New Results

Detection of Potential Phytochemicals against ctxAB Toxin to Combat Cholera

Yasmin Akter, Khalilur Rahman, Md Selim Reza, Abdullah Al-Mamun, Munirul Alam, Md Nurul Haque Mollah, Md. Mamun Monir
doi: https://doi.org/10.1101/2024.07.29.605560

Abstract

Vibrio cholerae is a gram-negative curved rod-shaped bacterium responsible for cholera, an intestinal infection characterized by severe acute watery diarrhea that can be fatal if untreated. The major virulence factor for Vibrio cholerae is cholera toxin (ctx), a potent toxin which has two subunits, A and B (ctxAB), that are crucial for the progression of the deadly disease. The B subunit is a pentavalent protein that binds to the intestinal mucosa to allow internalization of the A subunit to initiate rice-watery diarrhea. This study explored potential phytochemicals to inhibit the B subunit from binding to the host mucosa by examining their interaction with ctxB. Proteins encoded by the three genotypes of the ctxB gene (ctxB1, ctxB3, and ctxB7) present in the El Tor biotype strains of V. cholerae O1 responsible for the currently ongoing seventh cholera pandemic were targeted. Analysis of 52 phytochemicals obtained from PubChem identified a group of phytochemicals based on their binding affinity scores with the proteins of ctxB genotypes. Assessment of drug-likeliness and toxicity risk highlighted two phytochemicals, Limonin and Emodin, as the best potential candidates for inhibiting the mode of action of cholera toxin. Molecular dynamic (MD) simulation-based MM-PBSA analysis suggested these compounds stably interact with the receptors. Molecular docking and molecular dynamic simulations revealed that these phytochemicals might have potential to inhibit the cholera toxin function and reduce the severity of cholera.

Author Summary Cholera toxin (ctx) subunits A and B (ctxAB) play a significant role in the disease, with the B subunit facilitating the binding of the toxin to the intestinal cells, and the A subunit entering the cells, resulting in the cellular changes that lead to watery diarrhea. To inhibit the B subunit of cholera toxin from binding host mucosa, we explored candidate phytochemicals instead of synthetic molecules as drug agents by examining their binding behavior with ctxB using a molecular docking approach. The molecular docking, molecular dynamic simulations, and toxicity analyses identified two phytochemical compounds that have the potential to inhibit the mechanism of cholera toxin.

Introduction

Cholera is an acute form of secretory diarrhea, caused by the gram-negative proteobacterium, Vibrio cholerae. The clinical manifestations of cholera involve the continual discharge of abundant fluid exhibiting a rice-water consistency, often leading to severe dehydration [1]. As per the reports of WHO, 2.9 million cases of cholera emerge every year in the approximately 69 cholera-endemic countries and the estimated number of deaths is around 21,000 to 1,43,000 per year [2]. Seven cholera pandemics have been recorded in history since 1817, and the current seventh pandemic started in the early 1960s due to the emergence of Vibrio cholerae O1 biotype El Tor; while the previous pandemics were linked to the classical biotype of the bacterium [3]. El Tor strains are superior to classical strains in terms of host-to-host transmission efficiency and environmental and human host viability [4]. The El Tor strain exhibiting increased gene expression associated with biofilm formation, chemotaxis, and the transfer of iron, peptides, and amino acids, might be a potential reason for the recent upsurge of El Tor cholera worldwide due to the elevated ability of the bacterium to thriving in the aquatic environmental reservoirs [5].

The first-line treatment regimen for cholera is the oral rehydration saline (ORS) [6] fluids. Although ORS is considered the best therapeutic measure, its efficacy is limited. This is because the administration of ORS alone does not alleviate symptoms, eradicate V. cholerae infection, or disrupt the mechanism of action of cholera toxin (CT) [7]. Besides, two doses of effective antibiotics are a convention to shorten the duration of hospitalization and reduce the burden of the pathogen to prevent further disease transmission. Antibiotics like tetracycline, azithromycin, erythromycin, and fluoroquinolone have been employed for cholera disease treatment over the years [8-11]. Unfortunately, extensive use of these antibiotics has demonstrated a concerning trend of developing resistance or multidrug resistance, which is attributed to the acquisition of mobile genetic elements or mutations in one or more genes [12,13]. Bacteriophage therapy is also a potential tool to use against V. cholerae to combat cholera diseases but it has certain drawbacks because bacteria can make themselves resistant to phage infections by inhibiting phage genome injection through the super injection exclusion (Sie) mechanism, a protein-mediated process expressed by prophage [14].

In the course of infection, the cholera toxin (CT) takes part in binding with the specific receptor binding site, the enterocyte monosialoganglioside GM1, on host enterocytes which results in increased levels of cAMP levels causing major secretion of profuse diarrhea filled with water and electrolytes [15]. When the cholera toxin attaches itself with high precision and affinity to the receptor residing on the GM1, there occurs an increase in intestinal secretion, initiating endocytosis and instigating a sustained impact on the enterocyte cytosol [16]. Thus, we designed a therapeutic strategy in which the binding of the cholera toxin with monosialoganglioside GM1 can be prevented with phytochemicals without any adverse effects, which is very crucial. In this study, we conducted molecular docking for identifying potential phytochemicals instead of synthetic molecules as drug molecules that can inhibit cholera toxin. The phytochemicals are preferred over synthetic drugs because the latter might have some adverse effects on the human body [17,18]. For this, we tested 52 phytochemical compounds from PubChem for binding affinity and also examined the drug ability and toxigenicity of the molecules. Although numerous phytochemicals are accessible from PubChem, 52 phytochemicals used in the current study have been selected based on their high antimicrobial, antiviral, and antidiarrheal properties [19-21]. The selected phytochemicals generally display their antimicrobial properties by interfering with the intermediary mechanism, starting the process of cytoplasmic components, altering DNA/RNA synthesis and function, and interfering with regular cell communication [22].

