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Research Article
2025
:37;
1142024
doi:
10.25259/JKSUS_114_2024

Revealing potential dual inhibitors from Trigonella foenumgraecum components against AcrAB-TolC drug efflux pump and lipopolysac-charide in E. coli: In silico and molecular dynamics exploration

Department of Medical applied Science, Medical applied Science, Department of Medical Laboratory, College of Applied Medical Sciences-Shaqra, Sh, Shaqra, 11961, Saudi Arabia

* Corresponding author E-mail address: ralenazy@su.edu.sa (R. Alenazy)

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

Abstract

Gram-negative bacterial infections render serious public health problems worldwide. Drug efflux pumps in bacterial pathogens are one of the main mechanisms of resistance due to their ability to expel antimicrobials from the cell. The resistance-nodulation-division (RND) drug efflux pump superfamily has an important role in multidrug resistance (MDR) due to its role in conferring MDR to many bacterial species. The multidrug efflux pump AcrAB-TolC, which belongs to E. coli, a member of RND, and is considered one of the best models that could be targeted for studying to understand MDR, due to the availability of its functional and chemical structures and the similarity of these structures in many negative bacterial species. Furthermore, Gram-negative bacteria have an outer membrane, containing lipopolysaccharide (LPS), which plays a major role in innate resistance by preventing many antimicrobials from entering the bacteria. In this research, based on findings from our previous work, we employed in silico methods to identify and evaluate nine Fenugreek (Trigonella foenum-graecum L.) compounds for their ability to target the AcrAB-TolC and LPS outer membrane (OM) assembly pathways in E. coli, including LptD and BamD. Subsequently, we used computer simulations to predict the compound’s behavior at the molecular level, drug-likeness properties, and ADMET properties. Among all compounds identified in Fenugreeks, gamma-tocopherol was the most promising candidate. It exhibited favorable binding interactions with both the AcrAB-TolC pump and LptD protein, weakening the bacterial cell wall and increasing its permeability to antibiotics. Furthermore, gamma-tocopherol exhibited a good level of flexibility and minimal movement within the protein in hinge regions. Using web-based predictive tools, the notable Fenugreek compounds exhibited promising drug-like properties, low hepatotoxicity, and cytotoxicity. While further investigation is needed, this study highlights the potential of Fenugreek-derived compounds as efflux pump inhibitors (EPIs) for developing novel therapeutics against MDR E. coli infections, particularly gamma-tocopherol, warranting further exploration of their therapeutic potential.

Keywords

AcrAB-TolC
E. coli
Efflux pump inhibitors
Lipopolysaccharides (LPS)
in silico predictions
Outer-membrane proteins
Trigonella foenumgraecum

1. Introduction

The emergence of multidrug-resistant bacteria and the limited development of novel antimicrobials present a serious challenge to global public health. Pathogenic bacteria possess different antibiotic-resistance mechanisms; multidrug efflux pumps are the main mechanism as to playing a significant role in expelling various antimicrobials from the cell. These pumps are located across the entire cell surface, implicated in virulence and pathogenesis. Gram-negative bacteria contain several drug efflux pump superfamilies. The nodulation-cell division (RND) superfamily represents a main superfamily due to conferring multi-drug resistance (MDR) to different bacterial strains and species (Schuster et al., 2017; Colclough et al., 2020; Fanelli et al., 2023). Drug efflux pumps can actively extrude a wide range of toxic compounds, encompassing antibiotics, biocides, quorum-sensing molecules, dyes, and metabolites from the bacterial cytoplasm to the external environment (Blanco et al., 2018; Du et al., 2018). Their distinct characteristics make them promising targets for a new treatment that aims to make traditional antibiotics effective again.

