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. 2025 Sep 16;57(1):45. doi: 10.1007/s00726-025-03477-y

Rational designing and synthesizing an antimicrobial peptide from bovine milk casein and evaluating its biological properties

Seyed Reza Pourhosseini 1, Bahman Akbari 1, Elahe Ghods 2, Kamal Veisi 1,✉, Hamid Madanchi 2,3,✉
PMCID: PMC12441096  PMID: 40956460

Abstract

The overuse of antibiotics has led to a growing crisis—antimicrobial resistance, making it harder to treat infections and pushing scientists to find new solutions. Among the most promising alternatives are bioactive peptides, especially antimicrobial peptides, which offer broad-spectrum activity with a lower risk of resistance. One exciting source of these peptides is milk, particularly casein-derived peptides, which naturally possess antimicrobial properties. This study focused on bovine milk casein to design and synthesize a novel antimicrobial peptide. We evaluated several properties, such as antimicrobial activity, cytotoxicity, stability, and structure, using computational predictions to select the most promising candidate. The peptide NCP1 emerged as the best option and was synthesized for lab testing. Our results showed that NCP1 has antifungal activity and effectively stops the growth of Candida albicans with a minimum fungicidal concentration (MFC) of 250 µg/mL in less than four hours. It also prevented biofilm formation, interacted with DNA, and bound to ergosterol, ultimately damaging the fungal cell wall. Additionally, NCP1 demonstrated feeble antibacterial effects, particularly against Staphylococcus aureus and Pseudomonas aeruginosa. However, its antibacterial impact weakened over time due to interactions with environmental salts. Since the NCP1 peptide has low cytotoxicity and kills the yeasts selectively, further refinements to improve its potency and stability could pave the way for our future study of the presentation of a potent antimicrobial peptide.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00726-025-03477-y.

Keywords: Antimicrobial peptides, Casein, In Silico design, Antifungal peptides, Antimicrobial resistance

Introduction

Antimicrobial resistance (AMR) is a major global public health issue, driven by the irresponsible use of antibiotics in humans and animals, which contributes to the emergence of antibiotic-resistant bacteria, viruses, fungi, and parasites that do not respond to antimicrobial treatments (Helmy et al. 2023; Tang et al. 2023; Ranjbar and Alam 2024). The spread of AMR occurs through human contact inside and outside healthcare facilities and is worsened by the uncontrolled use of antimicrobials in animal feed (Salam et al. 2023). The rise of antimicrobial-resistant strains, including multidrug-resistant (MDR) and extensively drug-resistant (XDR) bacteria like Klebsiella pneumoniae and Escherichia coli resistant to carbapenems and cephalosporins in 193 countries, poses considerable challenges for treatment, especially since no new class of antibiotics has been introduced in the last twenty years, highlighting the urgent need for new strategies to combat AMR (Murugaiyan et al. 2022). Projections suggest that, if antimicrobial resistance remains unaddressed, it could result in a significant global health crisis, with an estimated 169 million deaths attributable to resistant infections between 2025 and 2050 (Ahmad et al. 2025).

Antimicrobial peptides (AMPs) are essential components of the innate immune system in many organisms and play a crucial role in defending against microbial infections. These peptides have unique characteristics that allow them to effectively interact with microbial membranes, as well as other cellular targets such as the cell wall, DNA, and proteins, and exhibit a wide range of activity against fungi, bacteria, viruses, and parasites. They are mainly known for their effectiveness against antibiotic-resistant strains and for inducing resistance less frequently than conventional antibiotics, despite the existence of some bacterial defense mechanisms against AMPs (Huan et al. 2020; López-García et al. 2022; Li et al. 2022a).

Recent research has shown that AMPs have potential beyond direct antimicrobial actions. For instance, some AMPs can prevent biofilm formation and promote biofilm dispersal at concentrations that do not inhibit growth, which is crucial for treating chronic infections and addressing antibiotic resistance (Castillo-Juárez et al. 2022). Moreover, AMPs are considered promising candidates for next-generation antibiotics due to their low toxicity and diverse mechanisms of action (Yan et al. 2022).

However, there are still challenges in the widespread use of AMPs, such as high production costs and the complexity of large-scale synthesis (Dini et al. 2022). Despite these challenges, ongoing research and technological advancements continue to enhance our understanding and utilization of AMPs in combating multidrug resistance, positioning them as a critical component in the future of antimicrobial therapy (Lazzaro et al. 2020; Lin et al. 2023).

Milk is a diverse and complex biological fluid containing proteins, fats, carbohydrates, minerals, and vitamins that meet the mammal’s nutritional needs. It contains essential proteins such as caseins and whey, which provide essential amino acids and have various biological functions. These proteins help release cytokines, regulate immune response, and have other beneficial effects (Ledesma-Martínez et al. 2019). Studies have shown that bioactive peptides with significant physiological impacts are released when milk proteins are digested. These peptides can enhance immune function, regulate blood pressure, and potentially play a role in cancer prevention. Milk components’ diverse chemical and functional activities emphasize their importance as a nutritional and bioactive substance (Ledesma-Martínez et al. 2019).

Advancements in designing antimicrobial peptides (AMPs) have focused on using computational tools and integrating multidisciplinary approaches to improve the efficacy and specificity of AMPs (Cardoso et al. 2023). Quantitative structure-activity relationship (QSAR) models have been essential in enhancing the biological activities of AMPs, thus making them more effective as therapeutic agents (Cardoso et al. 2020).

