mic and 8 Mic, respectively). Each group is performed in 3 parallel groups. Place the 5 mL centrifuge tubes in a metal bath at 37°C and incubate them. Then perform gradient dilution of the samples at different times. For example, add 900 μL of sterile PBS solution to a 1.5 mL sterile centrifuge tube, add 100 μL of culture and mix well. This is 10 μL of culture solution. -1 Add 100 μL of the solution from the upper tube to the 900 μL sterile PBS solution in the second tube to make 10. -2And so on up to 10 -5 Or 10 -6 Samples were taken at 0h (immediately without adding any reagent), 1h, 2h, 3h, 4h, 5h, 6h, and up to 7h, and serially diluted before being spotted onto LB agar plates. After the experiment, the plates were inverted and incubated in a 37℃ incubator for 18-24h.
[0069] (4) Observation of results
[0070] The next day, remove the plates and select those with colony counts between 30 and 300 for counting. Calculate the number of viable bacteria in the sample per hour based on the colony count on the plates. The calculation formula is: CFU / mL = (average colony count / plating amount) × dilution factor.
[0071] Figure 6 The time-kill curve of antimicrobial peptide (M7-2) co-incubated with Escherichia coli is shown. The CFU count results show that antimicrobial peptide M7-2 effectively inhibits the growth of Escherichia coli and reduces the bacterial load by 5 orders of magnitude.
[0072] 3. Determination of the hemolytic activity of antimicrobial peptides
[0073] (1) Preparation of antimicrobial peptide solution
[0074] The synthesized antimicrobial peptide powder was dissolved in dimethyl sulfoxide (DMSO) to prepare a 10 mM antimicrobial peptide stock solution. Positive control stock solution: Triton X-100 (pure solution).
[0075] (2) Preparation of 10% red blood cell suspension
[0076] Take an appropriate amount of fresh, sterile sheep blood, add 5-10 times the amount of PBS solution (pH 7.4), centrifuge (1000g, 5-10 min), and discard the supernatant. Repeat washing 2-3 times until the supernatant is clear; this is the washed, compacted red blood cells. Prepare a 10% red blood cell suspension with PBS solution at a ratio of 1:9, mix well, and use.
[0077] (3) Hemolytic activity detection
[0078] The assay was performed using sterilized polypropylene 96-well plates. Antimicrobial peptide solutions were prepared using a two-fold dilution method. Three parallel rows of antimicrobial peptides were set up: columns 1-8 contained 10% erythrocyte suspension and serially diluted antimicrobial peptide solutions, while column 9 was the growth control (no antimicrobial peptide solution was added). First, 5 μL of the stock antimicrobial peptide solution and 195 μL of PBS solution were added to column 1, and 100 μL of PBS solution was added to columns 2-9 respectively. Then, a two-fold serial dilution of the antimicrobial peptide solution was performed. 100 μL was transferred from the wells in column 1 to column 2 and mixed, then 100 μL was transferred from column 2 to column 3 and mixed. This step was repeated to complete the two-fold serial dilution (concentrations of 128, 64, 32, 16, 8, 4, 2, and 1 μM). After mixing in column 8, 100 μL was discarded. For the positive control Triton X-100 solution, add 4 μL of the solution (prepared as a 2-fold concentrate) to column 1, and perform serial dilutions as described above (concentrations of 1%, 0.5%, 0.25%, 0.125%, 0.06%, 0.03%, 0.016%, 0.008%, and 0.004%). Add 100 μL of 10% erythrocyte suspension to each well in columns 1-9 to achieve a final erythrocyte concentration of 5%. Incubate the 96-well plate at 37°C for 0.5 hours.
[0079] (4) Observation of results
[0080] Centrifuge the 96-well plate at 1000g for 3-5 minutes until red blood cells have completely settled. Take a new flat-bottomed 96-well plate and carefully transfer 100μL of supernatant from each well of the original plate to the new plate. Measure the absorbance at 540nm wavelength (OD 540nm) using a multi-mode microplate reader and calculate the hemolysis rate for each concentration. The calculation formula is: Hemolysis rate (%) = (Oxygenated protein) × 100%. The minimum hemolytic concentration is the concentration at which the antimicrobial peptide causes a 10% hemolysis rate.
[0081] Figure 7 The results of the hemolytic activity assay for the antimicrobial peptide (M7-2) showed that no hemolytic activity was detected within the detection range.
