Screening Of Peptides Research Articles

Dual antibacterial mechanism of [K4K15]CZS-1 against Salmonella Typhimurium: a membrane active and intracellular-targeting antimicrobial peptide.

Salmonella genus is a leading cause of food-borne infections with strong public health impact and economic ramifications. The development of antimicrobial resistance added complexity to this scenario and turned the antibiotic drug discovery into a highly important challenge. The screening of peptides has served as a successful discovery platform to design new antibiotic candidates. Motivated by this, the antimicrobial and cytotoxic properties of three cruzioseptins against Salmonella Typhimurium and RAW 264.7 murine macrophage cells, respectively, were investigated. [K4K15]CZS-1 was the most potent antimicrobial peptide identified in the screening step with a minimum inhibitory concentration (MIC) of 16 μg/mL (7.26 μM) and moderate cytotoxicity. From a structural point of view, in vitro and in silico techniques evidenced that [K4K15]CZS-1 is a α-helical cationic antimicrobial peptide. In order to capture mechanistic details and fully decipher their antibacterial action, we adopted a multidimensional approach, including spectroscopy, electron microscopy and omics analysis. In general lines, [K4K15]CZS-1 caused membrane damage, intracellular alterations in Salmonella and modulated metabolic pathways, such as the tricarboxylic acid (TCA) cycle, fatty acid biosynthesis, and lipid metabolism. Overall, these findings provide deeper insights into the antibacterial properties and multidimensional mode of action of [K4K15]CZS-1 against Salmonella Typhimurium. In summary, this study represents a first step toward the screening of membrane-acting and intracellular-targeting peptides as potential bio-preservatives to prevent foodborne outbreaks caused by Salmonella.

Encoding Molecular Docking for Quantum Computers.

Molecular docking is important in drug discovery but is burdensome for classical computers. Here, we introduce Grid Point Matching (GPM) and Feature Atom Matching (FAM) to accelerate pose sampling in molecular docking by encoding the problem into quadratic unconstrained binary optimization (QUBO) models so that it could be solved by quantum computers like the coherent Ising machine (CIM). As a result, GPM shows a sampling power close to that of Glide SP, a method performing an extensive search. Moreover, it is estimated to be 1000 times faster on the CIM than on classical computers. Our methods could boost virtual drug screening of small molecules and peptides in future.

Screening of novel DPP-IV inhibitory peptides derived from bovine milk proteins using a peptide array platform

Dipeptidyl peptidase IV (DPP-IV) has become an important target in the prevention and treatment of diabetes. Although many DPP-IV inhibitory peptides have been identified by a general approach involving the repeated fractionation of food protein hydrolysates, the obtained results have been dependent on the content of each peptide and fractionation conditions. In the present study, a peptide array that provides comprehensive assays of peptide sequences was used to identify novel DPP-IV inhibitory peptides derived from bovine milk proteins; these peptides were then compared with those identified using the general approach. While the general approach identified only known peptides that were abundant in the hydrolysate, the peptide array-based approach identified 10 novel DPP-IV inhibitory peptides, all of which had proline at the second residue from the N-terminus. The proper or combined use of these two approaches, which have different advantages, will enable the efficient development of novel bioactive foods and drugs.

Virtual screening and structure optimization of xanthine oxidase inhibitory peptides from whole protein sequences of Pacific white shrimp via molecular docking.

Xanthine oxidase (XO) inhibitory peptides are safer than conventional pharmacological therapy in relieving hyperuricemia. However, traditional enzymatic hydrolysis, separation, and purification techniques for bio-active peptide preparation are time-consuming, inefficient, and labor-intensive. In this study, molecular docking and BLAST were used to virtually screen XO inhibitory peptides from whole protein sequences of Pacific white shrimp according to the bio-active peptides database, and the structure of peptides was optimized based on the structure-effective relationship. Seven new XO inhibitory peptides were virtual screened rapidly from Pacific white shrimp, and YNITGW (IC50=9.78±0.13mM) showed the strongest activity. The results of YNITGW optimization showed that the insertion of Trp residue in the middle position of peptides could effectively enhance the activity. This study revealed that screening and optimizing peptides by molecular docking were a novel and feasible method to obtain bio-active peptides.

