Biological characterization of natural peptide BcI-1003 from Boana cordobae (anura): role in Alzheimer’s Disease and microbial infections.

doi:10.21203/rs.3.rs-2109194/v1

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Biological characterization of natural peptide BcI-1003 from Boana cordobae (anura): role in Alzheimer’s Disease and microbial infections.

https://doi.org/10.21203/rs.3.rs-2109194/v1

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Nature continues to be one of the most important sources of molecules for the development of novel therapeutic agents. The skin of anuran’s (frogs and toads) is a rich source of peptides with a great importance in the search of bioactive agents applying to human health. Alzheimer's disease (AD) is a complex disease associated with numerous pathological pathways, making their simultaneous modulation necessary. On the other hand, the increasing bacterial resistance against conventional antibiotics has made it essential to search for new antimicrobial drugs with different modes of action. Here in we report the natural peptide BcI-1003, isolated from Boana cordobae amphibian skin, as an agent capable to act on three key therapeutic targets of AD, inhibiting the activity of BChE (IC₅₀ = 669 µM) and MAO-B (IC₅₀ = 570 µM) enzymes, and showing a powerful and rapid antioxidant activity (EC₅₀ = 7.24 µM). Besides, BcI-1003 showed antimicrobial activity against clinically drug-resistant gram-positive and gram-negative bacterial strains, with MIC values ranging from 8 to 127 µM against Staphylococcus aureus MR-1; S. aureus MR-2 and Escherichia coli MDR-1.

Natural peptides

Alzheimer´s Disease

Antimicrobial peptides

Anuran amphibians

Nature continues to be one of the most important sources of molecules for the development of novel therapeutic agents (Newman and Cragg 2012). Additionally, the relevance of peptides in drug discovery programs has significantly increased in the past years (Albericio and Kruger 2012; Kaspar and Reichert 2013; de la Torre and Albericio 2018). Antimicrobial peptides (AMPs) are produced by a variety of living organisms, including fungi, bacteria, plants, vertebrates, and invertebrates. These natural molecules represent the first line of defense against pathogens (Bulet et al. 2004). The skin of amphibians serves as a complex defense system, producing a large variety of such bioactive substances, including AMPs (Zasloff 2002; Conlon et al. 2004), neurotoxic peptides (You et al. 2009), gastric disturbance peptides (Bevins and Zasloff 1990) and alkaloids (Daly et al. 2005). These molecules are stored in special glands called granular glands or poison glands scattered over the amphibian skin, and when the animal is injured or alarmed, its content is rapidly released as a defense weapon (Tyler et al. 2007).

Alzheimer’s disease (AD) is a neurodegenerative disorder of the brain, affecting almost 48 million older adults, with unparalleled growth and projections of 131.5 million older adults affected by 2050 (Venkatraghavan et al. 2019). Although the exact etiology is still not fully understood, several factors including low levels of acetylcholine (ACh), the formation of β-amyloid (Aβ) deposits and oxidative stress, demonstrated to play significant roles in its pathogenesis (Tang et al. 2012). ACh is hydrolysed by acetylcholinesterase (AChE) or butyrylcholinesterase (BChE) enzymes (Greig et al. 2002). Nowadays, cholinesterases (ChEs) inhibitors are the mainly symptomatic treatment indicated for AD, and the efforts in the development of new drugs continue focusing on this strategy (Bortolami et al. 2021). Also, the use of antioxidant agents that reduce the toxic effects of oxidative stress produced by the Aβ aggregates is capable of delaying and preventing these types of disorders (Santos et al. 2016). Furthermore, the inhibition of monoamine oxidase B (MAO-B) enzyme has also received increasing attention in recent years due to its role in improving the AD symptoms (Knez et al. 2017). Because of this, in order to modulate different pathological pathways simultaneously, the development of anti-AD drugs is now focused on a multi-target directed ligands (MTDLs) strategy. Chronic systemic bacterial infections may also be involved in the pathogenesis and progression of AD through a persistent inflammatory response in the brain, that produces upregulation of Aβ production (Little et al. 2004; Zhu et al. 2010). These conditions initiate the amyloid cascade leading to the self-aggregation of Aβ amyloid peptide as an antimicrobial response. Therefore, AMPs could delay the progression of AD, preventing bacterial infection and consequently the activation of the amyloid cascade (Moir et al. 2018).

On a separate note, the rise of bacterial resistance to conventional antibiotics is one of the major causes of high mortality rates and inefficient therapy. Regarding this, intensive research efforts are being channeled into the development of new antimicrobials agents (Costa et al. 2019; Han et al. 2021). Traditionally, the main targets for antibacterial drugs have been the bacterial cell walls and protein synthesis (Ye et al. 2020).

Argentina is a naturally rich area of amphibian species. Hylidae is a wide-spread anurans family well represented in the new world, with over 900 species (Faivovich et al. 2005). Boana cordobae (anura: Hylidae) (Faivovich et al. 2004) is an endemic species that inhabit only in the top of the mountain systems of Sierras Grandes, Sierra de Comechingones, and Sierras de San Luis, Argentina (Bionda et al. 2011). Previous work carried out by our research group, allowed to report the bioactivity of the B. cordobae complete skin extract (Spinelli et al. 2019). Herein we synthetized the peptide BcI-1003 isolated from B. cordobae by solid phase Fmoc peptide synthesis and carried out an in-depth biological characterization. BcI-1003 showed the capability to act against three AD targets (BChE, MAO-B and antioxidant) and also as an antimicrobial agent for gram positive and negative resistant bacteria strains.

Secondary structure prediction

The amino acid sequences was analyzed through web resources for 3D structure prediction named PEP-FOLD (http://bioserv.rpbs.univ-paris-diderot.fr/cgi-bin/PEP-FOLD). This approach allowed us to obtain a predictive structural model for the studied amino acid sequence (Camproux et al. 1999; Camproux et al. 2004; Zhang et al. 2008; Yang and Chen 2011).