Materials and Methods

Target proteins encoded by the genotypes of the ctxB gene

Initially, the El Tor strains were characterized by the ctxB3 genotype. Since then, they have seen evolutionary modifications and have acquired the classical cholera toxin genotype 1 (ctxB1) [23]. The Haitian cholera toxin (Haitian CT) is a novel variation of the V. cholerae O1 El Tor biotype that appeared after the devastating cyclone in Odisha in October 1999 [2], and in November 1999, the Erasama block in the Jagatsinghpur district reported the very first case of cholera with the ctxB7 genotype [23]. In this study, we considered proteins encoded by the three genotypes ctxB1, ctxB3, and ctxB7 of the El Tor biotype of V. cholerae O1 for molecular docking and dynamic simulation.

Molecular docking and pharmacokinetics analyses

The amino acid sequence of ctxB genotypes collected from NCBI was used for constructing 3D structures using SWISS-MODEL [24]. The 3D structures of the target proteins were visualized using Discovery Studio Visualizer 2019 [25]. PDB2PQR and H++ were used to determine the protonation status of the proteins [26,27]. After that, water molecules, attaching ligands, and heteroatoms were removed using AutoDock tools [28,29]. In addition, the software was used for setting the torsion tree, rotatable and nonrotatable bonds in the phytochemicals, and adding important hydrogen atoms to the target proteins, particularly in the site of binding, though these proteins can be associated with any kind of interaction with the ligands. Then, the entire protein surface was covered by a grid box.

The 3D structures of the phytochemical compounds were downloaded from the PubChem database, and Avogadro was utilized to minimize the energy of the phytochemicals [30,31]. Then, the binding affinities for each of the target proteins and phytochemical compounds were calculated using AutoDock Vina [32]. PyMol [33] and Discovery Studio Visualizer 2019 [25] were used for visualizing the surfaces of complexes, non-covalent interaction types, and distances.

In order to select top-ranked targets and agents, let Xpq represents the binding affinity score corresponding to the pth target protein (p = 1, 2, … r) and qth phytochemicals (q = 1, 2, … s). Then, descending row sums, Embedded Image, sorted target proteins as the receptors and column sums, Embedded Image, sorted lead phytochemicals as the candidate drug agent. Additionally, the canonical SMILES of the top-ranked phytochemicals were used as input for the pharmacokinetic assessments in two integrated online tools-SwissADME [34], and pkCSM [35], that precisely predict the phytochemical pharmacokinetics, drug-like characteristics, and pharmaceutical chemistry-friendly properties.

Molecular dynamic (MD) simulations

The molecular dynamics simulations of the chosen compounds with an AMBER14 force field [36,37] were performed using the YASARA software [38] to ascertain how the top-ranked protein-phytochemical complexes behave dynamically. The MD simulation was performed using nine distinct complexes, comprising three variants of ctxB (ctxB1, ctxB3, and ctxB7), each of which interacted with dehydropipernonaline, emodin, and limonin. The hydrogen bonding structure of the protein-phytochemical complexes was modified and solved with a TIP3P water model. The hydrogen bonding network of the protein-phytochemical complexes was altered and solved using a TIP3P water model before the simulation [39], and 0.990 gL-1 solvent density was used to sustain periodic boundary conditions. During solvation, pKa calculations were performed on the complexes containing titratable amino acids, and at 298 K, pH 7.4, and 0.9 percent NaCl, the simulated systems reached neutralization [40]. The initial energy minimization procedure for all simulation systems, consisting of 23,358, 23,963, and 23,663 atoms for the ctxB1-Dehydropipernonaline, ctxB1-Emodin, and ctxB1-Limonin complexes, respectively, and 23,263, 24,157, and 24,062 atoms for the ctxB3-Dehydropipernonaline, ctxB3-Emodin, and ctxB3-Limonin complexes, and 23,379, 23,707, and 25,038 atoms for the ctxB7-Dehydropipernonaline, ctxB7-Emodin, and ctxB7-Limonin complexes, respectively. The steepest gradient method was used for this optimization process, which involved 5000 cycles for each complex. Every 250 ps, the trajectories were recorded to carry out the subsequent analysis using macro and SciDAVis software (available at http://scidavis.sourceforge.net/). Then, for each snapshot, the MM-Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculation was performed using the following formula in the YASARA script [41,42]. Embedded Image Here, AMBER-14 and the built-in YASARA macros were used as the force field to calculate the MM-PBSA binding energy; higher positive energies suggest improved binding [43].

Results

3D structure of the mutants of ctxB

Vibrio cholerae carries the CT prophage gene, responsible for encoding the cholera toxin which leads to clinical symptoms of the deadly disease cholera [44]. 12 genotypes of ctxB toxin have been identified so far, of which three (ctxB3, ctxB1, and ctxB7) can be identified from the seventh pandemic El Tor strains. Recent genomic analyses showed V. cholerae O1 strains circulating at the Asian (Asian lineage) region contain ctxB1, the strains circulating globally (global lineage) contain ctxB7, and ctxB3 genotype strains seem to exist no longer [13]. Three-point mutations differentiated the three genotypes of ctxB, where both ctxB1 and ctxB7 commonly have 2 mutations and the other one has an additional point mutation (Fig 1a). 3D structures of the proteins encoded by three different genotypes of ctxB showed that ctxB1 and ctxB7 encoded proteins had different configuration than the ctxB3 encoded protein, which might have influence on binding affinities with the ligands (Fig 1b-d).

