Structural basis to identify a target site in Shiga toxin for the inhibitor discovery against growth of Shiga toxin-producing E. coli

Abstract

Background

Certain peptides that bind Shiga toxin 2 (Stx2) have been reported to treat Shiga toxin-producing Escherichia coli (STEC) infections. However, their mechanisms of action remain unknown. STEC infections lead to serious diseases, such as hemolytic uremic syndrome, in humans. Antibiotic therapy is usually not recommended because of the major challenges of antibiotic resistance and SOS repair. Currently, there is no human vaccine for STEC infection, leaving rehydration therapy as the recommended supportive therapy. Therefore, there is a need for targeted therapeutic intervention to inhibit STEC growth. The purpose of this study was to evaluate the interaction of five known peptides with Stx2 to identify a more suitable peptide based on structural changes. These peptides have been used to inhibit the growth of STEC.

Results

The current study demonstrated that only tetravalent peptide (TVP) out of 5 common peptides interrupted the Y77-E259 interaction of Stx2, making it active by exposing active site, which ultimately leads to STEC cell death. We also demonstrated that amino acids R170 and F171 of Stx2 in the docked complex of Stx2 and TVP form a helix-loop-helix (HLH). This might lead to the differential expression of genes regulated by Stx2 and ultimately inhibit STEC growth. However, in the case of Stx2-ribosomal P-stalk, these residues did not form HLH. The 3D refined model of TVP showed a low MolProbity score and low energy zones in the ANOLEA profile compared to the original one. Moreover, the low radius of gyration of the refined TVP suggests that it is more compact than the original TVP. Therefore, TVP is a suitable drug candidate for the inhibition of STEC growth. However, the low antigenicity of TVP makes it unsuitable as a drug candidate. We also evaluated three antibiotics that have been used as active ingredients in FDA-approved peptides. Only Oritavancin diphosphate showed strong polar interactions with Y77-E259 and also had the highest binding affinity.

Conclusions

Potential drug candidates that inhibit or interrupt the interaction between Y77-E259 and have high antigenicity, low toxicity, and no allergenicity should be explored against the growth of STEC.

Background

Shiga toxin-producing Escherichia coli (STEC) are a heterogeneous group of E. coli strains that produces Shiga toxins (Stxs). STEC infections are associated with various diseases such as diarrhea, hemorrhagic colitis (HC), hemolytic uremic syndrome (HUS) in humans, gastrointestinal sickness, edema disease in pigs, wildlife infections, calf mortality, diarrhea, and dysentery in calves (Chase-Topping et al. 2023; Deep et al. 2023; Fernandez et al. 2023; Fitzgerald et al. 2023; Freedman et al. 2023; Jones et al. 2023; Liu et al. 2023; Neu et al. 2023; Tang et al. 2023). Currently, the recommended therapy for STEC infection is supportive, such as rehydration therapy (Muhlen and Dersch 2020). The treatment of STEC infection with antibiotics is controversial for two main reasons: (1) antibiotic resistance (Heydari et al. 2020; Milton et al. 2023; Oguadinma et al. 2023; Rubab and Oh 2021) and (2) induction of SOS repair (Crane et al. 2021). Therefore, antibiotics are not usually recommended for STEC infections (Kakoullis et al. 2019; Tarr and Freedman 2022). However, certain antibiotics, such as rifampicin in the presence of an STEC-specific phage cocktail, do not induce the release of phages from the genome of the STEC strain, which makes it a promising anti-STEC agent(s) (Necel et al. 2022). Other strategies for the treatment of STEC infections include antibody therapy, extracellular vesicles, vaccines, toxin receptor analogs, and plants or natural products (Caballero-Prado et al. 2021; Henrique et al. 2022; Lee et al. 2023).

New therapeutic approaches and strategies have recently been developed to manage STEC infections in recent years. For example, therapeutic peptides interfere with intracellular Stx trafficking and successfully prevent Stx2 toxicity (Rahal et al. 2015), (Biernbaum et al. 2023; Li et al. 2016; Lino et al. 2011; Prada-Prada et al. 2020; Stearns-Kurosawa et al. 2011; Watanabe-Takahashi et al. 2021). For example, Ac-PPP-tet and TVP contain four Pro-Pro-Pro-Arg-Arg-Arg-Arg motifs. PPP-tet was shown to protect mice from fatal doses of E. coli O157:H7 (Nishikawa et al. 2006). The addition of acetyl groups renders this compound resistant to proteolysis during STEC infection. These data indicate that Ac-PPP-tet is a promising therapeutic agent for STEC infections. However, characterization of these peptides and the mechanism of their interaction with Stx2 have not been thoroughly investigated.