Peptide Synthesis

Peptide was synthesized by Fmoc solid-phase peptide synthesis (SPPS) as C-terminal amides. Couplings were performed using diisopropylethylamine (DIEA) and N-[(1H-benzotriazole-1-yl)(dimethylamino)methylene]-N-methylmethanaminiumhexafluoropho sphate N-oxide (HBTU). Fmoc removal was achieved with 20% piperidine in DMF (v/v). Final cleavage from the resin was achieved by a mixture of TFA /H₂O /1,2-ethanedithiol (EDT)/triisopropylsilane (TIS) (94.5: 2.5: 2.5: 0.5) (v/v). After 3 h, the resin was filtered off, and the crude peptide was precipitated in dry cold diethyl ether, centrifuged, and washed several times with cold diethyl ether until the scavengers were removed. The product was then lyophilized twice. The Synthetic peptide was purified by reverse phase HPLC using a C₁₈ Jupiter proteo phenomenex semi-preparative column (10 µm, 90 Å, 250 x 10 mm) with a gradient of 5–70% acetonitrile in water containing 0.1% trifluoroacetic acid. Then, these analogs were analyzed by analytical C₁₈ RP-HPLC.

Cholinesterases Inhibition assay

The cholinesterase inhibition was determined following Ellman’s method with modifications (Ellman et al. 1961). Briefly, increasing concentrations of the peptide were prepared in phosphate buffer (pH 7.5). For AChE, 50 µL of extract were added to a 96 wells microplate followed by 50 µL of Electrophorus electricus AChE (0.25 U/mL) in phosphate buffer (pH 7.5). After 30 min of incubation at 25°C, 100 µl of a solution of 5,5′-dithiobis (2-nitrobenzoic acid) (DTNB) (0.2 mM) and acetylthiocholine iodide (ATCI) (0.24 mM) were added. The absorbance was measured at 405 nm by microplate reader Thermo Scientific FC. The same procedures were applied for BChE assay, with modification of the enzyme and substrate used, which were human serum BChE and S-butyrylthiocholine iodide (BTCI) (7 mM), respectively. In both cases, Rivastigmine was used as positive control. Percentage of inhibition was calculated as (1-EAS/EAB) x 100, where EAS and EAB represent the absorbance enzymatic activity of the sample and basal, respectively.

MAO-B inhibition assay

The inhibition of MAO-B (obtained from the mitochondrial fraction of rat brain) was determined following the method described by Soto-Otero et al. with slightly modification (Méndez-Álvarez et al. 1997). Briefly, 20 µL of increasing concentrations of the peptide in phosphate buffer were mixed with 45 µL of MAO-B. After 30 min of incubation at 30°C, 10 µL of Horse Radish Peroxidase (5 U/mL), 20 µL of a solution of benzylamine (20 mM) and 20 µL of a solution of o-dianisidine (5 mM) were added and incubated at 30°C for 60 min. Selegiline was used as positive control. The absorbance was measured at 405 nm. Percentage of inhibition was calculated as (1-EAS/EAB) x 100, EAS and EAB represent the absorbance enzymatic activity of the sample and basal, respectively.

Molecular dynamic and docking studies

The molecular model of the BcI-1003 obtained by the PepFold 3.5 server (http://bioserv.rpbs.univ-paris-diderot.fr/cgi-bin/PEP-FOLD) to predict its structure (Camproux et al. 1999; Camproux et al. 2004; Zhang et al. 2008; Yang and Chen 2011). Following molecular docking was performed both for BChE and MAO-B, in other to acquired knowledge about the interaction with the peptide. The protein structures were obtained from the Protein Data Bank, human butyrylcholinesterase 2PM8 (Sehnal and Bittrich 2021), and MAO-B 2V5Z (Binda et al. 2007). For BChE and MAO-B PDB ligands were removed, and polar hydrogens were added (Discovery Studio Visualizer 2021 – Biovia). The peptide was docked with each enzyme using HADDOCK 2.4 software (Dominguez et al. 2003; van Zundert et al. 2016). 10 independent runs of flexible docking calculations were performed, and all the predicted structures were clustered through a k-means clustering algorithm (k = 10) developed in the CPPTRAJ module of the Amber 18.0 package. Finally, the structure with the lowest cumulative distance to every other point within the most populated cluster was used to evaluate the ligand-protein interactions and generate a 2D interaction diagram with Discovery Studio Visualizer 2021 (BIOVIA). The resulting structures with the best score were promoted to the MD simulations. For this, initially, missing hydrogen atoms were added using LEaP from Amber 18.0 (Case et al. 2020), and ionizable residues were protonated according to their standard protonation state at pH 7.0. This structure was solvated with a periodic octahedral TIP3P water box with a margin distance of 10.0 Å. System charge was neutralized adding counterions. To perform these processes, tLEaP module of Amber 18.0 package and the ff14SB force-field were used (Maier et al. 2015). Equilibration and production: the system was prepared for the production run performing first a two-step energy minimization, a thermalization, and an equilibration run. Briefly, the solvent molecules were first relaxed around the complex, restraining its backbone with a harmonic restraint of 10 kcal/(mol Å2). Then, the geometry of the whole system was optimized without constraints. Finally, the temperature was slowly raised from 0 to 298 K before the 1ns equilibration run of constant temperature (Langevin thermostat) and pressure (Berendsen barostat) (Berendsen et al. 1984; Pastor et al. 1988), in which the system density was adjusted. The 100 ns production run was subsequently started using the GPU implementation of the PMEMD program (Götz et al. 2012; Salomon-Ferrer et al. 2013) in Amber18, with the same simulation conditions of the equilibration process, that included the use of the SHAKE algorithm (Miyamoto and Kollman 1992) for the constraining of the bonds involving hydrogens, periodic boundary conditions and the Ewald algorithm (de Souza and Ornstein 1997) for the inclusion of the long-range electrostatic interactions. Newton motion equations were integrated using a 2 fs timestep, and snapshots of the system were saved every 1 ps during all the production runs.

DPPH radical scavenging activity

The antioxidant activity was determined by 2,2'-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay according to the method of Memarpoor-Yazdi with minor modifications (Memarpoor-Yazdi et al. 2013). 0.4 mL of increasing concentrations of the peptide were mixed with 1.2 mL of methanol and 0.4 mL of DPPH (0.15 mM in methanol). The mixture was incubated for 30 min in the dark. Ascorbic acid was used as positive control. The absorbance of the resulting solution was measured at 517 nm in a microplate reader Thermo Scientific FC. Percentage of DPPH radical scavenging activity (RSA) was calculated as (1-As/Ab) x 100, As and Ab representing the absorbance of the sample and basal, respectively.