The AcrAB-TolC efflux pump in Gram-negative bacteria plays a critical role in eliminating a diverse range of substances. These compounds can be intercepted before entering the cell or actively transported away from their cytoplasmic targets by transporters in the plasma membrane (Schuldiner, 2018; Shuster et al., 2016). E. coli has great clinical importance, which prompted its use in this study. E. coli is the most prevalent Gram-negative pathogen causing human infections with diverse characteristics (Yang et al., 2017). Enterotoxigenic E. coli (ETEC) is the most common cause of diarrheal illness, while uropathogenic E. coli (UPEC) is frequently implicated in urinary tract infections (UTIs). Additionally, E. coli strains can cause neonatal meningitis (NMEC) and various enteric infections categorized into distinct pathotypes (Clements et al., 2012; Desvaux et al., 2020). Certain strains of E. coli gain their ability to cause disease through the horizontal acquisition of virulence factors (Kaper et al., 2004). Notably, E. coli includes commensal strains that persist in the human and animal gastrointestinal tract shortly following parturition (Braz et al., 2020). E. coli encodes a diverse array of multidrug transporters that contribute to resistance against a wide range of antibiotics upon overexpression (Nishino and Yamaguchi, 2001). Antibiotic-resistant E. coli strains can readily transfer resistance determinants to other bacteria within the gastrointestinal tract, further exacerbating the problem (Rasheed et al., 2014).

Among the Enterobacterales family, the AcrAB-TolC efflux pump complex exemplifies exceptional medical importance for its role in recognizing various antimicrobials and then contributing to their expulsion from the cell. This tripartite complex consists of three subunits: AcrB, AcrA, and TolC. AcrB, an inner membrane protein utilizing proton motive force (pmf) in substrate translocation, identifies and then expels substrates inside the pump, while TolC, an outer membrane protein located in the channel, promotes substrate removal out of the cell, whereas AcrA, a periplasmic adapter protein linking AcrB with TolC (Kobylka et al., 2020; Alenazy, 2022). The periplasmic transport domain exhibits further structural organization, consisting of two distinct regions: the inner membrane-proximal porter domain and the distal funnel domain (Rajapaksha et al., 2021). The main contributing factors to MDR in E. coli are increased constituent levels in the AcrAB-TolC efflux pump system. (Du et al., 2015; Silhavy et al., 2010). Therefore, the discovery of EPIs represents a critical strategy to combat the rise of antibiotic resistance and restore the efficacy of compromised antibiotics.

Moreover, there are many different pathways for the lipopolysaccharide (LPS) transport (Lpt) system, such as LPS transport, the β-barrel assembly machine (BAM) complex, and localization of lipoproteins (Konovalova et al., 2017; Raetz and Whitfield, 2002). LPS, also called endotoxin, is a crucial molecule on the outer surface of Gram-negative bacteria that contributes to their virulence (Villa et al., 2013). LPt systems are included in distinct proteins and facilitate LPS transport across the periplasm and outer membrane (Gu et al., 2017). LptD is unique for being a single protein that folds into a massive β-barrel structure. This compartmentalized transport highlights the Lpt system components as potential targets for novel therapeutic development.

In this study, we targeted the components of Fenugreek (Trigonella foenumgraecum), which belongs to the Fabaceae family. T. foenumgraecum is widely consumed as a spice. (Yadav and Baquer, 2014). Both seeds and leaves serve as culinary ingredients in diverse global cuisines and possess functional nutraceutical and physiological uses. (Chalghoumi et al., 2016). Despite Fenugreek holding well-established antimicrobial properties (Sharma et al., 2017; Mawahib et al., 2015; Sulieman et al., 2008; Abdel-massih et al., 2010; Samreen et al., 2023) and its potentialities having been widely investigated in the past, its role as EPIs remains poorly explored.

In silico approaches can be ligand-based, using existing information on inhibitor substrates, and structure-based, relying on known crystal structures (Abdel-massih et al., 2010). This allows for rapid virtual screening of natural compounds from medicinal plants to identify those with potential efflux pump inhibitory (EPI) activity. Employing in silico screening and in vitro assays significantly shortens the drug discovery timeline and discards less effective compounds early. This allows for rapid virtual screening of natural compounds from medicinal plants to identify those with potential EPI activity (Macalino et al., 2020).

In our previous work, we evaluated the in vitro antibacterial activity of a Fenugreek seed extract against E. coli (Alenazy, 2023). Here, we reassessed the identified natural Fenugreek compounds, which could potentially have inhibitory activity against AcrB and TolC from AcrAB-TolC and LptD, and BamD proteins from LPS, playing the main role in assembling OM proteins and bacterial growth in E. coli. The shortlisted compounds were evaluated for their stability, molecular dynamics, and physicochemical properties using in silico techniques.