The development of AMPs aims to address the limitations of traditional antibiotics, especially in dealing with drug-resistant bacteria. This involves designing cationic and α-helical peptides with broad-spectrum antimicrobial activities and minimal harm to human cells. These peptides can also potentially disrupt bacterial biofilms and bind to bacterial DNA (Yang et al. 2023).

In this study, a 10-amino acid peptide derived from cow’s milk casein named NCP1 was designed using machine learning algorithms and a rational design strategy then antimicrobial properties, cytotoxicity, and some action mechanisms of this peptide were evaluated.

Materials and methods

Peptide design and bioinformatics studies

The process of this step began with the retrieval of all Bos taurus casein sequences from the National Center for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov/). Subsequently, the Collection of Anti-Microbial Peptides (CAMPR4) (http://www.camp.bicnirrh.res.in/) (Gawde et al. 2023) was employed to generate a pool of antimicrobial peptides, each consisting of 10 amino acids, within the Bos taurus casein sequences by “Predict antimicrobial region within peptides” tool. This choice was based on multiple criteria. It is well established that alpha-helical structures, which are commonly associated with antimicrobial activity, require at least 10 residues for stable formation (Raguse et al. 2002; Wang et al. 2016; Goki et al. 2024). Furthermore, longer peptides may be more susceptible to proteolytic degradation, which can lead to reduced stability in vivo. Longer AMPs have also been associated with increased potential cytotoxity to host cells (Madanchi et al. 2020b; Nikookar Golestani et al. 2023). On the other hand, longer peptides increase the complexity and cost of synthesis. Thus, a 10-residue length was considered optimal in terms of balancing activity, stability, and synthetic efficiency. The identification of antimicrobial peptides was accomplished through the application of multiple algorithms, including Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN) in both natural and synthetic datasets. A threshold range of 0.5 to 1 was established, with peptides exhibiting a threshold value exceeding 0.5 classified as antimicrobial. To enhance the probability of antimicrobial activity across all algorithms, the sequences demonstrating antimicrobial activity underwent four iterations of rational design in both natural and synthetic datasets by the “Rational design of antimicrobial peptides” tool. Following this initial screening, the physicochemical properties of the selected sequences were thoroughly evaluated. These properties, including isoelectric point (pI), Boman index, stability, hydrophobicity, Grand average of hydropathicity (GRAVY) index, and net charge, were assessed using the Antimicrobial Peptide Calculator and Predictor from the Antimicrobial Peptide Database (https://aps.unmc.edu/) (Wang et al. 2016) and ProtParam from Expasy (https://web.expasy.org/protparam/). To provide a comprehensive assessment of the peptides’ characteristics, additional analyses were conducted. The toxicity of the peptides was predicted using ToxinPred3.0 (https://webs.iiitd.edu.in/raghava/toxinpred3/) (Rathore et al. 2023), while their potential allergenicity was evaluated using both AllerCatPro 2.0 (https://allercatpro.bii.a-star.edu.sg/) (Nguyen et al. 2022) and AlgPred 2 (https://webs.iiitd.edu.in/raghava/algpred2/index.html) (Sharma et al. 2021). The Predicting Antigenic Peptides tool (http://imed.med.ucm.es/Tools/antigenic.pl) was employed to identify antigenic peptides. The half-life of peptides in the intestine was estimated using HLP (https://webs.iiitd.edu.in/raghava/hlp/) (Sharma et al. 2014). Furthermore, the SCRATCH Protein Predictor server (http://scratch.proteomics.ics.uci.edu/) was utilized to predict the antigenicity of the peptides using the ANTIGENpro tool and their solubility using SOLpro. The potential for cell permeability was predicted using CellPPD (http://crdd.osdd.net/raghava/cellppd/multi_pep.php) (Gautam et al. 2013), while the DNA-binding activity was assessed using the DNA BIND server (https://dnabind.szialab.org/) (Szilágyi and Skolnick 2006). Antifungal activity predictions were made using the AntiFP server (https://webs.iiitd.edu.in/raghava/antifp/) (Agrawal et al. 2018). To determine if there is a homologous peptide in Homo sapiens, the Peptide Match tool on the Protein Information Resource (PIR) (https://research.bioinformatics.udel.edu/peptidematch/index.jsp) was utilized (Chen et al. 2013). To elucidate the three-dimensional structure of the peptide, PEP-FOLD4.0 (https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4/) (Rey et al. 2023) and AlphaFold (https://alphafoldserver.com) was used. Ultimately, a peptide exhibiting both antifungal and antibacterial properties, along with the highest scores across all algorithms, was selected as a natural positive control.

Peptide synthesis

The peptide with the sequence FFSLKILKKK was produced using a solid-phase synthesis technique under ShineGene Biotech, Inc. (Shanghai, China), fluorene-9-methoxycarbonyl (Fmoc)-polypeptide active ester chemistry. The synthesized peptides were purified to 95% using the RP-HPLC (Reverse Phase-High Pressure Liquid Chromatography) method. Finally, the Sciex API100 LC/MS (Liquid Chromatography/ Mass Spectrometer) mass spectrometer (Massachusetts, USA) was used to confirm the peptides’ molecular weight and sequence accuracy.

Fungal strains, cell lines, reagents, and media

Sabouraud dextrose agar (SDA), Sabouraud dextrose broth (SDB), ethanol, and phosphate-buffered saline (PBS) were purchased from Merck Millipore Company (Merck, Darmstadt, Germany). Fetal bovine serum (FBS) and DMEM F12 media were purchased from Gibco Company (Gibco, Carlsbad, CA, USA). Cell culture antibiotics (penicillin and streptomycin), nystatin, fluconazole, amphotericin B, trypsin, trypan blue dye, NaOH, HCl, 3-(4,5‐dimethylthiazol‐2‐yl) ‐2,5‐diphenyltetrazolium bromide (MTT) dye, Triton‐X‐100, glutaraldehyde, Ergosterol, Chitin and dimethyl sulfoxide (DMSO) were procured from Sigma (Sigma‐Aldrich, St. Louis, MO, USA). The 100-base pair DNA ladder (DM2300) was purchased from SMOBIO Technology, Inc.