Antimicrobial activity

Minimal Inhibitory Concentration (MIC) determination against bacterial strains were performed by the broth microtiter dilution assay, according to the procedures proposed by R.E.W. Hancock Laboratory for testing antimicrobial peptides, with few modifications (Siano et al. 2011). The clinical isolated strains Staphylococcus aureus MR-1 and Staphylococcus aureus MR-2, both methicillin resistant; Escherichia coli MDR-1 resistant to ampicillin, cefazolin, ampicillin sulbactam and gentamicin and Klebsiella pneumoniae Kb-1 were used to these assays. All strains belong to the Culture Collection of Clinical Bacteriology Section of FBCB-UNL. All the strains were activated by culture (24 h at 37°C) in Mueller-Hinton Broth (MHB) (Biokar Diagnostics). Each inoculum was adjusted in order to achieve a cellular concentration of 5 x 10⁷ CFU/mL. All the peptides were dissolved in bovine serum albumin buffer with 0.01% acetic acid in order to favor their solubilization; 450 µL of each inoculum was added to 50 µL of peptide solution in serial 2-fold dilutions and were incubated for 18–24 h at 37 ºC. The MIC was determined as the lowest peptide concentration that inhibited the growth of each bacterial strain completely. The tests were done in triplicate. For determination of minimal bactericidal concentration (MBC), 10 µL from each tube without visible grown were taken and seeded on CLDE agar plaques and then were incubated for 24 h at 37°C. The lowest concentration of peptide without visible grown on the plaque was considered the MBC.

Circular Dichroism (CD) Analyses

Far-UV CD measurements were taken on a Jasco J-810 CD spectrometer (Tokyo, Japan) in a 0.1-cm path quartz curvet (Hellma, Mullheim, Germany) and recorded after the accumulation of five runs. CD analyses were recorded in the presence of dipalmitoylphosphatidylcholine (DPPC) and dipalmitoyl phosphatidylglycerol (DPPG) vesicles. For the preparation of small unilamellar vesicles (SUVs), the lipid dispersion in Milli Q H₂O was sonicated, using a tip-sonicator, until the solution became transparent. In all samples, the peptide concentration was 0.2 mg ⁄mL, and the final lipid concentration was 3 mM. To correct for background scattering caused by the vesicles, the spectrum of a single vesicle solution was subtracted from that of the peptide in the presence of vesicles. Additional spectra were obtained in the presence of Trifluoroethanol (TFE) [50% TFE (v⁄v)] and in H₂O (Sreerama et al. 2000, 2001).

Hemolytic Activity

The hemolytic activity was determined by previously reported methodology (Siano et al. 2011; Spinelli et al. 2020). Briefly, human erythrocytes were isolated from heparinized blood by centrifugation (1000 g for 10 min) after washing three times with saline solution. Erythrocyte solutions were prepared to a concentration of 0.4% (v⁄v) in isotonic saline solution. Test tubes containing 200 µL of erythrocyte solution were incubated at 37°C for 60 min with increasing concentrations of the peptide. After centrifugation at 1000 g for 5 min, the supernatant absorbance was measured at 405 nm. Lysis induced by 1% Triton X-100 was taken as 100%.

Data analysis

All experiments were assayed in triplicates. The statistical analysis was performed using the computing environment R (Team 2010). A confidence interval of 95% was considered. Furthermore, the package GRmetrics (Clark et al. 2017) from the Bioconductor project was used (Gentleman et al. 2004) for the creation of the dose-response models and the calculations of the IC₅₀. The plots were created with the package ggplot2 (Wickham 2016).

In this work we synthesized and performed an in-depth biological and biophysical characterization of the peptide BcI-1003 previously identified from B. cordobae specie (see supplementary and Figure S1). The synthesis was carried out using the solid phase synthesis by the Fmoc method, as C-terminal amide, given that amidation is a common feature of many AMPs isolated from frogs (Dourado et al. 2007; Gomes et al. 2007)

In silico analysis of structural, physicochemical and stability parameters of the synthetic peptide BcI-1003

The amino acid sequence and additional characteristics of peptide BcI-1003 are listed in Table 1. BcI-1003 consists of a polypeptide chain of 9 amino acid, with a net charge of + 5 at pH 7, and has a hydrophobic amino acids percentage (Hy/total aa) of 11.11%. According to Protparam tool (Gasteiger et al. 2005), BcI-1003 has a grand average of hydropathicity (GRAVY) of -1.911 and an aliphatic index of 0.00, so it is considered as a hydrophilic peptide. These results are in concordance with the low retention capacity of BcI-1003 in a C₁₈ column (R_t: 6.57 min) observed in the RP-HPLC analysis (Figure S2). The proteolytic stability prediction of BcI-1003 in an intestine environment was analyzed in silico by Protparam (Guruprasad et al. 1990) and HPL online tools (Gorris et al. 2009). For both methods, BcI-1003 showed a high proteolytic stability, given by an instability index of < 40 and a half-life (sec) > 1.0. The prediction of the secondary structure of BcI-1003 is shown in Fig. 1. The result showed that is a not structured peptide random coil.

Table 1

Physicochemical characterization of peptide BcI-1003
Peptide	Sequence	MW(g/mol)	Net charge at pH 7	Hy/total aa^	Gravy*	R_t (min)°	Instability index*	Half life (sec)^~	Toxicity
Peptide	Sequence	MW(g/mol)	Net charge at pH 7	Hy/total aa^	Gravy*	R_t (min)°	Instability index*	Half life (sec)^~	ToxinPred^†	ToxIBTL^⁑
BcI-1003	GSKKTKCPR-NH2	1003.27	+ 5	1/9 (11.1%)	-1.911	6.57	21.9	1.797	Non-toxic	Non-toxic
*calculated with Protparam tool https://web.expasy.org/cgi-bin/protparam/protparam. °R_t: time retention. ^Hy/total aa: % of hydrophobic amino acids in the whole sequence. ~calculated with HPL tool (http://crdd.osdd.net/raghava/hlp/pep_both.htm). ^†calculated with ToxinPred server (https://webs.iiitd.edu.in/raghava/toxinpred/index.html). ^⁑calculated with ToxIBTL server (https://server.wei-group.net/ToxIBTL/index.html).