There are two types of Stxs: Stx1 and Stx2. Stx2 is more toxic and has two subunits, A (holotoxin) and B. Glycolipid globotriaosylceramide (Gb3, CD77) acts as a receptor for B subunit. These receptors are present in various human cells such as glomerular and brain endothelial cells. After binding, the holotoxin is internalized by endocytosis, and the A1 and A2 fragments are formed due to proteolytically cleavage of the A subunit (Rudolph et al. 2020). The A1 subunit removes adenine from the highly conserved sarcin/ricin loop (SRL) in 28S rRNA, thereby inhibiting protein synthesis (de Virgilio et al. 2010). The active and ribosomal binding sites of Stx2 are located on opposite sides of the A1 subunit of Stx2 (Stx2A1) (Li and Tumer 2017). According to a previous report, the Stx2A1 subunit binds to the C-terminus of ribosomal P-stalk proteins via R172, R176, and R179 but does not remove adenine from SRL because their active sites (Tyr76/Tyr77, Tyr114, Glu167, and Arg170) are blocked (Li and Tumer 2017). This shows that removing the blockage of active sites is essential for depurination of SRL or inhibition of protein synthesis. However, information regarding the specific active sites has not been studied in detail. Interestingly, Stxs attack bacterial ribosomes as effectively as eukaryotic ribosomes, making them potential targets for the development of drugs against STEC (Suh et al. 1998). Hence, it is difficult to purify Stx2A from E. coli because it can attack the bacterial ribosomes (Rudolph et al. 2020).

The current bioinformatics approach used in this study demonstrated that blockage of Y77-E259 and Y114-E167 interactions is required to activate Stx2 by exposing its active site. These interactions were evaluated in five known peptides that have been used against STEC growth. While all peptides interacted with Y77 and E259, only one TVP (MAPPPRRRRA) interrupted the interaction between Y77 and E259 residues of Stx2A1, rendering Stx2 active by exposing the active site, ultimately leading to STEC cell death. We also showed a change in the structural conformation of the Stx2A-TVP complex compared to the Stx-2-ribosome p-stalk protein complex. However, its low antigenicity and negative G-factor make it an unsuitable drug candidate. Therefore, potential candidates that inhibit the interaction of Y77-E259 should be explored against the growth of STEC.

Methods

Bioinformatics analysis

The structures of Stx2 (PDB ID:7D6Q) and Stx2-ribosomal P-stalk proteins (PDB ID:7U6V) were downloaded in the PDB format. The PEP-FOLD server at the RPBS MOBYLE portal was used to determine the 3-D structure of therapeutic peptides against STEC infections (Thevenet et al. 2012). In this server, the amino acid sequence is provided in the FASTA format. These amino acids must include 20 standard amino acids. The server can not be used for the peptides longer than 50 amino acids and thus, has limitations. Docking between Stx2 and therapeutic peptides was performed using the ClusPro server (Comeau et al. 2004). The server has inherent problems of new additions and size of proteins submitted. The receptor protein can be no larger than 11,999 atoms and the ligand can be no larger than 4700 atoms after minimization (Comeau et al. 2004). Proteins and ligands were prepared using UCSF chimera as described previously (Pettersen et al. 2004; Sameer et al. 2023). The iMODS online server was used on the Stx2-TVP docking complex to perform a Normal Mode Analysis (NMA) (Lopez-Blanco et al. 2014). iMODS was used to generate the covariance matrix of the docking complex. The ERRAT method (Colovos and Yeates 1993) was used to detect incorrect regions, and the PROCHECK server through a Ramachandran plot (Laskowski et al. 1996) was used to predict the stereochemical quality validation of the Stx2-TVP complex. The structures of three antibiotics (active ingredients of FDA-approved peptides) (Chen and Lu 2020), Oritavancin diphosphate (CID:53297457), telavancin hydrochloride (CID:53297457), and daptomycin (CID:16134395), were downloaded from PubChem for docking studies. Molecular docking between stx2 and these antibiotics was performed using PyRx (Dallakyan and Olson 2015). The visualization tool, PyMOL, was used to observe the interactions of Stx2 with TVP and active ingredients of FDA-approved peptides.