Pseudomonas aeruginosa (ATCC 27853), Staphylococcus aureus (ATCC 25923), Candida albicans (ATCC 10231), Candida krusei (ATCC 28870), Candida glabrata (ATCC 90030), and Aspergillus niger (ATCC 9142) were provided by the Microbial Bank and Pathogenic Fungi Culture Collection of the Pasteur Institute of Iran. The mouse fibroblast cells (L929 cell lines ATCC CCL-1) were purchased from the National Cell Bank of the Pasteur Institute of Iran. for cytotoxicity test.

Ethical statement

This study was approved by the Medical Ethics Committee of Kermanshah University of Medical Sciences (Kermanshah, Iran) with the ethical code number IR.KUMS.MED.REC.1402.178. In this study, the blood donor for the hemolysis test first filled out an informed consent form, and then skilled laboratory personnel took 5 ml of blood from him.

Characterization of the secondary structure of peptide by circular dichroism (CD)

The peptide’s mean residue molar ellipticities were determined using a Jasco J-810 CD spectropolarimeter at 25 °C with a 200 nm/min scanning speed. The peptide’s solution in 70% TFE, ranging from 0.2 to 0.5 mg/mL, was placed in a 1-mm quartz cell, and its spectra were scanned from 190 to 260 nm with five scans (Madanchi et al. 2019a). Jasco J-810 Spectra Analysis software was used for CD spectra analysis.

Antimicrobial assay

The antimicrobial effectiveness of the peptide was evaluated using a serial dilution titration method to determine the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) or fungicidal concentration (MFC) against bacterial and fungal strains by the guidelines of the Clinical and Laboratory Standards Institute (CLSI). The bacteria were grown overnight at 37 °C (Some fungi were incubated at 25 °C) in MHB (SDB for fungi) and were diluted in the same medium. Two-fold serial dilutions of the peptide were added to the microtiter plates in a volume of 100 µL, followed by 100 µL of the fungi to give a final inoculum of 5 × 105 colony-forming units (CFU)/mL. The plates were incubated at 37 °C for 24 h and 48 h, and the MICs were determined. Next, 20 µL of the 24-h inhibitory concentration test sample (MIC well) and its further concentrations were plated on MHA (SDA for fungi strain) and incubated at 37 °C overnight to determine the MBC and MFC (Balouiri et al. 2016).

Killing kinetic assay

A killing kinetic assay was conducted against C. albicans to determine the fungicidal speed of the NCP1 peptide. First, logarithmically growing yeasts were inoculated into sterile SDB, adjusted to 5 × 105 CFU/mL, and added to the medium containing the peptides at concentrations equivalent to 1X MFC. Following incubation for 0, 2, 4, 6, 8, and 24 h at 37℃, samples were diluted (1:100) and plated in triplicate onto SDA plates. Then, the colonies (colony-forming units or CFUs) were counted. The results were reported based on the logarithm of CFU per specific time points. Fluconazole antibiotic was also used as a control at 2X MIC (Madanchi et al. 2019b).

Combinatorial effects of peptides with conventional antifungal drugs

The potential synergistic effect among fluconazole (Flu), nystatin (Nys), and peptide was studied using a synergy assay based on the checkerboard titration method. C. albicans ATCC 10,231 was used for the assay with the conventional antibiotics selected for fungi and the peptide. First, a concentration of fungi corresponding to 5 × 105 CFU/mL was prepared as fungi inoculum. The tested concentrations of both antibiotics and the peptide ranged from 2×MIC to Inline graphic×MIC, and the results were reported after 24 h of nongrowth in the given conditions (Le et al. 2015). The checkerboard assay results were analyzed using the fractional inhibitory concentration index (FIC):

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peptides and antibiotic are antagonistic if FIC ≥ 4.0, indifference if > 1 FIC < 4.0, additive if > 0.5 FIC ≤ 1, and synergism if FIC ≤ 0.5.

Biofilm assay

The peptide’s ability to prevent biofilm formation was tested using the tissue culture plate (TCP) method against standard C. albicans. A 72-hour culture of C. albicans was prepared at 37 °C, and different peptide concentrations were added to a 96-well plate using 2-fold dilutions. The blank control consisted of only the culture medium, while the negative control contained the fungal suspension in the culture medium. After removing the excess culture medium, the wells were washed with sterile PBS and fixed with 95% methanol for 15 min. Subsequently, 0.1% crystal violet solution was added to each well and incubated at 37 °C for 15 min. The wells were washed with distilled water, and 33% glacial acetic acid was added to each well. The extent of biofilm formation can be assessed by visually inspecting the turbidity. The optical density (OD) values of all wells at 570 nm were measured using a microplate reader (STAT FAX 2100, BioTek, Winooski, USA) (Stepanović et al. 2007). Biofilm inhibition was calculated using the following formula:

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Ergosterol and Chitin binding assay

An ergosterol and chitin binding assay was performed to measure the binding potency of peptides to fungal membrane sterols and structural polysaccharides. Ergosterol was dissolved in DMSO and Tween-20, heated to enhance emulsion solubility, and diluted in an SDB medium at 400 mg/mL. Chitin was prepared at a concentration of 0.5 mg/ml in PBS. Both solutions were incubated separately at 37 °C for 1 h. Following this, the MIC of the peptide was determined using the microdilution method in the presence and absence of ergosterol and chitin at various concentrations against C. albicans (Leite et al. 2014; Turecka et al. 2018; Namvar Erbani et al. 2021).