Alzheimer’s multi-target analysis

To study the capability of the peptide BcI-1003 to act as a multi-target agent on AD, we evaluated its activity against four representative pathological pathways. In this sense, the inhibition assay against cholinesterases (AChE and BChE) and MAO-B enzymes, and the antioxidant activity were performed. The biological activity was expressed as IC₅₀ or EC₅₀ values, defined as the concentration of sample that produces 50% of biological activity. The results are showed in the Table 2 and Figure S3. Regarding, the cholinesterases inhibitory activity, the peptide showed to be active against BChE with an IC₅₀ value of 669 ± 12 µM, while no evidence of activity against AChE was found at the tested range. The results are in concordance with previous work, where we reported the activity of the complete skin extract of B. cordobae against cholinesterases enzymes (Spinelli et al. 2019). On the basis of these results, growing evidence suggests that BChE rather than AChE plays a key role in the hydrolysis of the neurotransmitter acetylcholine, because during AD progression, the AChE level decreases extensively in the brain, while BChE activity is maintained in a higher level. Hence, discovering BChE inhibitors is a strategy that may increase the amount of acetylcholine (Greig et al. 2005; Hartmann et al. 2007). Cholinesterases and MAOs are enzymes that are closely associated with the AD symptomatology and progression. The modulation of both enzymes offers an important chance to alter the course of AD. More than 15 years of intensive research has led to the identification of an important number of dual inhibitors, where some present positive outcomes in clinical trials (Knez et al. 2017). In 2019 we reported the first study of amphibian extracts with the capability of inhibiting the activity of MAO-B and cholinesterases enzymes (Spinelli et al. 2019; Spinelli et al. 2021). In this sense, the amphibian peptide BcI-1003 showed the potential to inhibit MAO-B with an IC₅₀ value of 570.19 ± 8 µM. The in-vitro enzymatic inhibition studies were backed by molecular dynamic studies. For BChE, the results showed that BcI-1003 residues interact by hydrogen bound with both Asp70 and Tyr332 (Fig. 2), which constitute the peripherical anionic site (PAS) (Bajda et al. 2013). The PAS site is the region involved in non-catalytic processes and non-cholinergic functions of ChEs (Kryger et al. 1999). Through the PAS, ChEs act as a chaperone in the aggregation process of Aβ, accelerating the deposition of the amyloid plaques (Sadeghi et al. 2020). The inhibition of the PAS site is considered to be a promising strategy for the treatment of AD, since PAS inhibitors can potentially reduce the hydrolysis of ACh and deaccelerate the aggregation of Aβ at the same time (Pohanka 2011). Regarding the MAO-B in sillico studies, they showed that the enzyme-peptide complex is stabilized by several interactions. Notoriously, the Cys7 of the peptide interacts with Tyr435 of the MAO-B by a π-sulphur interaction (see Fig. 2). The residue Tyr435 is located at the aromatic cage of the MAO-B and plays a key role in the catalytic process (Li et al. 2006). Recently, Mathew et al. (2021) reported the strong competitive MAO-B inhibitor TM1 (a chalcone-thioester derivate) which interacts mainly with Tyr435 (Mathew et al. 2021). On the other hand, the antioxidant activity of the peptide was evaluated using the DPPH assay (Memarpoor-Yazdi et al. 2013). The ROS (reactive oxygen species) are one of the most important stress factors for amphibian naked skins. As an organ directly exposed to ROS from the environment as well as endogenous sources, skin is a candidate to oxidative stresses, so as result has developed an efficient antioxidant defense system (Yang et al. 2009). In this work, BcI-1003 showed a potent antioxidant activity with an effective concentration 50 (EC₅₀) value of 7.24 ± 0.5 µM, a value that it is in the order of activity of the ascorbic acid. In addition, we observed a rapid colour change when performing the DPPH bioassay due to a fast capture of the free radical. These results could be attributed to the Cys7 in the sequence of BcI-1003. Several reports have demonstrated that the presence of cysteine, a reductive residue, in the peptide sequence strongly contributes to the antioxidative activity, but also is the determinant residue for rapid radical scavenging (Liu et al. 2010; Wang et al. 2017). On the other hand, the presence of basic residues such as Lysine or Arginine have shown improvements in the antioxidant capacity of peptides (Yang et al. 2009). Out of the four AD therapeutic target studied, this was the most modulated by BcI-1003. The central nervous system cells are considered as one of the more vulnerable to oxidative stress by ROS (Olmez and Ozyurt 2012). Extensive studies demonstrated that the Aβ aggregates, as well as the MAO-B, exacerbated oxidative deamination increasing the ROS levels in neuronal cells, therefore intensifying the damage in AD. Accumulated evidence showed that the antioxidant agents act as neuroprotectors, reducing the toxic effects of oxidative stress and helping to improve cognition in AD patients (Knez et al. 2018). Moreover, several peptides of 3 to 20 amino acids demonstrated neuroprotective activity, acting as scavengers of free radicals such as H₂O₂ (Elias et al. 2008; Arasu et al. 2017; Shalgum et al. 2019; Prabha et al. 2022). Here, out of the four AD therapeutic targets studied, the antioxidant activity was the most strongly modulated by BcI-1003, being this peptide a hopeful neuroprotective agent. The peptide BcI-1003 has been shown to have the ability to act on three key therapeutic targets of AD, inhibiting the activity of BChE and MAO-B enzymes, and showing a powerful and rapid antioxidant capability. Previous studies have shown that the modification of key residues to natural sequences managed to increase inhibitory activities of enzymes, as well as confer new activities (Sanchis et al. 2020; Sanchis et al. 2022). This kind of strategy could be a useful tool to improve the activity of the natural peptide BcI-1003 against BChE and MAO-B.