Fig 1.
Fig 1. ctxB genotypes, binding sites, and their 3D structures.

(a) shows the amino acid sequences of the three mutated genotypes of cholera B toxin. ctxB1 shows amino acid substitution at positions 39, and 68, while ctxB7 undergoes additional mutation at the 20th position [45]. (b-d) displays the 3D structures modeled from the amino acid sequences of the three genotypic variants of the ctxB toxin. The 3D models were visualized using the Pymol [46] software and the area of mutations have been highlighted in red.

Drug Repurposing by Molecular Docking

Molecular docking was carried out for the 52 phytochemicals against encoded proteins of ctxB1, ctxB3, and ctxB7. A total of r = 3 receptors and s = 52 phytochemical compounds were used in the molecular docking process to determine the binding affinity scores (kcal/mol) for each pair of phytochemical compounds and receptors. Afterward, using the row sums of the binding affinity matrix X = (Xpq) to sort the target receptors and the column sums of the phytochemical compounds, we were able to identify just a small number of these compounds as potential candidates (Fig 2). The top 10 phytochemical agents were Limonin, Corilagin, Taraxesterol, Procyanidin, Beta-carotene, Emodin, Dehydropipernonaline, Apigenin, Guineesine, and Benzethonium based on the analysis results with binding affinity scores against the three receptor proteins encoded by ctxB1, ctxB3, and ctxB7 (Table S1 in supplementary information).

Fig 2.
Fig 2. Binding affinities of the top-ordered phytochemical agents against the 3 receptors.

Here, orange to red colors indicate the higher binding affinities of the phytochemicals. A total of 23 phytochemicals were identified with moderate to high binding affinities (<= -6.3) for ctxB1 and ctxB3. Two additional phytochemicals had moderate binding affinities for ctxB7.

Pharmacokinetics of the best phytochemicals

The ADME (Absorption, Distribution, Metabolism, and Excretion) properties of phytochemicals were determined using the ADME predictor [34,35]. The toxicity risk, drug store viability, and drug-likeness of each screened phytochemical were examined. The degree of indemnity and efficacy of the top three lead medications were established by pharmacokinetic characteristic analysis (Table 1). The significant factors that may influence the top-ranked phytochemicals were taken into account, such as molar refractivity, lipophilicity, water solubility, GI absorption, CNS permeability, P-gp substrate, bioavailability score, skin permeation, and Lipinski condition. The analyses revealed three phytochemicals, dehydropipernonaline, emodin, and limonin, as the best candidates for additional screening. They all meet the requirements to be considered as drugs, including lipophilicity (logP <5), molar refractivity of 40-130, high GI absorption, and water solubility (logS >-5). Our chosen phytochemicals comply with Lipinski’s rule, which states that orally active medications generally show no more than one violation of particular physicochemical characteristics, suggesting a good chance of oral absorption and efficacy. Finally, we verified whether our suggested phytochemicals were toxic or not for humans or rats. We find dehydropipernonaline with hepatotoxicity (Table S2 in supplementary information).

View this table:
Table 1. Pharmacokinetics of the best phytochemicals

Binding sites of ctxB and phytochemicals

The GM1 pentasaccharide receptor binds with the protein encoded by the wild-type ctxB (classical, similar to ctxB1) at residues Asn111, Asn35, Lys112, Glu72, Gln82, His78, Ile79, Glu32, Trp109, Tyr33, and His34 [47]. It is therefore interesting to examine the binding sites of phytochemicals with proteins of ctxB genotypes to understand their potential inhibitory properties. To explore this, we analyzed the docked ligand-protein complexes and visualized their 2D and 3D structures (Fig 3). The analysis revealed that the ctxB1-Dehydropipernonaline complex forms two hydrogen bonds and six other hydrophobic bonds. The hydrogen bonds occur at residues Lys112 (conventional) and Asn111 (carbon), while the hydrophobic bonds are at Trp109 (pi-pi stacked and pi-alkyl), Ala85 (alkyl), Ile86 (alkyl), Met89 (alkyl), and Tyr33 (pi-alkyl) (Table 2). Moreover, dehydropipernonaline and GM1 share four common binding amino acid positions to bind with the ctxB1 protein. The ctxB1-Emodin complex forms three conventional hydrogen bonds at residues Gln82, Lys112, and Asn111, along with three hydrophobic bonds at Trp109 (pi-stacked) and Tyr33 (pi-pi T-shaped and pi-alkyl). Consequently, emodin and GM1 share five common amino acid binding positions to bind with ctxB1. The ctxB1-Limonin complex forms two hydrogen bonds at residues Gln82 (conventional) and Ala118 (carbon), and one hydrophobic bond at Ile86 (pi-alkyl). Thus, limonin and GM1 share only one common amino acid position to bind with ctxB1. Structure of the protein encoded by ctxB7 is pretty similar to ctxB1 (Fig 1c-d). Hence, the binding positions of ctxB7-Dehydropipernonaline complex are similar to the ctxB1-Dehydropipernonaline except for an additional hydrogen bond at the Ala85 (carbon) residue. The amino acid residue Lys112 of ctxB1-Emodin complex doesn’t exist to forming the ctxB7-Emodin complex. Lastly, the formation of the ctxB7-Limonin complex is pretty different from ctxB1-Limonin. This complex (ctxB7-Limonin) is formed by two hydrogen bonds at residues Lys112 (conventional) and Glu72 (carbon), and one hydrophobic bond at Trp109 (pi-pi stacked), and all three positions are common for Limonin and GM1 to bind with protein encoded by ctxB7.