ASynPEP-DB: a database ofbiogenic peptides forinhibiting α-synuclein aggregation.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder, yet effective treatments able to stop or delay disease progression remain elusive. The aggregation of a presynaptic protein, α-synuclein (aSyn), is the primary neurological hallmark of PD and, thus, a promising target for therapeutic intervention. However, the lack of consensus on the molecular properties required to specifically bind the toxic species formed during aSyn aggregation has hindered the development of therapeutic molecules. Recently, we defined and experimentally validated a peptide architecture that demonstrated high affinity and selectivity in binding to aSyn toxic oligomers and fibrils, effectively preventing aSyn pathogenic aggregation. Human peptides with such properties may have neuroprotective activities and hold a huge therapeutic interest. Driven by this idea, here, we developed a discriminative algorithm for the screening of human endogenous neuropeptides, antimicrobial peptides and diet-derived bioactive peptides with the potential to inhibit aSyn aggregation. We identified over 100 unique biogenic peptide candidates and ensembled a comprehensive database (aSynPEP-DB) that collects their physicochemical features, source datasets and additional therapeutic-relevant information, including their sites of expression and associated pathways. Besides, we provide access to the discriminative algorithm to extend its application to the screening of artificial peptides or new peptide datasets. aSynPEP-DB is a unique repository of peptides with the potential to modulate aSyn aggregation, serving as a platform for the identification of previously unexplored therapeutic agents. Database URL: https://asynpepdb.ppmclab.com/.

Rapid liposomal formulation for nucleolin targeting to rhabdomyosarcoma cells

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma. More effective and less toxic therapies are urgently needed for high-risk patients. Peptide-guided targeted drug delivery can increase the therapeutic index of encapsulated drugs and improve patients’ well-being. To apply this strategy to RMS, we identified the peptide F3 in a screening for peptides binding to RMS cells surface. F3 binds to nucleolin, which is present on the surface of RMS cells and is abundantly expressed at the mRNA level in RMS patients’ biopsies compared to healthy tissues. We developed a rapid microfluidic formulation of F3-decorated PEGylated liposomes and remote loading of the chemotherapeutic drug vincristine. Size, surface charge, drug loading and retention of targeted and control liposomes were studied. Enhanced cellular binding and uptake were observed in three different nucleolin-positive RMS cell lines. Importantly, F3-functionalized liposomes loaded with vincristine were up to 11 times more cytotoxic than non-targeted liposomes for RMS cell lines. These results demonstrate that F3-functionalized liposomes are promising for targeted drug delivery to RMS and warrant further in vivo investigations.

Let There Be Light: Genome Reduction Enables Bacillus subtilis to Produce Disulfide-Bonded Gaussia Luciferase.

Bacillus subtilis is a major workhorse for enzyme production in industrially relevant quantities. Compared to mammalian-based expression systems, B. subtilis presents intrinsic advantages, such as high growth rates, high space-time yield, unique protein secretion capabilities, and low maintenance costs. However, B. subtilis shows clear limitations in the production of biopharmaceuticals, especially proteins from eukaryotic origin that contain multiple disulfide bonds. In the present study, we deployed genome minimization, signal peptide screening, and coexpression of recombinant thiol oxidases as strategies to improve the ability of B. subtilis to secrete proteins with multiple disulfide bonds. Different genome-reduced strains served as the chassis for expressing the model protein Gaussia Luciferase (GLuc), which contains five disulfide bonds. These chassis lack extracellular proteases, prophages, and key sporulation genes. Importantly, compared to the reference strain with a full-size genome, the best-performing genome-minimized strain achieved over 3000-fold increased secretion of active GLuc while growing to lower cell densities. Our results show that high-level GLuc secretion relates, at least in part, to the absence of major extracellular proteases. In addition, we show that the thiol-disulfide oxidoreductase requirements for disulfide bonding have changed upon genome reduction. Altogether, our results highlight genome-engineered Bacillus strains as promising expression platforms for proteins with multiple disulfide bonds.

Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids

Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing post-translational modifications (PTMs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the intrinsic solubility of mAA-containing peptides in aqueous solution at room temperature. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different small-size mAAs for a total number of 37 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides and confirm that our method can accurately assess the solubility of peptides containing mAAs. This method is available as a web server at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm.

Construction of Nonnatural Cysteine-Cross-Linked Phage Libraries.

Phage display is a powerful technique for rapid construction and screening of peptide libraries with over 109 sequence diversity. The M13 bacteriophage genome can be edited to incorporate randomized amino acids, which will be displayed on its minor coat protein (pIII). To enable screening of nonnatural cyclic peptides on phage, the minor coat protein can be modified with a chemical cross-linker. By taking advantage of the nucleophilicity and low abundance of free cysteines on phage, a variety of cysteine cross-linkers can be installed on the pIII protein. Here, we describe the construction of a chemically modified cyclic phage library through a cysteine cross-linking reagent, 1,3-dichloroacetone (DCA).

Peptidomic analysis of follicular fluid in patients with polycystic ovarian syndrome.

Objective: The aim of this study was to analyze and compare the differential expression of peptides within the follicular fluid of polycystic ovary syndrome (PCOS) patients versus normal women by using peptidomics techniques. The underlying mechanisms involved in PCOS pathogenesis will be explored, together with screening and identification of potential functional peptides via bioinformatics analysis. Materials and methods: A total of 12 patients who underwent in vitro fertilization and embryo transfer (IVF-ET) at the Reproductive Medicine Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from 1 September 2022 to 1 November 2022 were included in this study. The follicular fluid of PCOS patients (n = 6) and normal women (n = 6) were collected. The presence and concentration differences of various peptides were detected by the LC-MS/MS method. GO and KEGG analysis were performed on the precursor proteins of the differentially-expressed peptides, and protein network interaction analysis was carried out to identify functionally-relevant peptides among the various peptides. Results: A variety of peptides within the follicular fluid of PCOS versus normal patients were detected by peptidomics techniques. Altogether, 843 upregulated peptides and 236 downregulated peptides were detected (absolute fold change ≥2 and p < 0.05). Of these, 718 (718 = 488 + 230) peptides were only detected in the PCOS group, while 205 (205 = 174 + 31) were only detected in the control group. Gene Ontology enrichment and pathway analysis were performed to characterize peptides through their precursor proteins. We identified 18 peptides from 7 precursor proteins associated with PCOS, and 4 peptide sequences were located in the functional domains of their corresponding precursor proteins. Conclusion: In this study, differences in the follicular development of PCOS versus normal patients were revealed from the polypeptidomics of follicular development, which thus provided new insights for future studies on the pathological mechanisms of PCOS development.

Increased Expression Levels of Thermophilic Serine Protease TTHA0724 through Signal Peptide Screening in Bacillus subtilis and Applications of the Enzyme.

The thermostable protease TTHA0724 derived from Thermus thermophilus HB8 is an ideal industrial washing enzyme due to its thermophilic characteristics; although it can be expressed in Escherichia coli via pET-22b, high yields are difficult to achieve, leading to frequent autolysis of the host. This paper details the development of a signal peptide library in the expression system of B. subtilis and the optimization of signal peptides for enhanced extracellular expression of TTHA0724. When B. subtilis was used as the host and the optimized signal peptide was used, the expression level of TTHA0724 was 16.7 times higher compared with E. coli. B. subtilis as an expression host does not change the characteristics of TTHA0724. The potential application fields of TTHA0724 are studied. TTHA0724 can be used as a detergent additive at 60 °C, which can sterilize and eliminate mites while thoroughly cleaning protein stains. Soybean meal enzymatic hydrolysis with TTHA0724 at a high temperature produced a higher content of antioxidant peptides. These results indicate that TTHA0724 has great potential for industrial applications.

Identification and Verification of Novel Umami Peptides Isolated from Hybrid Sturgeon Meat (Acipenser baerii × Acipenser schrenckii).