Physiochemical property analysis of the TVP

Physiochemical properties of therapeutic peptides were computed using ‘peptides’ package of RStudio and ProtParam (Gasteiger et al. 2003). It predicts ten structural characteristics of antimicrobial peptides (AMP), including length, amino acid composition, molecular weight, net charge, isoelectric point, extinction coefficient, aliphatic index, instability index, potential peptide interaction index (Boman index), hydrophobic moment, and GRAVY hydrophobicity index (Gupta et al. 2013; Wilkins et al. 1999). The characteristic properties of effective AMP are their short length (< 10 kDa, 10–15 amino acid residues long), net positive charge of at least + 2 at pH 7, and amphipathic nature. A positive net charge on AMP predicts its binding specificity to negatively charged bacterial membranes. The extinction coefficient measures how strongly a protein absorbs or reflects light of a specific wavelength. The aliphatic index of a protein is related to the thermal stability of the protein. An instability index value of > 40 indicates instability. The Boman index differentiates the mechanism of action of antimicrobial peptides (protein membranes). A high value of the Boman index denotes its interaction with other proteins, while a negative value denotes no interaction with other proteins during their mechanism of action. Positive values of the hydrophobicity index and GRAVY indicate that the peptide can cross the cell membrane.

Evaluation of the 3D refined model

The structure of TVP (MAPPPRRRRA) was refined using the GalaxyRefine server (Ko et al. 2012) and evaluated for its stereochemical properties using a Ramachandran plot (Laskowski et al. 1996). Tools such as the QMEAN6 server (Qualitative Model Energy Analysis) were used to predict the quality of the models at the global and local levels (Benkert et al. 2009). The ANOLEA profile was created for the refined and original TVP to calculate the areas of high energy (Melo et al. 1997). The simulation was performed using the CHARMM force field between the refined and original models of the TVP with stx2, using GROMACS version 2022.5. System build-in commands were used for solvation, ion addition, and energy minimization. The simulation was performed for 100 ns, and the root-mean-square deviation (RMSD) and radius of gyration (Rg) were calculated for both the original and refined TVP. The statistical differences in RMSD and Rg were assessed by applying one-way analysis of variance followed by Bonferroni post-hoc test using OriginPro (Version:2019b) software. P < 0.05 was considered statistically significant.

Antigenicity, allergenicity and toxicity analysis

Antigenicity prediction was done using the VaxiJen v2.0, server (Doytchinova and Flower 2007). Using this approach, only those proteins were selected for further evaluation which had antigenicity scores higher than the threshold value of 0.4. AllergenOnline was used to identify allergic actions (Goodman et al. 2016). The server predicted allergenicity using six different approaches. However, the best approach is a BLAST search for allergen representative peptides because of its high accuracy, sensitivity, and specificity. ToxinPred was used to study the toxicity of the TVP (Gupta et al. 2013).

Results

Evaluation of the Stx2 and Stx2-ribosomal P-stalk

It has been shown that the position of glutamate 259 (E259) likely blocks the interaction of Stx2 with SRL, rendering it catalytically inactive (Rudolph et al. 2020). We first studied the interaction between Y77 and E259 in the cryo-EM structure of Stx2A1 in complex with the native ribosomal P-stalk (PDB ID:7U6V). In this structure, Y77-E259 and Y114-E167 were located far from each other and did not exhibit polar interactions (Fig. 1A, B). However, in Stx2 (PDB:7D6Q), these residues interacted via hydrogen bonding (Fig. 1C, D). These results suggest that the interaction of Stx2 with the ribosome p-stalk blocks or inhibits Y77-E259 and Y114-E167 interactions.