Table 2

Biological activities of BcI-1003 against Alzheimer’s Disease targets
	IC₅₀ (µM)
	AChE	BChE	MAO-B	DPPH
BCI-1003	N.I.	669 ± 12	570 ± 8	7.24 ± 0.51
Rivastigmine	34 ± 6	0.08 ± 0.00	-	-
Selegiline	-	-	0.01 ± 0.00	-
Ascorbic acid	-	-	-	3.5 ± 0.2
(N.I.): non-inhibitory activity. All values were expressed as IC₅₀/EC₅₀ ± SD. The IC₅₀/EC₅₀ values were determined by regression analyses of three replicate determinations.

Antimicrobial activity

To evaluate the antibacterial activity of peptide BcI-1003, the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) values were determined against clinically isolated drug-resistant strain of gram positive and negative bacteria. The results are shown in Table 3. The MIC and MBC values was expressed in µM. BcI-1003 inhibited the grown of the two meticiline-resistant S. aureus strains, with MIC values of 127.6 and 63.8 µM, and of the E. coli MDR-1 strain, with a MIC value of 8.0 µM. While against K. neumoniae strain, a naturally resistant bacterial, wasn´t active in all range of concentration tested. For both S. aureus strains, BcI-1003 had a bacteriostatic mode of action (MBC > 127.6 µM), while against E. coli strain showed a bactericidal activity, with MBC value of 127.6 µM. BcI-1003 exhibited a high cationicity (net charge of + 5) but lack of hydrophobicity and helicity, also presented a considerably higher antibacterial activity against the E. coli strain. This suggest that hydrophobicity and helicity seem to be less important parameters for activity against this gram-negative bacterium. Previously, we observed the same behaviour for peptide P2-Hp-1935, isolated from the frog Boana pulchella. This peptide presented a high cationicity (+ 5), but low percentage of hydrophobic amino acids (35%) and helicity, showing was more active against gram negative bacteria than gram positive ones (Siano et al. 2014). In general, the major AMPs contain a significant proportion of hydrophobic amino acid residues and have a positive net charge (ranging from + 2 to + 9). The cationic residues are electrostatically attracted to negative components of the bacterial wall and membrane, and the hydrophobic residues facilitate interactions with fatty acyl chains and subsequently caused the disrupting of the integrity of the bacterial membrane (Zasloff 2002). However, several reports indicate that for antimicrobial activity against gram-negative bacteria, structural requirements of AMPs are less rigorous, while a stabilized amphipathic alpha-helical conformation is an important parameter for activity against gram-positive bacteria (Giangaspero et al. 2001). In addition, numerous strains of gram-negative bacteria are susceptible to non-helical and unstructured cationic peptides, suggesting that inhibitory activity against gram-negative bacteria is mostly influenced by electrostatic interactions (Dathe et al. 1997; Giangaspero et al. 2001). In 2015, Nacif-Marçal reported the isolation and characterization of a novel antibacterial peptide from Hypsiboas semilineatus, Hs-1 (FLPLILPSIVTALSSFLKQG) (Nacif Marçal et al. 2015). This peptide had 55% of hydrophobic amino acids and a net charge of + 1 at pH 7, with a propensity to form an amphipathic alpha helix. It showed a selective spectrum of action against gram positive bacteria (MIC values ranging from 11.7 to 46 µM). The authors suggested that the lack of inhibitory activity against gram negative bacteria could be due to the low cationicity of Hs-1.

Table 3

Antimicrobial activity of peptide BcI-1003 against gram (+) and (–) bacteria.
	Clinical isolated strain	MIC (µM)	MBC (µM)
Gram (+) bacteria	Staphylococcus aureus MR-1	127.6	> 127.6
Gram (+) bacteria	Staphylococcus aureus MR-2	63.8	> 127.6
Gram (–) bacteria	Escherichia coli MDR-1	8.0	127.6
Gram (–) bacteria	Klebsiella pneumoniae Kb-1	> 127.6	> 127.6

Circular Dichroism (CD) Analyses

BcI-1003 CD spectra recorded in different media are shown in Fig. 3. In H₂O the peptide adopted a random coil conformation, as expected for short linear peptides. These data are consistent with a minimum at 198 nm. In 2,2,2-trifluoroethanol (TFE)/H₂O (50% v/v), an alpha-helix inductive solvent, and in presence of neutral dipalmitoylphosphatidylcholine (DPPC) vesicles, that simulate eukaryotic membranes, the peptide was preferentially unordered. However, in presence of dipalmitoylphosphatidylglycerol (DPPG) vesicles, that mimic the bacterial membrane, BcI-1003 was partially structured, with a spectrum consistent with a β-structure, showing a minimum around 213 nm. This suggests that the peptide interacts electrostatically with the negatively charged DPPG vesicles, which induce the adoption of a secondary structure conformation.

Toxicological profile

The knowledge of the cytotoxic activity of a compound is of great importance because this could be a limiting factor for its applicability. In this sense, the hemolytic activity against human healthy erythrocytes was determined (Figure S4). Notably, BcI-1003 demonstrated to be non-hemolytic, with hemolysis values below 10% at the assayed concentrations. In addition to the hemolysis results, the in-silico analysis by ToxinPred (Gupta et al. 2013) and ToxIBTL (Wei et al. 2022) confirmed that the peptide BcI-1003 is non-toxic (see Table 1).

The present study reports the potential of the natural peptide BcI-1003 isolated from the skin of the frog B. cordobae, to act on three Alzheimer´s disease targets (BChE, MAO-B, and antioxidant), attending to the new anti-Alzheimer strategies. Also, the peptide showed the capability to inhibit the growth of clinical drug-resistant strains of gram positive and negative bacteria. On the other hand, BcI-1003 demonstrated to be an unstructured and non-hemolytic peptide. Therefore, this work represents the starting point for future in-depth studies that allow progress towards the discovery of a new drug for application in human health.

ACKNOWLEDGEMENTS: The authors are grateful to the grant PICT-2017-0035 that supported this work.

Author contributions: SA and SR the research idea, wrote the manuscript. SR and HV carried out all the biological studies. SI performed the computational studies. ME director of bacteriology department and interpretation of the antimicrobial activities. SA director of organic chemistry laboratory.

Conflict of interest: The authors declare no conflict of interest.