[0082] Based on the above results, the antimicrobial peptide (M7-2) obtained by analyzing a marine microbial antimicrobial peptide library with optimal parameters and combining this with database activity prediction and screening tools exhibits good antimicrobial activity and low hemolysis rate. This indicates its potential to replace antibiotics and provides a feasible method for antimicrobial peptide design.
[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. An antimicrobial peptide derived from marine microorganisms, characterized in that: Selected from compounds represented by formula (I), or from stereoisomers, prodrugs, crystal forms, pharmaceutically acceptable salts, pharmaceutically acceptable esters or pharmaceutically acceptable solvates of said compounds; 。 2. The method for screening antimicrobial peptides derived from marine microorganisms according to claim 1, characterized in that: The process includes the following steps: First, based on the genomic resources of *Bacillus* genus from the marine environment, short open reading frame sequences are obtained to ensure that the target sequence conforms to the core structural features and length range of the antimicrobial peptide precursor molecule. Then, through sequence redundancy optimization, multi-model collaborative validation, and database construction, a non-redundant antimicrobial peptide sequence is obtained. Next, the peptide RWWCRWR is synthesized using a solid-phase synthesis method and reacted with acetic anhydride and pyridine to perform N-terminal acetyl capping and C-terminal amino capping to obtain the antimicrobial peptide Ac-RWWCRWR-NH2 shown in formula (I).
3. The method for screening antimicrobial peptides derived from marine microorganisms according to claim 2, characterized in that: In the process of obtaining short open reading frame sequences, the bioinformatics tool EMBOSS was used to perform a whole-genome scan of the *Bacillus* genus resources, specifically identifying and predicting short open reading frame sequences. The screening criteria were set as a sequence length of 18-150 base pairs to ensure that the target sequence conforms to the core structural characteristics and length range of antimicrobial peptide precursor molecules.
4. The method for screening antimicrobial peptides derived from marine microorganisms according to claim 2, characterized in that: During the sequence redundancy optimization process, the predicted short open reading frame sequences are batch merged, and the Seqkit tool is used to carry out efficient sequence deduplication. By accurately comparing and filtering, 100% similar redundant sequences are removed, effectively avoiding resource consumption and result deviation caused by repeated analysis, and ensuring the efficiency and accuracy of subsequent prediction analysis.
5. The method for screening antimicrobial peptides derived from marine microorganisms according to claim 2, characterized in that: In the process of multi-model collaborative validation, the redundancy-removed smORF sequence is input into eight deep learning prediction models in three open-source projects: c_AMPs-prediction, SMEP, and AMP-potency-prediction-EvoGradient. Collaborative prediction and cross-validation of antimicrobial activity are carried out. Strict judgment criteria are set. Only when all eight deep learning prediction models unanimously determine that the sequence has antimicrobial activity can it be included in the candidate antimicrobial peptide category. Multi-model cross-validation significantly improves the reliability and credibility of the prediction results.
6. The method for screening antimicrobial peptides derived from marine microorganisms according to claim 2, characterized in that: During the database construction process, non-redundant candidate antimicrobial peptides were finally obtained through screening, and a comprehensive database of antimicrobial peptides from marine genus *Bacillus* was constructed. Based on core indicators such as multi-model prediction confidence and sequence physicochemical properties, a comprehensive evaluation was conducted, and the antimicrobial peptide Ac-RWWCRWR-NH2 was finally selected.
7. The application of the antimicrobial peptide derived from marine microorganisms according to claim 1 in the preparation of antimicrobial drugs.
8. The application of an antimicrobial peptide derived from marine microorganisms according to claim 7, characterized in that: The bacteria mentioned in the antibacterial drug are Escherichia coli, Vibrio parahaemolyticus, Acinetobacter baumannii, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, and Bacillus anthracis.
9. The application of a marine microbial source according to claim 8, characterized in that: The minimum inhibitory concentrations (MICs) of the antibacterial drugs against Escherichia coli, Vibrio parahaemolyticus, Acinetobacter baumannii, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, and Bacillus anthracis are 8 μM, 16 μM, 16 μM, 32 μM, 4 μM, 16 μM, and 32 μM, respectively.
10. The application of a marine microbial source according to claim 7, characterized in that: The active ingredient of the antibacterial drug is a compound represented by formula (I) above, or selected from stereoisomers, prodrugs, crystal forms, pharmaceutically acceptable salts, pharmaceutically acceptable esters, or pharmaceutically acceptable solvates of the compound.