View this table:
Table 2. Non-bond interactions between three top-ordered receptors and phytochemicals
Fig 3.
Fig 3. Nine complexes, and their 2D, and 3D chemical interactions.

Using Discovery Studio visualizers, the three-dimensional view of interacting complexes was displayed [21]. The complexes are indicated: (a) ctxB1-Dehydropipernonaline; (b) ctxB1-Emodin; (c) ctxB1-Limonin; (d) ctxB3-Dehydropipernonaline; (e) ctxB3-Emodin; (f) ctxB3-Limonin; (g) ctxB7-Dehydropipernonaline; (h) ctxB7-Emodin; and (i) ctxB7-Limonin.

In addition, the complex of ctxB3 and Dehydropipernonaline forms one conventional hydrogen bond at His68, and six hydrophobic bonds at Leu29, Arg88, Met89, Ala119, Ala85 (pi-alkyl), and Ile86 (pi-alkyl) residues. ctxB3-emodin complex forms two hydrogen bonds at Gln82 (conventional), and His78 (carbon) and three hydrophobic bonds at Trp109 (pi-pi stacked), Tyr33 (pi-pi T-shaped), Ile79 (Alkyl) residues. And, ctxB3-Limonin complex forms two hydrogen bonds at Gln82 and Ala118, and one hydrophobic bond at Ile86.

Molecular Dynamic Simulations

In our analysis, limonin, emodin, and dehydropipernonaline were the top three candidate phytochemicals among those that were revealed as the best candidates. Thereby, the top three phytochemical compounds were selected for 100 ns MD-based MM-PBSA simulations to be used for stability study. Every complex, with the exception of the ctxB3 and emodin complex, was remarkably stable between the initial and moving phytochemical-target complex changes (Fig 4). For each of the three selected phytochemicals, we determined the root mean square deviation (RMSD), and MM-Poisson-Boltzmann surface area (MM-PBSA) corresponding to the receptors.

Fig 4.
Fig 4. Molecular Dynamic simulation results.

The root means square deviations (RMSDs) of the three protein backbone atoms (C, Cα, and N) are displayed in (Fig 4a-c) over time for every docked complex. The binding free energy (in kJ mol−1) of each snapshot, was calculated and is displayed in (Fig 4d-f). Positive values signify stronger binding. Phytochemicals: Green indicates limonin, red indicates emodin, and blue indicates dehydropipernonaline.

An average RMSD less than 2.5Å is considered binding stability for the complexes [48]. Analyses showed the average RMSD was between 1.59-1.91 Å for all of the nine complexes, which indicates their binding stability. As seen in (Fig 4a), every complex displayed almost stable RMSD and MM-PBSA over the times, except the complexes between ctxB1 and limonin and ctxB3 and emodin, which fluctuate frequently during the first few nanoseconds. Eventually, all complexes reached a stable state after 60 ns of the experiment. Here, we determined the MM-PBSA binding free energy for each of the nine complexes that resulted from the pairing of three chosen phytochemicals with three previously identified receptors. The average binding energies were between 58.227 and 142.734 kJ/mol for ctxB1-phytochemical complexes, between -15.038 and 157.331 for ctxB3-phytochem ical complexes, and between 5.837 and 140.373 kJ/mol for ctxB3-phytochemical complexes. Remarkably, we observed that ctxB3 and emodin had average negative binding energies in dynamic simulation, supporting the molecular docking analysis result for this complex (Fig 3).

Discussion and Conclusion

Emergence of multiple antimicrobial resistance against the available antibiotics for treating infectious diseases is a grand challenge which demands alternative therapeutic agents to save lives. In this study, we identified alternative medications for cholera disease, which act by inhibiting the mode of action of cholera toxin. Cholera toxin is a traditional A-B type toxin, which functions constitutively activating AC and causing G protein to be ADP-ribosylated, which raises cyclic AMP levels in the host cell, the rapid discharge of chloride ions by the cystic fibrosis transmembrane conductance regulator (CFTR), the decreased influx of sodium ions, and massive water release via intestinal cells causes acute diarrhea, and vomiting, indicating the initial manifestations of cholera [1]. The cholera toxin initiates its pathogenic effect through the high-affinity attachment of its B subunits to the monosialoganglioside GM1 receptors of the host [49]. Since the key toxin responsible for the pathogenicity of V. cholerae is the ctxB, inhibiting this gene function may prevent the cholera bacterium from acting in its intended manner. We employed a molecular docking technique to find potential phytochemicals as drug agents with antibacterial properties since phytochemicals have lower adverse effects compared to the synthetic drugs [17,18]. We investigated potential phytochemicals by assessing their binding behavior against the CTX subunit B using a molecular docking technique to prevent the B subunit from binding with host mucosa. Molecular docking was used to target proteins encoded by three genotypes of the ctxB gene (ctxB1, ctxB3, and ctxB7) of the El Tor biotype of Vibrio cholerae O1, which is responsible for the currently ongoing 7th cholera pandemic. We examined a pool of 52 phytochemicals obtained from PubChem and identified the top ten compounds (Limonin, Corilagin, Taraxesterol, Procyanidin, Beta Carotene, Emodin, Dehydropipernonaline, Apigenin, Guineesine, and Benzethonium) as primary candidates based on binding affinity scores with the proteins encoded by three different genotypes of ctxB. After doing an ADME analysis, we were able to identify three possible phytochemicals (limonin, emodin, and dehydropipernonaline) that may inhibit the cholera toxin. However, dehydropipernonaline showed hepatotoxicity in our in-silico findings.