To explore the umami mechanism in sturgeon meat, five peptides (ERRY, VRGPR, LKYPLE, VKKVFK, and YVVFKD) were isolated and identified by ultrafiltration, gel filtration chromatography, and UPLC-QTOF-MS/MS. The omission test confirmed that the five umami peptides contributed to the umami taste of sturgeon meat. Also, the peptides had the double effective role of enhancing both umami and saltiness. The threshold of ERRY was only 0.031, which exceeded most umami peptides in the last 3 years. Molecular docking results showed that five peptides could easily bind to Gly167, Ser170, and Try218 residues in T1R3 through hydrogen bonds and electrostatic interactions. Furthermore, molecular dynamics simulations indicated that hydrogen bonds and hydrophobic interactions were the main intermolecular interaction forces. This study could contribute to revealing the umami taste mechanism of sturgeon meat and provide new insights for effective screening of short umami peptides.

Design and In-silico Screening of Short Antimicrobial Peptides (AMPs) as Anti-Tubercular Agents Targeting INHA

Introduction: Tuberculosis has been studied as a potentially serious bacterial infection affecting the lung caused by Mycobacterium tuberculosis. In addition to its severe impact on health, resistance to existing drugs has also been seen as a rising concern in the space of medicinal solutions. Therapeutic peptides have the potential to complement existing drug designs to provide effective outcomes against Mycobacterium tuberculosis-resistant strains. Methods: This study illustrated a computational approach to design and test peptides against NADHdependent enoyl-acyl carrier protein reductase of Mycobacterium tuberculosis. A human antimicrobial peptide LL-37 was used as a template, and a further 6 peptides were designed, and their binding and interactions against NADH-dependent enoyl-acyl carrier protein reductase were examined. Further, toxicity, immunogenicity, and a broad spectrum of physicochemical properties were calculated to evaluate the therapeutic and safety profile of these peptides. Results: These peptides were structurally modelled and docked with the protein to determine their binding poses and affinity. The molecular interaction of LL-37 with protein was treated as a reference to evaluate the effectiveness of designed peptides. Solvent accessible surface area (SASA) and ΔG binding free energy of docked complexes assisted in the ranking of these peptides. Eventually, peptides P1: LLGDFFRKSKEK, P3: LLFGDRFLLKEK and P7: LLGDFFRLLKEK were selected for 100 ns molecular dynamic simulation as they showed predicted dissociation constants of 8.7×10-4 M, 3.3×10-4 M and 1.2×10-4 M, respectively. These peptides showed direct hydrogen bond formation with ILE21 and LYS165, which are critical active site residues of the protein. The structural variation pattern collected from the MD simulation suggested a strong and stable binding of P3 and P1 with the protein with RMSD 4-5 Å with the starting conformation under the non-fluctuating state. These two peptides showed relatively similar binding results compared with the control peptide LL-37. Comprehensive structural analysis was performed for the middle structures of the most populated cluster generated from 100 ns MD simulation trajectory. Conclusion: Later, MMPBSA binding energies of these structures were computed, where the average binding free energies of P1, P3, and P7 peptides were -146.93 kcal/mole, -161.16 kcal/mole, and - 151.44 kcal/mole, respectively. These energies suggested that P3 is strongly bound to the active site of NADH-dependent enoyl-acyl carrier protein reductase. Overall, this study proposed the application of these peptides as a possible therapeutic solution to inhibit the growth of Mycobacterium tuberculosis.

Screening and Activity Analysis of α-Glucosidase Inhibitory Peptides Derived from Coix Seed Prolamins Using Bioinformatics and Molecular Docking.

Hydrolysates of coix seed prolamins (CHPs) have an excellent hypoglycemic effect and can effectively inhibit α-glucosidase, which is the therapeutic target enzyme for type 2 diabetes mellitus. However, its hypoglycemic components and molecular mechanisms remain unclear, and its stability in food processing needs to be explored. In this study, four potential α-glucosidase inhibitory peptides (LFPSNPLA, FPCNPLV, HLPFNPQ, LLPFYPN) were identified and screened from CHPs using LC-MS/MS and virtual screening techniques. The results of molecular docking showed that the four peptides mainly inhibited α-glucosidase activity through hydrogen bonding and hydrophobic interactions, with Pro and Leu in the peptides playing important roles. In addition, CHPs can maintain good activity under high temperatures (40~100 °C) and weakly acidic or weakly alkaline conditions (pH 6.0~8.0). The addition of glucose (at 100 °C) and NaCl increased the inhibitory activity of α-glucosidase in CHPs. The addition of metal ions significantly decreased the inhibitory activity of α-glucosidase by CHPs, and their effects varied in magnitude with Cu2+ having the largest effect followed by Zn2+, Fe3+, K+, Mg2+, and Ca2+. These results further highlight the potential of CHPs as a foodborne hypoglycemic ingredient, providing a theoretical basis for the application of CHPs in the healthy food industry.