Docking studies for peptide-ergosterol interaction

A molecular docking simulation was performed to investigate the NCP1 peptide interactions with ergosterol as a potential antifungal mechanism of action. First, the 3D structure of ergosterol (CID 444679) was obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The SDF file of ergosterol was transformed into a PDB file using OpenBabel software version 2.4.1 (O’Boyle et al. 2011). All input files, including the peptide and ergosterol, were prepared using the AutoDock Tools (ADT) 1.5.7 package and DockThor (https://dockthor.lncc.br/v2/). Polar hydrogens were added to the peptide and their partial atomic charges were determined using the Kollman-united charges method. Also, the charges of ergosterol were assigned according to the Gasteiger-Marsili charges(Trott and Olson 2010). The peptide-ligand interactions in complexes obtained from the docking were studied using PDBsum Generate (https://www.ebi.ac.uk/thornton-srv/databases/pdbsum/Generate.html) and PRODIGY (https://rascar.science.uu.nl/prodigy/) (Xue et al. 2016).

Cytotoxicity test

The peptide’s cytotoxicity was assessed for the L929 cell line using the MTT assay. Cells were seeded at a density of 5 × 105 cells per well in a 96-well plate, and the wells were treated with varying concentrations of the peptide. A negative control using PBS was included. After a 24-hour incubation, the medium (containing 10% FBS) was replaced with fresh medium containing 10% MTT solution (5 mg/mL MTT in PBS), and the plate was then incubated for 4 h in a 5% CO2 environment at 37 °C. Subsequently, the medium was aspirated, and DMSO (100 µL per well) was added to solubilize the formazan crystals, after which the plate was gently shaken. Finally, the absorbance at 595 nm was measured using a microplate reader (STAT FAX 2100, BioTek, Winooski, USA) (Madanchi et al. 2020a).

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Hemolytic assay

The potential effects of the peptide on human erythrocytes were investigated using a hemolytic assay. A volunteer with blood type O provided fresh blood samples, from which a suspension of human erythrocytes was prepared by diluting it 1:20 in PBS. Subsequently, 100 µL of the diluted erythrocyte suspension was added in triplicate to 100 µL of a 2-fold serial dilution series of the peptide in a 96-well plate. A positive control containing 1% Triton-X 100 was used to induce 100% lysis of the erythrocytes, while a negative control utilized a sterile 0.9% NaCl solution. The plates were then incubated at 37 °C for 1 h and centrifuged for 10 min at 3000 rpm. Following centrifugation, 150 µL of the supernatant was transferred to a new 96-well plate, and the absorbance was measured at 414 nm using a microplate reader (STAT FAX 2100, BioTek, Winooski, USA). Finally, the percentage of hemolysis was calculated using the following formula (Madanchi et al. 2020b).

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DNA binding assay

An electrophoretic mobility shift assay (EMSA) was conducted to investigate the DNA-binding activity of the NCP1. For this purpose, 7.5 µL of 100-base pair DNA ladder (DM2300) with a concentration of 56 µg / 500 µL was combined with 7.5µL of 400 µg/mL and 60 µg/mL of the peptide solution in TE buffer (10 mM Tris, 1 mM EDTA buffer, pH 8.0). The mixtures were then incubated at room temperature for 30 min and subsequently electrophoresed in 1.5% agarose gels containing 0.5 µg/mL safe stain (Nam et al. 2014).

Investigating the effects of the peptide on C. albicans surface by FE-SEM

The fungi cells of C. albicans ATCC 10,231 were cultured in RPMI (with 2% glucose) and placed in an incubator at 37 °C for 24 h. After that, the cells were collected by centrifugation at 4000 rpm for 1 min and rinsed three times with PBS (pH 7.4). Subsequently, a C. albicans suspension of 106 CFU was exposed to the peptide at a concentration of 0.5×MIC for specific periods (0, 2, and 4) and then separated at 4000 rpm for 1 min. The suspension was rinsed twice with PBS (pH 7.4) and then treated with 2.5% glutaraldehyde in 0.1 M PBS (pH 7.4) for 1 h at 25 °C in a dark chamber. The samples were separated at 4000 rpm for 1 min, rinsed three times in distilled water, placed on 1 cm² FE-SEM slides, and subsequently dehydrated using an ethanol gradient (10%, 30%, 60%, 70%, 90%, and 100%). Finally, the dehydrated fungi cells were dissolved in 100% ethanol for 15 min and air-dried at room temperature (25 °C). The C. albicans cells were coated with gold nanoparticles via an automatic sputter coater. The samples were then examined using a FE‐SEM instrument (JSM‐7610 F, JEOL Co., Japan and MIRA3, TESCAN Co., Czech) (Akbari et al. 2018).

Effect of salts on antimicrobial activity of NCP1 peptide

To evaluate the effect of salts on the efficacy and stability of the antimicrobial properties of NCP1 peptide, the minimum inhibitory concentrations (MICs) against C. albicans were measured under different conditions. Fungal inoculum at a concentration of 5 × 105 CFU/ml was added to the wells of a 96-well plate containing different concentrations of salts (150 mM NaCl and 1 mM MgCl₂). The plate was incubated for 24 h at 37 °C, and the MIC values ​​were determined to evaluate the antimicrobial efficacy and stability of the peptide in the presence of these salts (Memariani et al. 2016).