Fig. 1

Docking analysis showing interactions of tyrosine 77 (Y77)-glutamate 259 (E259) (magenta, stick) and tyrosine 114-glutamate 167 (E167) (purple, stick) in the complex of Stx2-ribosomal P-stalk (gray), a cartoon model depicting interactions of Y77 and E259 in the complex of Stx2-ribosomal P-stalk, b hydrogen bonding between Y77 and E259 in Stx2-ribosome P-stalk. c, d Docking analysis showing interactions of tyrosine 77 (Y77)-glutamate 259 (E259) (magenta, stick) and tyrosine 114-glutamate 167 (E167) (purple, stick) in the complex of Stx2 (cyan), c cartoon model depicting interactions of Y77 and E259 in the complex of Stx2, d hydrogen bonding between Y77 and E259 in Stx2. Blue colored dashes are showing hydrogen bonding. Amino acids were labeled using a one-letter code

Effect of Shiga toxin associated peptides on the Y77-E259 and Y114-E167 interactions

Docking analysis of the Stx2-peptides complexes revealed that out of the five known peptides, only one TVP (MAPPPRRRRA) blocked the interaction between the Y77 and E259 residues of Stx2A1 (Fig. 2 and Table 1). Therefore, it makes Stx2 catalytically active by exposing its active site (Y77), resulting in the inhibition of bacterial ribosomes. However, all peptides showed a close interaction with the Y77 and E259 residues of stx2A1 (data not shown), suggesting the role of interaction of peptides with these residues in STEC killing.

Fig. 2

Interaction of the TVP (gray, stick) with Y77 (magenta, stick) and E259 (cyan, stick) of Stx2

Table 1 Evaluation of the polar interaction of therapeutic peptides with Stx2

The binding pocket of TVP was predicted by the CASTp 3.0 available online at http://cast.engr.uic.edu (Tian et al. 2018). The binding pocket is lined by chains A, D, and E of Stx2 (Fig. 3A,B). The area and volume of the binding pocket was 381.6A°² and 191.5A°³, respectively. Amino acids occupying the binding pocket are shown in Fig. 3C. TVP exhibited hydrogen bonding with E72, Y77, V78, S112, T115, Q257, and E259 in chain A and K7 and D70 in chain D, whereas hydrophobic interactions were formed by N74, N75, Y114, Q118, R125, V162, E167, R170, T199, L200, W202, L239, Q261, and I262 in chain A, and K7, I8, E9, K22, Q43, and G46 in chain D of Stx2 (Fig. 4A, B).

Fig. 3

Structural model depicting the presence of TVP in the binding pocket of Stx2. a Binding site of peptide indicated by red region, b Binding pocket surrounded by chains A (cyan), D (yellow), and E (blue) of Stx2. c Amino acids occupying the binding pocket are shown in gray colored shaded region

Fig. 4

Molecular docking of Stx2-TVP complex, a Surface model depicting the hydrogen bonding (red) and hydrophobic interactions (blue) between TVP (gray) and Stx2 (cyan) in the binding pocket, b Hydrogen bonding between active residues (red; sticks) of Stx2 with TVP (gray, sticks) and hydrophobic interactions between amino acid residues (blue, lines) of Stx2 with peptide. Magenta colored dashes are showing hydrogen bonding. Amino acids were labeled using a one-letter code

The covariance matrix indicates that Y77 and E259 show anti-correlated motion (blue region), which indicates that Y77 and E259 are moving far from each other after interaction with the TVP (Fig. 5A). The Ramachandran plot showed that 92.9% and 7.1% of residues were in the favored and allowed regions, respectively. No residues were found in outlier regions (Fig. 5B). However, the overall G-factor value was slightly negative (− 0.05), indicating residues in slightly unlikely conformations. The structure was also validated using another structure verification server called Errat, which showed an overall quality factor of 83.36 for Stx2-TVP. In ERRAT, an error value exceeding the 99% confidence level indicates a poorly modeled region. For both Y77 and E259, the error values were below the 50% confidence level, indicating that these residues are present in the optimal model region of the Stx2-TVP complex (Fig. 6).