Walnut Protein Peptides Ameliorate DSS-Induced Ulcerative Colitis Damage in Mice: An in Silico Analysis and in Vivo Investigation.

Walnut (Juglans regia L.) is a food with food-medicine homology, whose derived protein peptides have been shown to have anti-inflammatory activity in vitro. However, the effects and mechanisms of walnut protein peptides on ulcerative colitis (UC) in vivo have not been systematically and thoroughly investigated. In this study, we applied virtual screening and network pharmacology screening of bioactive peptides to obtain three novel WPPs (SHTLP, HYNLN, and LGTYP) that may alleviate UC through TLR4-MAPK signaling. In vivo studies have shown that WPPs improve intestinal mucosal barrier dysfunction and reduce inflammation by inhibiting activation of the TLR4-MAPK pathway. In addition, WPPs restore intestinal microbial homeostasis by reducing harmful bacteria (Helicobacter and Bacteroides) and increasing the relative abundance of beneficial bacteria (Candidatus_Saccharimonas). Our study showed that the WPPs obtained by virtual screening were effective in ameliorating colitis, which has important implications for future screening of bioactive peptides from medicinal food homologues as drugs or dietary supplements.

Coarse-grained molecular dynamics-guided immunoinformatics to explain the binder and non-binder classification of Cytotoxic T-cell epitope for SARS-CoV-2 peptide-based vaccine discovery.

Epitope-based peptide vaccine can elicit T-cell immunity against SARS-CoV-2 to clear the infection. However, finding the best epitope from the whole antigen is challenging. A peptide screening using immunoinformatics usually starts from MHC-binding peptide, immunogenicity, cross-reactivity with the human proteome, to toxicity analysis. This pipeline classified the peptides into three categories, i.e., strong-, weak-, and non-binder, without incorporating the structural aspect. For this reason, the molecular detail that discriminates the binders from non-binder is interesting to be investigated. In this study, five CTL epitopes against HLA-A*02:01 were identified from the coarse-grained molecular dynamics-guided immunoinformatics screening. The strong binder showed distinctive activities from the non-binder in terms of structural and energetic properties. Furthermore, the second residue from the nonameric peptide was most important in the interaction with HLA-A*02:01. By understanding the nature of MHC-peptide interaction, we hoped to improve the chance of finding the best epitope for a peptide vaccine candidate.

Flow cytometry-based high-throughput screening of synthetic peptides for palladium adsorption

Conventionally, the measurement of metal ion adsorption capacity in biosorbent relies on expensive and time-consuming ICP-OES technique. Herein, a semi-quantitative method to measure Pd(II) adsorption capacity of single cells has been presented by analyzing side scatter (SSC) intensity in flow cytometry. Within the sensitive range and applicable conditions, excellent linearity correlation (R2 ranges from 0.89 to 0.96) between the amount of Pd(II) absorbed on yeast and the fold increase in SSC intensity has been observed. Using this method, six strains with high Pd adsorption capacities have sorted from a yeast library with metal-binding peptides displayed (up to 107 strains) based on SSC signal intensity. The optimal peptide (EF1) displayed on yeast and E. coli surface demonstrated Pd adsorption improvements of ∼32% and ∼200%, respectively. In summary, our study proposes an alternative high-throughput method for analyzing the Pd(II) adsorption capacity of individual yeast cells, enabling the screening of specific peptides/proteins with high Pd(II) affinity from extensive libraries.

PET imaging with [68Ga]-labeled TGFβ-targeting peptide in a mouse PANC-1 tumor model.