Statistical analysis

In this study, all the experiments were conducted three times. The statistical significance of the differences in the MICs, toxicity, and hemolysis values was assessed using a t-test in the SPSS Statistics 22.0 program (SPSS Inc., Chicago, IL, USA). For assays involving multiple concentrations, one-way ANOVA was used. P values less than 0.05 were considered statistically significant.

Results

Peptide design and predicting its physicochemical and biological properties

The casein sequences, including Alpha S1 casein (GenBank: ACG63494.1), alpha S2 casein (NCBI Reference Sequence: XP_024848785.1), beta casein (GenBank: AAA30431.1), and kappa casein (GenBank: AAQ87923.1), were obtained from the NCBI database. The CAMPR4 server was used to extract all potential antimicrobial peptides (AMPs) from these casein sequences, resulting in an initial pool of peptides. The extracted peptides underwent prediction using SVM, RF, and ANN algorithms. After removing duplicates, the peptides were filtered based on their antimicrobial, biological, and physicochemical properties, retaining only those with a threshold value exceeding 0.5. Peptides demonstrating the highest antimicrobial activity underwent four iterations of rational design to enhance their antimicrobial activity (Supplementary Table 1). Based on these criteria, the best peptide with the FFSLKILKKK sequence was selected, and NCP1 was named. The physicochemical and biological properties of the NCP1 peptide are shown in Tables 1 and 2, respectively. Homology analysis using the Peptide Match tool on PIR confirmed, there are no homologous sequences in Homo sapiens proteome. Predicting the 3D structure of NCP1 peptide with PepFOLD4.0 showed that its structure is a helix, while AlphaFold predicted the 3D structure of NCP1 to be a mixture of coil and helix (Fig. 1).

Table 1.

Physicochemical properties of NCP1 peptide and their prediction servers

Servers Physicochemical properties Score/ Interpretation
ProtParam Stability Stable
ProtParam Theoretical pI 10.47
ProtParam GRAVY 0.13
ProtParam Hydrophobic Ratio (%) 50
ProtParam Net Charge + 4
AMP Calculator and Predictor Boman Index (kcal/mol) 0.488
SoLPro Solubility 0.848791/Soluble
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Table 2.

Biological properties of NCP1 peptide and their prediction servers

Servers Biological properties Interpretation
CAMPR4 score Antimicrobial activity AMP
ToxinPred3 Toxicity Non-Toxin
AllerCatPro2 Allergenicity No evidence
AlgPred2 Allergenicity Non-Allergen
PAP and ANTIGENpro Immunogenicity Non-Antigenic
CellPPD Cell-penetrating potential CPP
HLP Stability in the human intestine Normal
AntiFP Antifungal activity Antifungal
PIR Presence in the human proteome No match
DNA BIND DNA binding activity Bind to DNA
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Fig. 1.

Fig. 1

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Predicted 3D structure of NCP1 peptide using (A) PepFOLD4.0, and (B) AlphaFold servers. This illustration shows that the NCP1 structure was identified as a helix by PepFOLD4.0, while this peptide was simulated as a mixture of helix and coil structure using AlphaFold

Peptide synthesis

ShineGene Biotech company (Shanghai, China) synthesized 10 mg of NCP1 peptide with a molecular weight of 1251.62 Daltons and a purity of over 90%. Its accuracy was verified by mass spectrometry and RP-HPLC, which are shown in supplementary figure S1.

Characterization of the secondary structure of the NCP1 peptide by CD

The analysis of the CD graph for the 70% TFE solution of the NCP1 peptide showed that it has a helical structure of 54.3%, a coil of 40.1%, and a beta-strand of 6.5% (Supplementary Fig. 2 or Figure S2). These results were almost consistent with the prediction of this peptide’s structure with the AlphaFold server.

Antimicrobial activity of NCP1 peptide

The NCP1 peptide showed specific antifungal activity against selected fungi, particularly C. albicans, C. krusei, and C. glabrata. The MIC for C. albicans and C. krusei was measured at 125 µg/mL, while for C. glabrata, it was 500 µg/mL. The MIC for Aspergillus niger was higher than 500 µg/mL. Also, the MIC for S. aureus and P. aeruginosa was higher than 500 µg/mL. Fluconazole, Penicillin, and Streptomycin were used as standard antibiotics. The MFCs for C. albicans and C. krusei were determined to be 250 µg/mL. Table 3 shows all MICs and MBCs/MFCs data.

Table 3.

MIC and MBC (MFC for fungi) for NCP1 against several microorganisms after 24 h

Microorganism MIC/MBC or MFC (µg/mL)
NCP1 Fluconazole Penicillin Streptomycin
C.albicans 125 /250 6.25 / 50 - -
C. krusei 125 / 250 50 / >50 - -
C. glabrata 500 / >500 > 50 / >50 - -
A. niger > 500 / >500 > 50 / >50 - -
S. aureus > 500 / >500 - 0.78125 /NA 62.5/NA
P. aeruginosa > 500 / >500 - - 3.125 /NA
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Killing time of NCP1 peptide

The result shows significant differences emerged after 2 h, where the NCP1’s antifungicidal activity was markedly higher than that of fluconazole. After 4 h, the NCP1 peptide had eradicated all C. albicans, and no colony growth was observed up to 24 h. In contrast, while reducing fungal growth after 4 h, fluconazole failed to achieve complete fungal eradication at any point during the time frame studied (Supplementary Tables 2 and Figure S3). These findings underscore the superior speed and efficacy of the NCP1’s antifungicidal activity compared to fluconazole, as illustrated in Fig. 2.

Fig. 2.