Fig. 5

a Covariance matrix indicate coupling between residues, where red represents correlated, white represents uncorrelated and blue represents anti-correlated motions of residues. Black boxes represent relative movement of residues positioned at 50–100 or 250–300. These regions covered the Y77 and E259 regions. b Ramachandran plot of the Stx2-TVP complex. The red-colored boxes represent most favored regions. Additional allowed regions are denoted by yellow color boxes

Fig. 6

ERRAT plot showing the error values for residues in the Stx2-TVP complex. An error value exceeding the 99% confidence level indicates a poorly modeled region. The arrow indicates the error value at the < 50% confidence level for Y77 and E259

Effect of TVP on the ribosome binding sites of Stx2

PyMOL was used to superimpose the structures of Stx2-TVP and Stx2-ribosomal P-stalk (Fig. 7A). The region near the ribosomal binding site (R172, R176, and R179) of Stx2 was also studied (Fig. 7B). Structural analysis of the Stx2-TVP complex demonstrated that two residues (R170 and F171) located near ribosomal binding sites (RBS) were present in the loop of the A subunit of Stx2 (Fig. 7C). Loops containing R170 and F171 are present between the two alpha helices (helix-loop-helix, HLH). HLH functions as a transcription factor that binds DNA and regulates gene expression (Massari and Murre 2000; Obata et al. 2022). However, in the case of Stx2-ribosomal P-stalk, these residues were located in the α-helix region of Stx2A1 (Fig. 7D).

Fig. 7

a Superimposition of Stx2-TVP (cyan) and Stx2-ribosomal P-stalk (golden), b Closer view of the superimposed structure near the ribosome binding sites (R172, R176, and R179) of c Stx2-TVP and d Stx2-ribosomal P-stalk depicting the presence of R170 (green, stick) and F171 (magenta, stick) in loop and helix, respectively. Amino acids were labeled using a one-letter code

Secondary structure analysis

The secondary structure of TVP was predicted using SOPMA server (Geourjon and Deleage 1995). It predicts the secondary structure based on the availability of amino acid sequences in the databases. The results showed that TVP was composed of 100% random coils (Fig. 8A). The Ramachandran plot showed that 60% and 40% of residues were in the favored and allowed regions, respectively. However, none of the residues was present in the outlier region. According to the PROCHECK analysis, the overall G-factor of TVP was − 0.55. The G-factor predicts the distance of each residue from the normal region of a plot. Negative G-factors indicate that the residues are not in the likely conformations.

Fig. 8

a Structure of the original TVP model. b Ramachandran plot of refined TVP. The most favored regions are denoted by red color. Additional allowed regions are denoted by yellow color, c Superimposition of original (gray) and refined (cyan) model of TVP, d Rg, e RMSD of original TVP (black) and refined TVP (red). P < 0.05 significant difference

Refinement of tertiary structure of TVP

The tertiary (3D) structure of the TVP was refined using the GalaxyRefine server. The accuracy of the model is defined by the GDA-HA, MolProbity, and clash scores. MolProbity score highlights steric clashes. Five models were generated using GalaxyRefine, of which Model 1 was selected because of its conformational properties. Additionally, for the refined model, GDT-HA was 0.8750, whereas MolProbity, clash score, and poor rotamers were 1.692, 15.5, and 0.0, respectively. The GDT-HA, MolProbity, clash score, and poor rotamers for the original model were 1, 1.742, 6.6, and 0, respectively. When compared with the other models, Model 1 was predicted to be the best refined model based on different scores. Moreover, the Ramachandran plot showed that 100% of the residues were in the favored region of the three-dimensional structure (Fig. 8B). The G-factor for this model was + 0.28, indicating residues in likely conformations. Superimposition of the refined model with the original TVP showed differences in structural configuration (Fig. 8C). No significant changes were observed for the RMSD; however, the Rg was less for the refined model of TVP, suggesting more compactness of the refined structure (Fig. 8D, E).

Additionally, the QMEAN values (blue region) of the refined model are higher (0.67) than those of the original model (0.40), which indicates that the model scores are higher than those of the original model on average. In the ANOLEA profile, the initial model had many areas of high energy, which were greatly improved in the refined model, suggesting greater reliability (Fig. 9A, B).