The potential phytochemical Limonin identified in this study as an inhibitor of CT can be extracted from citrus fruits, which have been utilized as medical fruit all year round due to their various therapeutic properties, which include vitamin C, flavonoids, carotenoids, folic acid, limonoids, and high-quality soluble fibers [49,50]. Several research investigations have demonstrated the diverse biological and pharmacological properties of limonin, such as its ability to protect the liver and have antiviral, anti-inflammatory, anti-cancer, and anti-oxidative properties [51-55]. One study suggested lemon juice and vinegar as the natural substitute for antibiotics [57]. Emodin has long been utilized as an active component in herbs in traditional Chinese medicine and exhibited diuretic, antibacterial, antiulcer, anti-inflammatory, anticancer, and antinociceptive properties [58]. The fruits of Piper retrofractum Vahl are used for gastroprotective and cholesterol-lowering properties [59]. It contains dehydropipernonaline, which in our investigation showed anti-cholera toxin action, but it may considerably damage the liver due to its hepatotoxicity properties. Our docked complex showed that the suggested phytochemicals bind to the amino acid of ctxB at the several common sites as the GM1 receptor [47]. So, they can be potential compounds to inhibit ctxB from binding with GM1. Additionally, a molecular dynamics simulation incorporating the chosen phytochemicals and cholera toxin mutants, ctxB1, ctxB3, and ctxB7, was run to assess MM-PBSA binding free energy and RMSD of the nine complexes. All parameters consistently showed increased stability in the protein-ligand interaction, except the complex formed by emodin and ctxB3. Therefore, we may conclude two phytochemicals limonin and emodin to be promising for blocking cholera toxin function and preventing the deadly disease. However, validation of these results requires wet-lab synthesis and further in-vivo studies.

Author Information

Author notes

1. Yasmin Akter and Khalilur Rahman equally contributed to this manuscript as co-first authors.

Contributions

M.M.M, M.A., and M.N.H.M developed the study concept and facilitated the nonprofit collaborative partnership. Y.A. collected the necessary information from different sources and performed the molecular docking. The further analysis, including molecular dynamic simulation, was accomplished by K.R. Y.A., and K.R. jointly drafted the manuscript. M.S.R. contributed to organizing the method section. M.M.M. and M.N.H.M. supervised the study. All the authors reviewed and approved the final manuscript.

Corresponding author

Correspondence to Md. Mamun Monir and Md Nurul Haque Mollah

Data Availability

The datasets generated and analyzed during the current study will be available from the corresponding author on request.

Competing interests

The authors declare no competing interests

Supplementary Information

Supplementary Information

Acknowledgments

This project was conducted as a non-profit collaborative effort between icddr,b, and the University of Rajshahi. icddr,b extends its gratitude to the Governments of the People’s Republic of Bangladesh and Global Affairs Canada (GAC) for their unrestricted support. We thank Kazi Ahsan from the School of Medicine at Washington University, St. Louis, USA, for his valuable comments on the draft manuscript, which helped enhance its quality.