Fig. 2

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Graph of C. albicans colony count versus time (hours) of the effect of NCP1 peptide compared to the antibiotic fluconazole

Combinatorial effects of the NCP1 with conventional antifungal drugs

In a synergism test, fluconazole and nystatin were used in combination with the NCP1 peptide against C. albicans. The results, interpreted through the FIC index, indicated that the combination of the NCP1 peptide with either fluconazole or nystatin showed no synergistic effects. This suggests that the NCP1 peptide does not enhance the antifungal efficacy of fluconazole and nystatin when used together against C. albicans. Table 4 interprets the results of synergy measurement and the FIC index.

Table 4.

Combined effects of NCP1 peptide with antibiotics fluconazole and Nystatin against C. albicans

Combination FIC index Interpretation
NCP1 + Fluconazole 2.25 Indifference
NCP1 + Nystatin 1.6875 Indifference
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Anti-biofilm activity of NCP1 peptide

The anti-biofilm activity of the NCP1 peptide was evaluated against C. albicans. At the three highest concentrations tested (500, 250, and 125 µg/mL), the NCP1 peptide demonstrated substantial inhibition of biofilm formation, with inhibition percentages exceeding 90%. At lower concentrations, the biofilm inhibition ranged between 12% and 37% (Fig. 3).

Fig. 3.

Fig. 3

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This image shows a 96-well plate for measuring peptide anti-biofilm activity, and a graph of the inhibition percentage of C. albicans biofilm by the effect of NCP1 peptide at different concentrations

Toxicity of NCP1 peptide against mice skin fibroblast cells and human red blood cells

The MTT assay results on the L929 cell line revealed that the cell viability at the highest concentration of the NCP1 peptide (500 µg/mL) was nearly 80% (Fig. 4A). The IC50 value for the NCP1 was approximately 1811 µg/mL, while the MIC for C. albicans was 125 µg/mL. Also, the NCP1’s hemolytic activity was assessed using a hemolysis assay on human red blood cells (RBCs). At the highest concentration of 500 µg/mL, the NCP1 exhibited a hemolytic activity of less than 2.5%, indicating its low toxicity (Fig. 4B).

Fig. 4.

Fig. 4

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(A) Percentage of toxicity of NCP1 peptide at different concentrations on L929 cell line over 24 h, (B) Hemolysis percentage of human red blood cells by NCP1 peptide at different concentrations (µg/ml)

EMSA test results

EMSA is a suitable method to study how peptides interact with DNA. When using 1.5% agarose gel and NCP1 peptide (final concentration approximately 200 µg/mL), strong binding between the peptide and the DNA ladder was observed and the complex of peptide-DNA remained in the well and no movement was observed (Fig. 5A). Furthermore, when using a 30 µg/ml NCP1 peptide, little binding between DNA and peptide was detected because the peptide-complexed DNA bands were only slightly delayed compared to the free DNA. However, as shown in Fig. 5, the delay of DNA bands when using low peptide concentration was not comparable to that of high peptide concentration (Fig. 5B).

Fig. 5.

Fig. 5

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Image of agarose gel of EMSA assay. (A) DNA treated with 200 µg/ml NCP1 peptide. (B) DNA treated with 30 µg/ml NCP1 peptide. Well 1: DNA ladder alone, well 2: DNA ladder complex with peptide

Assessment of NCP1 peptide binding to ergosterol and Chitin

The results of the peptide-ergosterol binding assay showed that the NCP1 peptide interacted with ergosterol. The MIC of the NCP1 peptide against C. albicans in the absence of ergosterol was 125 µg/mL, while in the presence of ergosterol, the MIC was approximately 500 µg/mL. These results indicate that ergosterol neutralizes the effect of the NCP1 peptide and prevents its effectiveness against C. albicans. However, in the case of chitin, the results showed that there was no binding between the NCP1 peptide and chitin, and the MIC of the peptide did not change in the presence or absence of chitin and was equal to 125 µg/mL (Table 5 and supplementary figures S4 and S5).

Table 5.

MIC values (µg/ml) of NCP1 peptide in the presence and absence of ergosterol and Chitin against Candida albicans

Compound Ergosterol Chitin
Absence Presence Absence Presence
NCP1 125 500 125 125
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Docking simulation to investigate the interactions of NCP1 peptide with ergosterol

Docking performed by DockThor and Auto Dock vina server shows the binding affinity between NCP1 peptide and ergosterol, which is shown in Fig. 6A and B. Other results related to the molecular docking simulation are reported in Table 6. These results indicate a favorable interaction between the NCP1 peptide and ergosterol, supporting the proposed mechanism of membrane disruption. The binding is mainly stabilized by electrostatic interactions and van der waals forces, as reflected in the calculated energy values. Also, the residues involved in binding to ergosterol are shown in the Ligplot diagram (Fig. 6C).

Fig. 6.

Fig. 6

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(A) Docking results of NCP1 peptide (blue) with ergosterol (gray) by DockThor server (A) and AutoDock Vina software (B). The red dashed lines indicate the interactions between NCP1 peptide and ergosterol. (C) The ligPlot plot (the result of the PDBsum Generate server) shows interactions between NCP1 peptide and ergosterol. The green dashed line indicates hydrogen bonding and the red lines on the semicircle indicate hydrophobic interactions

Table 6.