Fig. 9

a ANOLEA plots showing energy zones of individual amino acids in original and refined TVP, b ANOLEA plot showing overall energy zone for original and refined TVP

Physiochemical properties of tetravalent peptide

TVP has 174 atoms and its molecular weight was found to be 1.21 kDa. Further analysis showed that TVP had an isoelectric point (pI) value of 12.48, indicating its basic nature. The positive charge of TVP (+ 4) denotes its binding affinity for the negatively charged bacterial membranes. The amino acid composition showed the amphipathic nature of TVP, with four polar and six non-polar residues. Moreover, the membrane position of the TVP is globular, indicating its natural folding nature. These results suggest that TVP possesses characteristic properties that are essential for its effectiveness as an effective antimicrobial peptide. However, low aliphatic index and high instability index suggest that TVP is thermally unstable. Moreover, the hydrophobicity index and grand average of hydropathicity (GRAVY) were negative, indicating its hydrophilic nature (Table 2).

Table 2 Physiochemical attributes of TVP

Allergenicity, toxicity, and antigenicity analysis

Effective antimicrobial peptides do not have any allergenicity. No hits were found against the database of 2890 allergen representative peptides (ARPs), suggesting that all the five peptides were non-allergenic in nature. ToxinPred analysis indicated the non-toxic nature of therapeutic peptides. Of the five peptides, only three had antigenic scores > 0.4, suggesting their protective antigenicity (Table 3) (Doytchinova and Flower 2007).

Table 3 Antigenicity, allergenicity, toxicity and physiological attributes of therapeutic peptides

Effect of antibiotics on the Y77-E259 and Y114-E167 interactions

Of the three antibiotics (active ingredients of FDA-approved peptides), only oritavancin diphosphate interacted with Y77, E259, and Y114 (Table 4). The same glycopeptide antibiotic exhibited the highest binding affinity. These analyses suggest a possible role of this antibiotic in the inhibition of STEC growth.

Table 4 Evaluation of the polar interaction of antibiotics with Stx2

Discussion

Antimicrobial peptides (AMPs) are small amino acid-based molecules that can kill various microorganisms at micromolar concentrations. AMPs were first identified in circulating phagocytes of humans (Spitznagel 1997). Later, they were identified in granulocytes, platelets, specialized epithelial glands, wet mucosal epithelial cells of the intestine, and fetal membranes. A variety of AMPs comprising an important part of the innate immune system have been identified, and an updated list is available in the data repository of antimicrobial peptides (DRAMP) (Bin Hafeez et al. 2021). AMPs have been shown to inhibit microbial growth prior to the recruitment of immune cells (Gallo and Nizet 2003).

Previous studies have shown that peptides are used to treat STEC infection (Rahal et al. 2015; Stearns-Kurosawa et al. 2011). Additionally, it was also shown that Stx2 can bind to the ribosome p-stalk but did not show activity due to blockage of the active site (Li and Tumer 2017). However, information about the active site and mechanism of action by which TVPs reduce STEC infection is unknown. This study demonstrated that TVP completely blocks the Y77-E259 interaction and thus exposes the Y77 active site, making Stx2 active. We also showed that structural conformation near the RBS of Stx2 changes in the presence of TVP and may affect gene expression regulated by Stx2 (Massari and Murre 2000; Obata et al. 2022). However, the negative G-factor and its non-antigenic nature likely make it an unsuitable drug candidate.

Antimicrobial agents such as antibiotics are also used to treat STEC infections. However, the use of these agents remains controversial. In some studies, antibiotics have been shown to enhance the risk of HUS; however, opposite results have also been reported. This may be related to the strains and antimicrobial agents used in their studies. There are various ways by which antibiotics can increase the release of Shiga toxin; for example, by developing resistance or by triggering a bacterial SOS response or other types of physiological stresses that activate the lytic cycle of the bacteriophage encoding Stx, thereby increasing Shiga toxin production (Hwang et al. 2021). Antibiotic resistance in STEC is due to the presence of plasmids carrying drug resistance genes. The unselective and uncontrolled use of antibiotics has encouraged the development of drug-resistant strains of STEC in animal and human populations. These antibiotic-resistant strains in animal populations can pose a global public health hazard due to their transmission from animals to humans. Ruminants, especially cattle, have been identified as major reservoirs of STEC (Boriollo et al. 2021). Antibiotics, such as azithromycin, fosfomycin, and meropenem, are usually recommended for the treatment of early stage STEC infections. These antibiotics are known to prevent Shiga toxin release and kidney failure. However, antibiotic resistance can either reduce or negatively affect these treatment options (Mir and Kudva 2019). These studies suggest that treatment of STEC infections with antimicrobial agents should be reconsidered. For example, rifampicin and gentamycin together reduce Shiga toxin production (Puno-Sarmiento et al. 2020; Ramstad et al. 2021). It was also shown that a treatment of antibiotic-peptide combination reduces STEC infection without any effect on the release of Shiga toxins. This study suggests a strategy for the repurposing of antibiotics for treatment of STEC infection (Puno-Sarmiento et al. 2020).