Reference

  1. 1.↵
    Kaper JB, Morris JG, Levine MM. Cholera. Clin Microbiol Rev. 1995;8: 48–86. doi:10.1128/CMR.8.1.48
    OpenUrlAbstract/FREE Full Text
  2. 2.↵
    Ali M, Nelson AR, Lopez AL, Sack DA. Updated Global Burden of Cholera in Endemic Countries. PLoS Negl Trop Dis. 2015;9: e0003832. doi:10.1371/journal.pntd.0003832
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Andam CP
    Monir MM, Hossain T, Morita M, Ohnishi M, Johura F-T, Sultana M, et al. Genomic Characteristics of Recently Recognized Vibrio cholerae El Tor Lineages Associated with Cholera in Bangladesh, 1991 to 2017. Andam CP, editor. Microbiol Spectr. 2022;XX. doi:10.1128/SPECTRUM.00391-22
    OpenUrlCrossRef
  4. 4.↵
    1. Baron S
    Finkelstein RA. Cholera, Vibrio cholerae O1 and O139, and Other Pathogenic Vibrios. 4th edition. Baron S, editor. University of Texas Medical Branch at Galveston; 1996. Available: https://www.ncbi.nlm.nih.gov/books/NBK8407/
  5. 5.↵
    Beyhan S, Tischler AD, Camilli A, Yildiz FH. Differences in gene expression between the classical and El Tor biotypes of Vibrio cholerae O1. Infect Immun. 2006;74: 3633–3642. doi:10.1128/IAI.01750-05
    OpenUrlAbstract/FREE Full Text
  6. 6.↵
    Thiagarajah JR, Donowitz M, Verkman AS. Secretory diarrhoea: mechanisms and emerging therapies. Nat Rev Gastroenterol Hepatol. 2015;12: 446–457. doi:10.1038/nrgastro.2015.111
    OpenUrlCrossRefPubMed
  7. 7.↵
    Munos MK, Walker CLF, Black RE. The effect of oral rehydration solution and recommended home fluids on diarrhoea mortality. Int J Epidemiol. 2010;39: i75–i87. doi:10.1093/ije/dyq025
    OpenUrlCrossRefPubMed
  8. 8.↵
    Saha D, Karim MM, Khan WA, Ahmed S, Salam MA, Bennish ML. Single-Dose Azithromycin for the Treatment of Cholera in Adults. New England Journal of Medicine. 2006;354: 2452–2462. doi:10.1056/NEJMoa054493
    OpenUrlCrossRefPubMedWeb of Science
  9. 9.
    Ghosh A, Ramamurthy T. Antimicrobials & cholera: are we stranded? Indian J Med Res. 2011;133: 225–31.
    OpenUrlPubMed
  10. 10.
    Yaghoubi S, Zekiy AO, Krutova M, Gholami M, Kouhsari E, Sholeh M, et al. Tigecycline antibacterial activity, clinical effectiveness, and mechanisms and epidemiology of resistance: narrative review. European Journal of Clinical Microbiology & Infectious Diseases. 2022;41: 1003–1022. doi:10.1007/s10096-020-04121-1
    OpenUrlCrossRef
  11. 11.↵
    Yuan X, Li Y, Vaziri AZ, Kaviar VH, Jin Y, Jin Y, et al. Global status of antimicrobial resistance among environmental isolates of Vibrio cholerae O1/O139: a systematic review and meta-analysis. Antimicrob Resist Infect Control. 2022;11: 62. doi:10.1186/s13756-022-01100-3
    OpenUrlCrossRef
  12. 12.↵
    Narendrakumar L, Gupta S Sen, Johnson JB, Ramamurthy T, Thomas S. Molecular Adaptations and Antibiotic Resistance in Vibrio cholerae : A Communal Challenge. Microbial Drug Resistance. 2019;25: 1012–1022. doi:10.1089/mdr.2018.0354
    OpenUrlCrossRef
  13. 13.↵
    Monir MM, Islam MT, Mazumder R, Mondal D, Nahar KS, Sultana M, et al. Genomic attributes of Vibrio cholerae O1 responsible for 2022 massive cholera outbreak in Bangladesh. Nat Commun. 2023;14: 1154. doi:10.1038/s41467-023-36687-7
    OpenUrlCrossRef
  14. 14.↵
    Kalatzis PG, Castillo D, Katharios P, Middelboe M. Bacteriophage Interactions with Marine Pathogenic Vibrios: Implications for Phage Therapy. Antibiotics. 2018;7: 1–23. doi:10.3390/ANTIBIOTICS7010015
    OpenUrlCrossRef
  15. 15.↵
    Sánchez J, Holmgren J. Cholera toxin structure, gene regulation and pathophysiological and immunological aspects. Cellular and Molecular Life Sciences. 2008;65: 1347–1360. doi:10.1007/s00018-008-7496-5
    OpenUrlCrossRefPubMedWeb of Science
  16. 16.↵
    Cervin J, Wands AM, Casselbrant A, Wu H, Krishnamurthy S, Cvjetkovic A, et al. GM1 ganglioside-independent intoxication by Cholera toxin. PLoS Pathog. 2018;14: e1006862. doi:10.1371/journal.ppat.1006862
    OpenUrlCrossRef
  17. 17.↵
    Farooq S, Ngaini Z. Natural and Synthetic Drugs as Potential Treatment for Coronavirus Disease 2019 (COVID-2019). Chemistry Africa. 2021;4: 1–13. doi:10.1007/s42250-020-00203-x
    OpenUrlCrossRef
  18. 18.↵
    Behzadi A, imani S, Deravi N, Mohammad Taheri Z, mohammadian fatemeh, moraveji zahra, et al. Antiviral Potential of Melissa officinalis L.: A Literature Review. Nutr Metab Insights. 2023;16: 117863882211466. doi:10.1177/11786388221146683
    OpenUrlCrossRef
  19. 19.↵
    Perveen S, Chaudhary H. In silico screening of antibacterial compounds from herbal sources against vibrio cholerae. Pharmacogn Mag. 2015;11: 550. doi:10.4103/0973-1296.172960
    OpenUrlCrossRef
  20. 20.