Parameters from molecular Docking simulation of the NCP1-ergosterol peptide complex

Complex Affinity (Kcal/mol) Total Energy (Kcal/mol) vdW Energy Elec. Energy
NCP1 - ERG -6.727 44.341 -5.685 -13.5
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Investigation of the effect of NCP1 peptide on Candida albicans by FE-SEM

The effect of NCP1 peptide on the morphology of C. albicans at 2 and 4 h time points was evaluated by FE-SEM imaging. Treatment with NCP1 peptide at a 0.5 MIC concentration of 125 µg/ml at 2 h caused significant morphological changes, including wrinkling, nucleic acid leakage, formation of primary pores, and blistering on the fungal surface (panel B in Fig. 7). After 4 h, these changes were more severe, with larger pores and cell lysis (Fig. 7).

Fig. 7.

Fig. 7

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FE-SEM electron microscope images of C. albicans treated with NCP1 peptide at MIC concentration for 2 and 4 h. (A) No treatment, (B) Treatment with NCP1 peptide at MIC concentration for 2 h, and (C) Treatment with NCP1 peptide at MIC concentration for 4 h. Labeling includes (0): intact cells, (1): released nucleic acids, (2): blisters, (3): cell surface wrinkles, (4): cell surface pores, and (5): cell lysis

Salt stability of NCP1 peptide

The results of the effect of salts on the stability of NCP1 peptide showed that NCP1 peptide was not stable in SDB medium containing 150 mM NaCl and 1 mM MgCl2 and its MIC in medium containing NaCl salt was reported to be greater than 250 µg/mL and in medium containing MgCl2 salt was reported to be equal to 250 µg/mL (Table 7).

Table 7.

MIC (µg/ml) values ​​of NCP1 peptide against C. albicans in the presence of MgCl2 and NaCl salts

Condition SDB SDB + MgCl2 SDB + NaCl
MIC values 125 250 > 250
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Discussion

The use of computational biology methods and machine learning algorithms has been very useful in the discovery and design of antimicrobial, anticancer, and generally bioactive peptides from natural sources. Milk, as one of the richest natural sources, contains a large protein complex called casein, which was used in this study as a template protein for the design of the antimicrobial peptide NCP1 using a rational design approach. The CAMPR4 server was the basis for designing and optimizing antimicrobial peptides. To ensure reliable selection three models (SVM, RF, and ANN) were applied to natural and synthetic datasets. The goal was to identify peptides consistently scoring high across all models. The Rational Design process was used for the first time to modify all antimicrobial-classified peptides from CAMPR4. Duplicate sequences were removed, and unique sequences underwent four rounds of Rational Design to maintain similarity to their original versions. Further mutations were avoided to prevent excessive alterations. After reassessment, the top-scoring peptides were selected, and their physicochemical and biological properties were analyzed. A thorough screening process identified NCP1 as the most promising candidate.

NCP1 exhibited selective antifungal activity, effectively inhibiting C. albicans and C. krusei at a MIC of 125 µg/mL, while its MIC exceeded 500 µg/mL against A. niger, S. aureus, and P. aeruginosa. This indicates NCP1’s specificity as an antifungal agent, distinguishing it from broad-spectrum peptides. Such selectivity is advantageous as it reduces resistance risks in non-target organisms. In contrast, Kim et al. reported that LPcin-YK3, derived from bovine lactoferrin, showed stronger antibacterial activity (MIC = 0.62–1.25 µg/mL) than antifungal activity (C. albicans, MIC = 10 µg/mL). This highlights NCP1’s preference for fungal targets over bacterial ones (Kim et al. 2018).

NCP1 demonstrated rapid antifungal activity, eliminating C. albicans within 2–4 h at its MFC concentration and preventing regrowth for 24 h. Compared to fluconazole, which requires longer durations to inhibit ergosterol synthesis, NCP1 acted more efficiently through direct membrane disruption. After 4 h, fluconazole could not completely eradicate C. albicans, whereas NCP1 achieved full elimination in less time. Aguirre-Guataqui et al. studied the chimeric peptide C8, which, despite being effective at 200 µg/mL, required 48 h to reduce C. albicans SC5314 growth by 99% (Aguirre-Guataqui et al. 2022). This demonstrates NCP1’s superior speed in fungal eradication, likely due to its structural ability to penetrate membranes and induce rapid destruction.

NCP1 did not exhibit synergy with fluconazole or nystatin (FIC > 1, < 4.0), likely due to overlapping mechanisms. Both NCP1 and nystatin bind ergosterol, potentially leading to competitive inhibition, while fluconazole reduces ergosterol synthesis, altering membrane dynamics and reducing NCP1’s efficacy. Studies suggest that synergy is more evident when agents have distinct mechanisms. For instance, Iram et al. showed that peptides derived from bovine colostrum whey exhibited synergy with gentamicin and levofloxacin against resistant E. coli ESBL1384 (FIC = 0.5) (Iram et al. 2023). This synergy was attributed to peptide-induced membrane disruption and antibiotic interference with biochemical pathways.

One of our most important findings was the dose-independent effect of the NCP1 peptide observed in some assays. NCP1 effectively inhibited C. albicans biofilm formation in a dose-independent manner, achieving over 90% inhibition at MIC. Interestingly, at lower concentrations (0.48 µg/mL), NCP1 exhibited higher inhibition (about 32%) than at some higher concentrations. This behavior may be attributed to more complex interactions within the biofilm, particularly the possibility that at lower concentrations, NCP1 may have better penetration into deeper layers of the biofilm or may more effectively target specific phases or subpopulations of cells. Another possibility is that at higher concentrations, NCP1 may undergo aggregation, which could reduce its bioactivity. Unlike NCP1, Li Yufang et al. reported that BCp12, a milk-derived peptide, reduced S. aureus biofilms in a dose-dependent manner (61–84% inhibition at MIC and ½MIC) (Li et al. 2022b). NCP1’s unique behavior suggests advantages such as reduced toxicity, minimized resistance development, and enhanced efficacy at lower doses.