Albericio F, Kruger HG (2012) Therapeutic peptides. Future Med Chem 4(12):1527–1531
Arasu A, Kumaresan V, Palanisamy R, Arasu MV, Al-Dhabi NA, Ganesh MR, Arockiaraj J (2017) Bacterial membrane binding and pore formation abilities of carbohydrate recognition domain of fish lectin. Dev Comp Immunol 67:202–212
Bajda M, Więckowska A, Hebda M, Guzior N, Sotriffer CA, Malawska B (2013) Structure-based search for new inhibitors of cholinesterases. Int J Mol Sci 14(3):5608–5632
Berendsen H, Postma JPM, van Gunsteren W, DiNola AD, Haak JR (1984) Molecular-Dynamics with Coupling to An External Bath. J Chem Phys 81:3684–3695
Bevins CL, Zasloff M (1990) Peptides from frog skin. Annu Rev Biochem 59:395–414
Binda C, Wang J, Pisani L, Caccia C, Carotti A, Salvati P, Edmondson DE, Mattevi A (2007) Structures of human monoamine oxidase B complexes with selective noncovalent inhibitors: safinamide and coumarin analogs. J Med Chem 50(23):5848–5852
Bionda C, Lajmanovich R, Di Tada I (2011) Composition of amphibian assemblages in agroecosystems from the central region of Argentina. Russ J Herpetol 18(2):93–98
Bortolami M, Rocco D, Messore A, Di Santo R, Costi R, Madia VN, Scipione L, Pandolfi F (2021) Acetylcholinesterase inhibitors for the treatment of Alzheimer’s disease – a patent review (2016–present). Expert Opin Ther Pat 31(5):399–420
Bulet P, Stocklin R, Menin L (2004) Anti-microbial peptides: from invertebrates to vertebrates. Immunol Rev 198:169–184
Camproux AC, Gautier R, Tuffery P (2004) A hidden markov model derived structural alphabet for proteins. J Mol Biol 339(3):591–605
Camproux AC, Tuffery P, Chevrolat JP, Boisvieux JF, Hazout S (1999) Hidden Markov model approach for identifying the modular framework of the protein backbone. Protein Eng 12(12):1063–1073
Case DA, Ben-Shalom IY, SR B (2020) AMBER 2020. J Computat Chem 2020; 26:1668-88
Clark NA, Hafner M, Kouril M, Williams EH, Muhlich JL, Pilarczyk M, Niepel M, Sorger PK, Medvedovic M (2017) GRcalculator: an online tool for calculating and mining dose-response data. BCM Cancer 17(1):698
Conlon JM, Kolodziejek J, Nowotny N (2004) Antimicrobial peptides from ranid frogs: taxonomic and phylogenetic markers and a potential source of new therapeutic agents. Biochim Biophys Acta 1696(1):1–14
Costa F, Teixeira C, Gomes P, Martins MCL (2019) Clinical Application of AMPs. In: Matsuzaki K (ed) Antimicrobial Peptides: Basics for Clinical Application. Springer Singapore, Singapore, pp 281–298
Daly JW, Spande TF, Garraffo HM (2005) Alkaloids from amphibian skin: a tabulation of over eight-hundred compounds. J Nat Prod 68(10):1556–1575
Dathe M, Wieprecht T, Nikolenko H, Handel L, Maloy WL, MacDonald DL, Beyermann M, Bienert M (1997) Hydrophobicity, hydrophobic moment and angle subtended by charged residues modulate antibacterial and haemolytic activity of amphipathic helical peptides. FEBS lett 403(2):208–212
de la Torre BG, Albericio F (2018) The Pharmaceutical Industry in 2017. An Analysis of FDA Drug Approvals from the Perspective of Molecules. Molecules 23(3):533–541
de Souza ON, Ornstein RL (1997) Effect of Warmup Protocol and Sampling Time on Convergence of Molecular Dynamics Simulations of a DNA Dodecamer Using AMBER 4.1 and Particle-Mesh Ewald Method. J Biomol Struct Dyn 14(5):607–611
Dominguez C, Boelens R, Bonvin AM (2003) HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J Am Chem Soc 125(7):1731–1737
Dourado FS, Leite JR, Silva LP, Melo JA, Bloch C Jr, Schwartz EF (2007) Antimicrobial peptide from the skin secretion of the frog Leptodactylus syphax. Toxicon 50(4):572–580
Elias RJ, Kellerby SS, Decker EA (2008) Antioxidant activity of proteins and peptides. Crit Rev Food Sci Nutr 48(5):430–441
Ellman GL, Courtney KD, Andres V Jr, Feather-Stone RM (1961) A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem Pharmacol 7:88–95
Faivovich J, Garcia PC, Ananias F, Lanari L, Basso NG, Wheeler WC (2004) A molecular perspective on the phylogeny of the Hyla pulchella species group (Anura, Hylidae). Mol Phylogenet Evol 32(3):938–950
Faivovich J, Haddad C, Garcia P, Frost D, Campbell J, Wheeler WC (2005) Systematic review of the frog family Hylidae, with special reference Hylinae: Phylogenetic analysis and taxonomic revision.Bull am Mus Nat Hist294–340
Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel R, Bairoch A (2005) Protein Identification and Analysis Tools on the ExPASy Server. In: Walker JM (ed) The Proteomics Protocols Handbook. Humana Press, pp 571–607
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J et al (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5(10):R80
Giangaspero A, Sandri L, Tossi A (2001) Amphipathic alpha helical antimicrobial peptides. Eur J Biochem 268(21):5589–5600
Gomes A, Giri B, Saha A, Mishra R, Dasgupta SC, Debnath A, Gomes A (2007) Bioactive molecules from amphibian skin: their biological activities with reference to therapeutic potentials for possible drug development. Indian J Exp Biol 45(7):579–593
Gorris HH, Bade S, Röckendorf N, Albers E, Schmidt MA, Fránek M, Frey A (2009) Rapid Profiling of Peptide Stability in Proteolytic Environments. Anal Chem 81(4):1580–1586
Götz AW, Williamson MJ, Xu D, Poole D, Le Grand S, Walker RC (2012) Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born. J Chem Theory Comput 8(5):1542–1555
Greig NH, Lahiri DK, Sambamurti K (2002) Butyrylcholinesterase: an important new target in Alzheimer's disease therapy. Int psychogeriatr 14(Suppl 1):77–91