    Ahsan M, Chowdbury AKA, Islam SN, Ahmed ZU. Garlic Extract and Allicin: Broad Spectrum Antibacterial Agents Effective Against Multiple Drug Resistant Strains ofShigella dysenteriae type 1 andShigella flexneri, EnterotoxigenicEscherichia coli andVibrio cholerae. Phytotherapy Research. 1996;10: 329–331. doi:10.1002/(SICI)1099-1573(199606)10:4<329::AID-PTR826>3.0.CO;2-2
    OpenUrlCrossRef
  21. 21.↵
    Barbieri R, Coppo E, Marchese A, Daglia M, Sobarzo-Sánchez E, Nabavi SF, et al. Phytochemicals for human disease: An update on plant-derived compounds antibacterial activity. Microbiol Res. 2017;196: 44–68. doi:10.1016/j.micres.2016.12.003
    OpenUrlCrossRef
  22. 22.↵
    Monte J, Abreu A, Borges A, Simões L, Simões M. Antimicrobial Activity of Selected Phytochemicals against Escherichia coli and Staphylococcus aureus and Their Biofilms. Pathogens. 2014;3: 473–498. doi:10.3390/pathogens3020473
    OpenUrlCrossRefPubMed
  23. 23.↵
    Pal BB, Behera DR, Nayak SR, Nayak AK. Origin and Dissemination of Altered El Tor Vibrio cholerae O1 Causing Cholera in Odisha, India: Two and Half Decade’s View. Front Microbiol. 2021;12. doi:10.3389/fmicb.2021.757986
    OpenUrlCrossRef
  24. 24.↵
    Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46: W296– W303. doi:10.1093/nar/gky427
    OpenUrlCrossRefPubMed
  25. 25.↵
    San Diego. BIOVIA, Dassault Systèmes, Discovery Studio Visualizer, v21.1.0.20298, San Diego: Dassault Systèmes, [2020]. 2005.
  26. 26.↵
    Dolinsky TJ, Czodrowski P, Li H, Nielsen JE, Jensen JH, Klebe G, et al. PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations. Nucleic Acids Res. 2007;35: W522–W525. doi:10.1093/nar/gkm276
    OpenUrlCrossRefPubMedWeb of Science
  27. 27.↵
    Gordon JC, Myers JB, Folta T, Shoja V, Heath LS, Onufriev A. H++: a server for estimating pKas and adding missing hydrogens to macromolecules. Nucleic Acids Res. 2005;33: W368–W371. doi:10.1093/nar/gki464
    OpenUrlCrossRefPubMedWeb of Science
  28. 28.↵
    Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009;30: 2785–2791. doi:10.1002/jcc.21256
    OpenUrlCrossRefPubMedWeb of Science
  29. 29.↵
    Azam SS, Abbasi SW. Molecular docking studies for the identification of novel melatoninergic inhibitors for acetylserotonin-O-methyltransferase using different docking routines. Theor Biol Med Model. 2013;10: 63. doi:10.1186/1742-4682-10-63
    OpenUrlCrossRef
  30. 30.↵
    Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, et al. PubChem 2019 update: improved access to chemical data. Nucleic Acids Res. 2019;47: D1102–D1109. doi:10.1093/nar/gky1033
    OpenUrlCrossRefPubMed
  31. 31.↵
    Hanwell MD, Curtis DE, Lonie DC, Vandermeersch T, Zurek E, Hutchison GR. Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. J Cheminform. 2012;4: 17. doi:10.1186/1758-2946-4-17
    OpenUrlCrossRefPubMed
  32. 32.↵
    Trott O, Olson AJ. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2009; NA-NA. doi:10.1002/jcc.21334
    OpenUrlCrossRefPubMedWeb of Science
  33. 33.↵
    Warren L. DeLano, Sarina Bromberg. PyMOL User’s Guide. DeLano Scientific LLC. 2004.
  34. 34.↵
    Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7: 42717. doi:10.1038/srep42717
    OpenUrlCrossRefPubMed
  35. 35.↵
    Pires DE V., Blundell TL, Ascher DB. pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures. J Med Chem. 2015;58: 4066–4072. doi:10.1021/acs.jmedchem.5b00104
    OpenUrlCrossRefPubMed
  36. 36.↵
    Case DA, Cheatham TE, Darden T, Gohlke H, Luo R, Merz KM, et al. The Amber biomolecular simulation programs. J Comput Chem. 2005;26: 1668–1688. doi:10.1002/jcc.20290
    OpenUrlCrossRefPubMedWeb of Science
  37. 37.↵
    Dickson CJ, Madej BD, Skjevik ÅA, Betz RM, Teigen K, Gould IR, et al. Lipid14: The Amber Lipid Force Field. J Chem Theory Comput. 2014;10: 865–879. doi:10.1021/ct4010307
    OpenUrlCrossRefPubMed
  38. 38.↵
    Elmar Krieger, Gert Vriend, Chris Spronk. YASARA - Yet Another Scientific Artificial Reality Application. Available: http://www.yasara.org/
  39. 39.↵
    Boonstra S, Onck PR, van der Giessen E. CHARMM TIP3P Water Model Suppresses Peptide Folding by Solvating the Unfolded State. J Phys Chem B. 2016;120: 3692–3698. doi:10.1021/acs.jpcb.6b01316
    OpenUrlCrossRef
  40. 40.↵
    Krieger E, Vriend G. New ways to boost molecular dynamics simulations. J Comput Chem. 2015;36: 996–1007. doi:10.1002/jcc.23899
    OpenUrlCrossRefPubMed
  41. 41.↵
    Mitra S, Dash R. Structural dynamics and quantum mechanical aspects of shikonin derivatives as CREBBP bromodomain inhibitors. J Mol Graph Model. 2018;83: 42–52. doi:10.1016/j.jmgm.2018.04.014
    OpenUrlCrossRef
  42. 42.↵