In this study, only Oritavancin diphosphate formed polar interactions with Y77 and E259. However, it did not block the Y77-E259 interaction as in the case of TVP. This antibiotic has been classified by WHO as critically important to humans. Whether this binding creates an obstruction in the smooth interaction of Y77 with E259 needs to be validated by experimental work. Oritavancin is approved by the FDA for the treatment of acute bacterial skin and skin structure infections (SSSIs) in adults. SSSIs are suspected to be caused by gram-positive microorganisms, such as Staphylococcus aureus (methicillin-susceptible [MSSA] (Kumar et al. 2023) and methicillin-resistant [MRSA]), Streptococcus pyogenes, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus anginosus group (including S. anginosus, Streptococcus intermedius, and Streptococcus constellatus), and Enterococcus faecalis (vancomycin-susceptible isolates only) (Cada and Baker 2014). However, its role in STEC has not been evaluated. Overall, the current study suggests that potential drug candidates that can block the interaction between Y77-E259 should be explored against STEC growth.

Conclusions

STEC poses health risks to animal reservoirs and food products with respect to easy transmission, causing outbreaks, and transferring resistance genes to other pathogens in animals, humans, and plants (Al Qabili et al. 2022; Carter et al. 2023; El-Bastawisy et al. 2023). Therefore, prevention of STEC infection must be strengthened to avoid the spread of STEC. Despite the tremendous risks posed by E. coli, the emergence of antibiotic resistance has raised challenges in the treatment of STEC infections. Antibiotic treatment of STEC infections in humans is not usually recommended because they may worsen the disease by inducing toxin-related tissue damage and symptoms (Rubab and Oh 2021). Other strategies include antibody therapy, vaccines, toxin receptor analogs, and plants or natural products. Polyclonal antibodies have shown promising neutralizations in vitro and in vivo. However, animal sources of polyclonal antibodies may induce anti-antibody actions that inactivate therapeutic antibodies before showing toxin-neutralizing activity. Similarly, natural drugs have been tested in animal models, but not in clinical trials (Liu et al. 2022). Currently, there is no vaccine available for the treatment of STEC infections in humans (Liu et al. 2022). Therefore, it is imperative to identify new therapeutic approaches and strategies for managing STEC infection. In this study, only TVP interrupted the interactions between Y77 and E259 of the Stx2. This interruption exposes the active site (Y77) of Stx2, ultimately inhibiting STEC growth. Early studies have identified that Y77of Stx2 plays an important role in the catalytic activity of Stx2 (Di et al. 2011). The change in the structural conformation of the Stx2A-TVP complex forms HLH, which regulates differential gene expression and ultimately inhibits STEC growth. Therefore, the results of this study highlight the importance of interrupting the Y77-E259 interaction to inhibit STEC growth by TVP. However, TVP is an unsuitable drug candidate owing to its low antigenicity and negative G-factor. Additionally, the formation of insoluble toxic byproducts during peptide synthesis leads to adverse effects on the nervous, musculoskeletal, and cardiovascular systems. They can even cause cancer. Thus, the FDA has banned many peptides. Peptides also exhibit low bioavailability and metabolic liabilities. However, they cannot easily cross the epithelial barrier. Therefore, potential drug candidates that inhibit or interrupt the interaction between Y77-E259 should be explored against the growth of STEC. In this regard, three antibiotics were explored to evaluate their effects on the Y77-E259 interaction. Of the three antibiotics, only oritavancin diphosphate interacted with Y77, E259, and Y114, and exhibited the highest binding affinity. These analyses suggest a possible role of this antibiotic in the inhibition of STEC growth. It would be valuable to explore specific drug candidates or experimental approaches that can block or inhibit the Y77-E259 interaction.