Greig NH, Utsuki T, Ingram DK, Wang Y, Pepeu G, Scali C, Yu QS, Mamczarz J, Holloway HW, Giordano T et al (2005) Selective butyrylcholinesterase inhibition elevates brain acetylcholine, augments learning and lowers Alzheimer beta-amyloid peptide in rodent. Proc Natl Acad Sci 102(47):17213–17218
Gupta S, Kapoor P, Chaudhary K, Gautam A, Kumar R, Raghava GP (2013) In silico approach for predicting toxicity of peptides and proteins. PLoS ONE 8(9):e73957
Guruprasad K, Reddy BV, Pandit MW (1990) Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng 4(2):155–161
Han Y, Zhang M, Lai R, Zhang Z (2021) Chemical modifications to increase the therapeutic potential of antimicrobial peptides. Peptides 146:170666
Hartmann J, Kiewert C, Duysen EG, Lockridge O, Greig NH, Klein J (2007) Excessive hippocampal acetylcholine levels in acetylcholinesterase-deficient mice are moderated by butyrylcholinesterase activity. J Neurochem 100(5):1421–1429
Kaspar AA, Reichert JM (2013) Future directions for peptide therapeutics development. Drug Discov Today 18(17–18):807–817
Knez D, Coquelle N, Pislar A, Zakelj S, Jukic M, Sova M, Mravljak J, Nachon F, Brazzolotto X, Kos J et al (2018) Multi-target-directed ligands for treating Alzheimer's disease: Butyrylcholinesterase inhibitors displaying antioxidant and neuroprotective activities. Eur J Med Chem 156:598–617
Knez D, Sova M, Košak U, Gobec S (2017) Dual inhibitors of cholinesterases and monoamine oxidases for Alzheimer's disease. Fut Med Chem 9(8):811–832
Kryger G, Silman I, Sussman JL (1999) Structure of acetylcholinesterase complexed with E2020 (Aricept): implications for the design of new anti-Alzheimer drugs. Structure 7(3):297–307
Li M, Binda C, Mattevi A, Edmondson DE (2006) Functional role of the "aromatic cage" in human monoamine oxidase B: structures and catalytic properties of Tyr435 mutant proteins. Biochemistry 45(15):4775–4784
Little CS, Hammond CJ, MacIntyre A, Balin BJ, Appelt DM (2004) Chlamydia pneumoniae induces Alzheimer-like amyloid plaques in brains of BALB/c mice. Neurobiol Aging 25(4):419–429
Liu C, Hong J, Yang H, Wu J, Ma D, Li D, Lin D, Lai R (2010) Frog skins keep redox homeostasis by antioxidant peptides with rapid radical scavenging ability. Free Radic Biol Med 48(9):1173–1181
Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C (2015) ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J Chem Theory Comput 11(8):3696–3713
Mathew B, Oh JM, Khames A (2021) Replacement of Chalcone-Ethers with Chalcone-Thioethers as Potent and Highly Selective Monoamine Oxidase-B Inhibitors and Their Protein-Ligand Interactions. Pharmaceuticals 14(11):1148–1165
Memarpoor-Yazdi M, Mahaki H, Zare-Zardini H (2013) Antioxidant activity of protein hydrolysates and purified peptides from Zizyphus jujuba fruits. J Funct Foods 5(1):62–70
Méndez-Álvarez E, Soto-Otero R, Sánchez-Sellero I, Lamas ML-R (1997) Inhibition of brain monoamine oxidase by adducts of 1,2,3,4-tetrahydroisoquinoline with components of cigarette smoke. Life Sci 60(19):1719–1727
Miyamoto S, Kollman PA (1992) Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models. J Comput Chem 13(8):952–962
Moir RD, Lathe R, Tanzi RE (2018) The antimicrobial protection hypothesis of Alzheimer's disease. Alzheimer's Demnt 14(12):1602–1614
Nacif Marçal L, Pereira G, Abranches M, Costa N, Almeida S, Honda E, De Paula S, Feio R, Oliveira L (2015) Identification and characterization of an antimicrobial peptide of Hypsiboas semilineatus (Spix, 1824) (Amphibia, Hylidae). Toxicon 99:16–22
Newman DJ, Cragg GM (2012(Natural products as sources of new drugs over the 30 years from 1981 to 2010.J Nat Prod75(3):311–335
Olmez I, Ozyurt H (2012) Reactive oxygen species and ischemic cerebrovascular disease. Neurochem Int 60(2):208–212
Pastor RW, Brooks BR, Szabo A (1988) An analysis of the accuracy of Langevin and molecular dynamics algorithms. Mol Phys 65(6):1409–1419
Pohanka M (2011) Cholinesterases, a target of pharmacology and toxicology. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 155(3):219–229
Prabha N, Guru A, Harikrishnan R, Gatasheh MK, Hatamleh AA, Juliet A, Arockiaraj J (2022) Neuroprotective and antioxidant capability of RW20 peptide from histone acetyltransferases caused by oxidative stress-induced neurotoxicity in in vivo zebrafish larval model. J King Saud Univ Sci 34(3):101861
Sadeghi L, Yekta R, Dehghan G (2020) The inhibitory effects of bile acids on catalytic and non–catalytic functions of acetylcholinesterase as a therapeutic target in Alzheimer's disease. Acta Neurobiol Exp 80(2):108–116
Salomon-Ferrer R, Götz AW, Poole D, Le Grand S, Walker RC (2013) Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald. J Chem Theory Comput 9(9):3878–3888
Sanchis I, Spinelli R, Siano A (2022) Rational design and synthesis of modified natural peptides from Boana pulchella (anura) as acetylcholinesterase inhibitors and antioxidants. Aminoacids 54(2):181–192
Sanchis I, Spinelli R, Aschemacher N, Humpola MV, Siano A (2020) Acetylcholinesterase inhibitory activity of a naturally occurring peptide isolated from Boana pulchella (Anura: Hylidae) and its analogs. Aminoacids 52(3):387–396
Santos MA, Chand K, Chaves S (2016) Recent progress in repositioning Alzheimer's disease drugs based on a multitarget strategy. Fut Med Chem 8(17):2113–2142