Transforming growth factor β (TGFβ) is upregulated in many types of tumors and plays important roles in tumor microenvironment construction, immune escape, invasion, and metastasis. The therapeutic effect of antibodies and nuclide-conjugated drugs targeting TGFβ has not been ideal. Targeting TGFβ with small-molecule or peptide carriers labeled with diagnostic/therapeutic nuclides is a new development direction. This study aimed to explore and confirm the imaging diagnostic efficiency of TGFβ-targeting peptide P144 coupled with [68Ga] in a PANC-1 tumor model. TGFβ-targeting inhibitory peptide P144 with stable activity was prepared through peptide synthesis and screening, and P144 was coupled with biological chelator DOTA and labeled with radionuclide [68Ga] to achieve a stable TGFβ-targeting tracer [68Ga]Ga-P144. This tracer was first used for positron emission tomography (PET) molecular imaging study of pancreatic cancer in a mouse PANC-1 tumor model. [68Ga]Ga-P144 had a high targeted uptake and relatively long uptake retention time in tumors and lower uptakes in non-target organs and backgrounds. Target pre-blocking experiment with the cold drug P144-DOTA demonstrated that the radioactive uptake with [68Ga]Ga-P144 PET in vivo, especially in tumor tissue, had a high TGFβ-targeting specificity. [68Ga]Ga-P144 PET had ideal imaging efficiency in PANC-1 tumor-bearing mice, with high specificity in vivo and good tumor-targeting effect. [68Ga]Ga-P144 has relatively high specificity and tumor-targeted uptake and may be developed as a promising diagnostic tool for TGFβ-positive malignancies.

Prediction of Cholecystokinin-Secretory Peptides Using Bidirectional Long Short-term Memory Model Based on Transfer Learning and Hierarchical Attention Network Mechanism.

Cholecystokinin (CCK) can make the human body feel full and has neurotrophic and anti-inflammatory effects. It is beneficial in treating obesity, Parkinson's disease, pancreatic cancer, and cholangiocarcinoma. Traditional biological experiments are costly and time-consuming when it comes to finding and identifying novel CCK-secretory peptides, and there is an urgent need to develop a new computational method to predict new CCK-secretory peptides. This study combines the transfer learning method with the SMILES enumeration data augmentation strategy to solve the data scarcity problem. It establishes a fusion model of the hierarchical attention network (HAN) and bidirectional long short-term memory (BiLSTM), which fully extracts peptide chain features to predict CCK-secretory peptides efficiently. The average accuracy of the proposed method in this study is 95.99%, with an AUC of 98.07%. The experimental results show that the proposed method is significantly superior to other comparative methods in accuracy and robustness. Therefore, this method is expected to be applied to the preliminary screening of CCK-secretory peptides.

Investigation of Peptides for Molecular Recognition of C-Reactive Protein-Theoretical and Experimental Studies.

We investigate the interactions between C-reactive protein (CRP) and new CRP-binding peptide materials using experimental (biological and physicochemical) methods with the support of theoretical simulations (computational modeling analysis). Three specific CRP-binding peptides (P2, P3, and P9) derived from an M13 bacteriophage have been identified using phage-display technology. The binding efficiency of the peptides exposed on phages toward the CRP protein was demonstrated via biological methods. Fibers of the selected phages/peptides interact differently due to different compositions of amino acid sequences on the exposed peptides, which was confirmed by transmission electron microscopy. Numerical and experimental studies consistently showed that the P3 peptide is the best CRP binder. A combination of theoretical and experimental methods demonstrates that identifying the best binder can be performed simply, cheaply, and fast. Such an approach has not been reported previously for peptide screening and demonstrates a new trend in science where calculations can replace or support laborious experimental techniques. Finally, the best CRP binder─the P3 peptide─was used for CRP recognition on silicate-modified indium tin oxide-coated glass electrodes. The obtained electrodes exhibit a wide range of operation (1.0-100 μg mL-1) with a detection limit (LOD = 3σ/S) of 0.34 μg mL-1. Moreover, the dissociation constant Kd of 4.2 ± 0.144 μg mL-1 (35 ± 1.2 nM) was evaluated from the change in the current. The selectivity of the obtained electrode was demonstrated in the presence of three interfering proteins. These results prove that the presented P3 peptide is a potential candidate as a receptor for CRP, which can replace specific antibodies.