    Weis A, Katebzadeh K, Söderhjelm P, Nilsson I, Ryde U. Ligand Affinities Predicted with the MM/PBSA Method: Dependence on the Simulation Method and the Force Field. J Med Chem. 2006;49: 6596–6606. doi:10.1021/jm0608210
    OpenUrlCrossRefPubMed
  43. 43.↵
    Srinivasan E, Rajasekaran R. Computational investigation of curcumin, a natural polyphenol that inhibits the destabilization and the aggregation of human SOD1 mutant (Ala4Val). RSC Adv. 2016;6: 102744–102753. doi:10.1039/C6RA21927F
    OpenUrlCrossRef
  44. 44.↵
    Tor E. CtxB 1 outcompetes CtxB 7 in Vibrio cholerae O1, Bangladesh. 2017;2011: 2010–2013.
    OpenUrl
  45. 45.↵
    Baek Y, Lee D, Lee J, Yoon Y, Nair GB, Kim DW, et al. Cholera Toxin Production in Vibrio cholerae O1 El Tor Biotype Strains in Single-Phase Culture. Front Microbiol. 2020;11. doi:10.3389/fmicb.2020.00825
    OpenUrlCrossRef
  46. 46.↵
    Schrödinger L, DeLano W. PyMOL. 2020. Available: http://www.pymol.org/pymol
  47. 47.↵
    Merritt EA, Sarfaty S, Hol WGJ, Jobling MG, Holmes RK, Chang T, et al. Structural studies of receptor binding by cholera toxin mutants. Protein Science. 1997;6: 1516–1528. doi:10.1002/pro.5560060716
    OpenUrlCrossRefPubMedWeb of Science
  48. 48.↵
    Ashraf N, Asari A, Yousaf N, Ahmad M, Ahmed M, Faisal A, et al. Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors. Front Chem. 2022;10. doi:10.3389/fchem.2022.1003816
    OpenUrlCrossRef
  49. 49.↵
    Merritt EA, Sarfaty S, Akker F van den, L’Hoir C, Martial JA, Hol WG. Crystal structure of cholera toxin B-pentamer bound to receptor GM1 pentasaccharide. Protein Sci. 1994;3: 166. doi:10.1002/PRO.5560030202
    OpenUrlCrossRefPubMedWeb of Science
  50. 50.↵
    Klimek-Szczykutowicz M, Szopa A, Ekiert H. Citrus limon (Lemon) Phenomenon—A Review of the Chemistry, Pharmacological Properties, Applications in the Modern Pharmaceutical, Food, and Cosmetics Industries, and Biotechnological Studies. Plants 2020, Vol 9, Page 119. 2020;9: 119. doi:10.3390/PLANTS9010119
    OpenUrlCrossRef
  51. 51.↵
    Ciriminna R, Fidalgo A, Scurria A, Sciortino M, Lino C, Meneguzzo F, et al. The Case for a Lemon Bioeconomy. Adv Sustain Syst. 2020;4: 2000006. doi:10.1002/ADSU.202000006
    OpenUrlCrossRef
  52. 52.
    Fan S, Zhang C, Luo T, Wang J, Tang Y, Chen Z, et al. Limonin: A Review of Its Pharmacology, Toxicity, and Pharmacokinetics. Molecules. 2019;24. doi:10.3390/MOLECULES24203679
    OpenUrlCrossRef
  53. 53.
    Bae JR, Park WH, Suh DH, No JH, Kim YB, Kim K. Role of limonin in anticancer effects of Evodia rutaecarpa on ovarian cancer cells. BMC Complementary Medicine and Therapies 2020 20:1. 2020;20: 1–13. doi:10.1186/S12906-020-02890-Y
    OpenUrlCrossRef
  54. 54.
    Shimizu S, Miyamoto S, Fujii G, Nakanishi R, Onuma W, Ozaki Y, et al. Suppression of intestinal carcinogenesis in Apc-mutant mice by limonin. J Clin Biochem Nutr. 2015;57: 39–43. doi:10.3164/JCBN.15-28
    OpenUrlCrossRef
  55. 55.↵
    Qin S, Lv C, Wang Q, Zheng Z, Sun X, Tang M, et al. Extraction, identification, and antioxidant property evaluation of limonin from pummelo seeds. Animal Nutrition. 2018;4: 281. doi:10.1016/J.ANINU.2018.05.005
    OpenUrlCrossRef
  56. 56.
    Balestrieri E, Pizzimenti F, Ferlazzo A, Giofr S V., Iannazzo D, Piperno A, et al. Antiviral activity of seed extract from Citrus bergamia towards human retroviruses. Bioorg Med Chem. 2011;19: 2084–2089. doi:10.1016/J.BMC.2011.01.024
    OpenUrlCrossRefPubMed
  57. 57.↵
    Alsaraf KM, Abd ST, Hussein NS, Jabor AA. International Journal of Advanced Research in Biological Sciences In vitro Evaluation the effect of Natural Products against Vibrio cholerae. Int J Adv Res Biol Sci. 2016;3: 271–275. Available: http://s-o-i.org/1.15/ijarbs-2016-3-3-35
    OpenUrl
  58. 58.↵
    Stompor-Goracy M. The Health Benefits of Emodin, a Natural Anthraquinone Derived from Rhubarb—A Summary Update. International Journal of Molecular Sciences 2021, Vol 22, Page 9522. 2021;22: 9522. doi:10.3390/IJMS22179522
    OpenUrlCrossRef
  59. 59.↵
    Kim KJ, Lee MS, Jo K, Hwang JK. Piperidine alkaloids from Piper retrofractum Vahl. protect against high-fat diet-induced obesity by regulating lipid metabolism and activating AMP-activated protein kinase. Biochem Biophys Res Commun. 2011;411: 219–225. doi:10.1016/J.BBRC.2011.06.153
    OpenUrlCrossRef
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Posted July 29, 2024.
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Detection of Potential Phytochemicals against ctxAB Toxin to Combat Cholera
Yasmin Akter, Khalilur Rahman, Md Selim Reza, Abdullah Al-Mamun, Munirul Alam, Md Nurul Haque Mollah, Md. Mamun Monir
bioRxiv 2024.07.29.605560; doi: https://doi.org/10.1101/2024.07.29.605560
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