Sehnal D, Bittrich S (2021) Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures. Nucleic Acids Res 49(W1):W431–w437
Shalgum A, Govindarajulu M, Majrashi M, Ramesh S, Collier WE, Griffin G, Amin R, Bradford C, Moore T, Dhanasekaran M (2019) Neuroprotective effects of Hibiscus Sabdariffa against hydrogen peroxide-induced toxicity. J Herb Med 17–18:100253
Siano A, Humpola MV, de Oliveira E, Albericio F (2018) Leptodactylus latrans Amphibian Skin Secretions as a Novel Source for the Isolation of Antibacterial Peptides. Molecules 23(11):2943–2957
Siano A, Humpola MV, de Oliveira E, Albericio F, Simonetta AC, Lajmanovich R, Tonarelli GG (2014) Antimicrobial peptides from skin secretions of Hypsiboas pulchellus (Anura: Hylidae). J Nat Prod 77(4):831–841
Siano A, Humpola MV, Rey MC, Simonetta A, Tonarelli GG (2011) Interaction of acylated and substituted antimicrobial peptide analogs with phospholipid-polydiacetylene vesicles. Correlation with their biological properties. Chem Biol Drus Des 78(1):85–93
Spinelli R, Aimaretti FM, Lopez JA, Siano AS (2021) Amphibian skin extracts as source of bioactive multi-target agents against different pathways of Alzheimer's disease. Nat Prod Res 35(4):686–689
Spinelli R, Barraro Guevara LA, Lépes JA, Camargo CM, Groot de Restrepo H, Siano AS (2020) Cytotoxic and antiproliferative activities of amphibian (anuran) skin extracts on human acute monocytic leukemia cells. Toxicon 177:25–34
Spinelli R, Sanchis I, Aimaretti FM, Attademo AM, Portela M, Humpola MV, Tonarelli GG, Siano AS (2019) Natural Multi-Target Inhibitors of Cholinesterases and Monoamine Oxidase Enzymes with Antioxidant Potential from Skin Extracts of Hypsiboas cordobae and Pseudis minuta (Anura: Hylidae. Chem Biodivers 16(1):e1800472
Sreerama N, Venyaminov SY, Woody RW (2000) Estimation of protein secondary structure from circular dichroism spectra: inclusion of denatured proteins with native proteins in the analysis. Anal Biochem 287(2):243–251
Sreerama N, Venyaminov SY, Woody RW (2001) Analysis of protein circular dichroism spectra based on the tertiary structure classification. Anal Biochem 299(2):271–274
Tang H, Zhao H-T, Zhong S-M, Wang Z-Y, Chen Z-F, Liang H (2012) Novel oxoisoaporphine-based inhibitors of acetyl- and butyrylcholinesterase and acetylcholinesterase-induced beta-amyloid aggregation. Bioorg Med Chem Lett 22(6):2257–2261
Team RDC (2010) R: A Language and Environment for Statistical Computing Vienna, Austria. R Foundation for Statistical Computing
Tyler M, Wassersug R, Smith B (2007) How frogs and humans interact: Influences beyond habitat destruction, epidemics and global warming. Appl Herpetol 4(1):1–18
van Zundert GCP, Rodrigues JPGLM, Trellet M, Schmitz C, Kastritis PL, Karaca E, Melquiond ASJ, van Dijk M, de Vries SJ, Bonvin AMJJ (2016) The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes. J Mol Biol 428(4):720–725
Venkatraghavan V, Bron EE, Niessen WJ, Klein S (2019) Disease progression timeline estimation for Alzheimer's disease using discriminative event based modeling. NeuroImage 186:518–532
Wang X, Ren S, Guo C, Zhang W, Zhang X, Zhang B, Li S, Ren J, Hu Y, Wang H (2017) Identification and functional analyses of novel antioxidant peptides and antimicrobial peptides from skin secretions of four East Asian frog species. Acta Biochim Biophys Sin 49(6):550–559
Wei L, Ye X, Sakurai T, Mu Z, Wei L (2022) ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning. Bioinformatics 38(6):1514–1524
Wickham H (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York
Yang H, Wang X, Liu X, Wu J, Liu C, Gong W, Zhao Z, Hong J, Lin D, Wang Y et al (2009) Antioxidant peptidomics reveals novel skin antioxidant system. Mol Cell Proteomics 8(3):571–583
Yang JY, Chen X (2011) Improving taxonomy-based protein fold recognition by using global and local features. Proteins 79(7):2053–2064
Ye L, Zhang J, Xiao W, Liu S (2020) Efficacy and mechanism of actions of natural antimicrobial drugs. Pharmacol Ther 216:107671
You D, Hong J, Rong M, Yu H, Liang S, Ma Y, Yang H, Wu J, Lin D, Lai R (2009) The first gene-encoded amphibian neurotoxin. J Biol Chem 284(33):22079–22086
Zasloff M (2002) Antimicrobial peptides of multicellular organisms. Nature 415(6870):389–395
Zhang W, Liu S, Zhou Y (2008) SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model. PLoS ONE 3(6):e2325
Zhu L, Maruvada R, Sapirstein A, Malik KU, Peters-Golden M, Kim KS (2010) Arachidonic acid metabolism regulates Escherichia coli penetration of the blood-brain barrier. Infect Immun 78(10):4302–4310

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Biological characterization of natural peptide BcI-1003 from Boana cordobae (anura): role in Alzheimer’s Disease and microbial infections.

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Version 1

Abstract

Figures

Introduction

Materials And Methods

Secondary structure prediction

Peptide Synthesis

Cholinesterases Inhibition assay

MAO-B inhibition assay

Molecular dynamic and docking studies

DPPH radical scavenging activity

Antimicrobial activity

Circular Dichroism (CD) Analyses

Hemolytic Activity

Data analysis

Results And Discussion

In silico analysis of structural, physicochemical and stability parameters of the synthetic peptide BcI-1003

Alzheimer’s multi-target analysis

Antimicrobial activity

Circular Dichroism (CD) Analyses

Toxicological profile

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1