Docking studies confirmed NCP1’s binding affinity to ergosterol, supporting its role in fungal membrane disruption. Experimental results also validated NCP1’s mechanism of altering membrane permeability and disrupting integrity. However, NCP1 did not interact with chitin, indicating that its antifungal action does not rely on targeting fungal cell walls. Namvar Erbani et al. studied CMt1, another ergosterol-binding peptide, and found that its MIC against C. albicans significantly increased (> 1000 µg/mL) when excess ergosterol was present, neutralizing its antifungal effect (Namvar Erbani et al. 2021). This confirms ergosterol as a key target for NCP1’s antifungal mechanism.

NCP1 exhibited minimal hemolysis, with only 2.2% hemolysis at 500 µg/mL, demonstrating its high safety profile. At lower concentrations (0.48 µg/mL), hemolysis remained below 1%. In comparison, Aguirre-Guataqui et al. reported that the chimeric peptides C6 caused 2% hemolysis at 25–100 µg/mL, C9 caused 2–11% hemolysis at 13–50 µg/mL, and C1 showed 5% hemolysis at 100–200 µg/mL (Aguirre-Guataqui et al. 2022). Although these peptides have different MIC values compared to NCP1, and a direct comparison of safety dose is not possible without evaluating their therapeutic index, the data still indicate that NCP1 causes very low hemolysis even at much higher concentrations, supporting its potential as a safe therapeutic candidate.

NCP1 not only disrupted fungal membranes via ergosterol binding but also interacted with DNA. This suggests at least a dual mechanism, where NCP1 disrupts membranes and simultaneously interferes with nucleic acids, leading to cell death. FE-SEM images revealed pore formation on fungal cells, supporting NCP1’s interaction with membranes through models such as barrel-stave or carpet mechanisms. NCP1’s effects included osmotic imbalance, cellular shrinkage, and leakage of ions, ultimately leading to membrane collapse and fungal death. Additionally, an increase in extracellular nucleic acids indicated severe membrane damage, allowing large molecules like RNA and DNA to escape. NCP1’s ability to cause irreversible cell destruction reduces the likelihood of resistance development. Given the rising resistance of fungi to conventional treatments, antimicrobial peptides like NCP1 offer promising alternatives for fungal control. Beyond pharmaceuticals, NCP1 could be useful in agricultural and food industries to prevent fungal contamination. Wang et al. found that CAMP211-225, a peptide derived from human milk casein, functioned solely through membrane disruption without interacting with DNA (Wang et al. 2020). This contrasts with NCP1’s dual mechanism, highlighting its broader antifungal potential.

NCP1’s antimicrobial activity was unstable in saline environments, indicating its sensitivity to ionic conditions. This was evident in MIC assays, where the MIC for S. aureus and P. aeruginosa exceeded 500 µg/mL. The MHB medium used in these tests contained high salt concentrations, which may have contributed to the reduced efficacy compared to the results observed in the SDB medium against fungi. Omidbakhsh Amiri et al. reported similar findings, where divalent cations such as magnesium and calcium significantly reduced peptide activity. Specifically, αs165-181’s activity dropped to 1.81% and 6.66% in the presence of 5 mM magnesium and calcium, and at 10 mM, its activity was almost eliminated (Omidbakhsh Amiri et al. 2021). These findings highlight the need for stability improvements to enhance NCP1’s therapeutic potential.

Conclusion

Since milk is a rich source of bioactive peptides, the results indicated that casein-derived peptides could possess strong antimicrobial properties. In this study, bioinformatics tools were used to analyze antimicrobial peptides derived from bovine casein protein. The peptide NCP1 demonstrated significant antifungal activity, especially against yeast-like fungi such as Candida albicans and Candida krusei. This suggests its potential for developing targeted treatments for fungal infections. Beyond its antimicrobial effects, this peptide exhibited multiple beneficial properties, including the ability to inhibit fungal biofilms, bind to fungal ergosterol, and induce notable morphological changes in C. albicans, such as pore formation, cell shrinkage, and lysis. Importantly, NCP1 showed no toxicity toward red blood cells and demonstrated DNA-binding capability. However, a key limitation of this peptide is its low stability in varying salt concentrations, which could pose challenges for its clinical application. Overall, the findings highlight milk as a valuable source of bioactive peptides with potential applications in antimicrobial therapies. Given the stability challenges of these peptides, further experimental studies are crucial to enhance their stability and optimize their therapeutic dosage.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (48.1KB, xlsx)
Supplementary Material 2 (511.2KB, docx)

Acknowledgements

We also thank all the staff of the Medical Biotechnology Department and the Comprehensive Research Laboratory of Semnan University of Medical Sciences.

Author contributions

S.R.P. Writing the manuscript draft, data collection, and analysis. K.V. Thesis supervisor. B.A. Thesis advisor. H. M. Thesis supervisor, conceptualizing, designing, and study implementation, data collection and analysis, writing and editing the manuscript. E.G. Collaboration in antimicrobial tests.

Funding

The authors are grateful to the Vice Chancellery for Research and Technology of Kermanshah University of Medical Sciences for financial support in grant number 4020586.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of interest

The authors declare no competing interests.

Consent for publication

Not applicable.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Kamal Veisi, Email: k.veissie@gmail.com.

Hamid Madanchi, Email: hamidmadanchi@yahoo.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (48.1KB, xlsx)
Supplementary Material 2 (511.2KB, docx)

Data Availability Statement

No datasets were generated or analysed during the current study.

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