2. Materials and Methods

2.1 Receptor preparation for docking simulations

To prepare the target proteins for docking simulations and achieve more refined receptor targeting, 4D crystal structures of AcrB (PDB: 1T9Y) (Ruiz et al., 2006), TolC (PDB: 1EK9) (Lipinski et al., 2001), LPS assembly protein (LptD) (PDB: 4RHB), and outer membrane protein assembly factor (BamD) (PDB: 5D0O) from E. coli were retrieved from the Protein Data Bank repository (https://www.rcsb.org/). These structures included co-crystallized ligands and water molecules, which were subsequently removed to allow for the docking of the shortlisted phytochemicals. Furthermore, any polar hydrogen atoms and other heteroatoms were added to the protein structures to account for their role in potential interactions with the ligands during docking. UCSF Chimera X software version 1.6.1 (Koronakis et al., 2000) was employed to prepare the protein structures for virtual screening and docking simulations. Following these preparation steps, the refined protein structures were saved in an improved PDB file format.

2.2 Ligand selection and preparation

Guided by antimicrobial properties, we previously isolated phytochemicals from T. foenumgraecum (Alenazy, 2023) to evaluate their role as EP and assemble OM protein inhibitors. To facilitate molecular docking simulations, the structures of these nine targeted ligands were retrieved from the PubChem-NCBI database (https://pubchem.ncbi.nlm.nih.gov/) in the simplified molecular input line entry system (SMILES) format (Table S1). To ensure optimal conformation and minimized energy for docking simulations, the retrieved ligand structures underwent further processing. This optimization step utilized Avogadro software version 1.2.0. (Pettersen et al., 2021). The software employed the Merck Molecular Force Field (MMFF) with the following parameters: 1000 minimization steps, the Conjugate Gradient algorithm, and a convergence criterion of 10-6. Finally, the optimized chemical structures were saved in the MOL2 file format.

Table S1

2.3 Binding pocket identification and druggability assessment

We identified and analyzed potential ligand-binding sites within the selected protein structures using FPocketWeb 1.0.1, a web-based tool that applies the FPocket algorithm.

2.4 Molecular docking simulations

In silico docking simulations were performed using the CB-Dock2 web server (https://cadd.labshare.cn/cb-dock2/) to predict how the selected ligands might interact with the target proteins. This platform offers a multi-step approach, first identifying potential binding pockets on the protein surface (cavity detection). Each ligand was then virtually placed within these pockets (docking) to simulate potential binding interactions with the surrounding amino acid residues. CB-Dock2 assigned a binding energy score to each ligand-protein complex, with higher scores indicating a more favorable and stable interaction. Following the docking simulations, we focused on the top-scoring pose (conformation) for each ligand-receptor pair. CB-Dock2 provided detailed information for these top poses, including numerical binding energy values, visual interaction diagrams depicting the specific contacts between ligand and protein residues, and textual descriptions highlighting key amino acids involved in the predicted binding. To further examine these interactions, we employed Discovery Studio Visualizer version 21.1.0.20298 for generating 2D visualizations of the interaction diagrams, while UCSF Chimera X software version 1.6.1 was used to create 3D images of the top-ranked ligand-receptor complexes, providing a more realistic representation of the potential binding mode.

2.5 In Silico prediction of ADMET properties

To assess the drug-likeness and potential for oral bioavailability of the shortlisted compounds with favorable binding energies, we employed the freely available Swiss ADME web tool (www.swissadme.ch) developed by the Swiss Institute of Bioinformatics (Avery et al., 2018). This platform offers in silico predictions of various pharmacokinetic properties encompassing absorption, distribution, metabolism, and excretion (ADME). The SDF files containing the chemical structures of the selected ligands, previously prepared for docking simulations, were uploaded to SwissADME. The software then computed critical physicochemical properties for each compound.

2.6 Molecular dynamics simulation

Protein-ligand complexes were chosen for further analysis based on their binding affinity scores obtained from the docking simulations. The stability of the protein-ligand complexes identified through docking simulations, normal mode analysis (NMA) was employed for the main-chain deformability, mobility profiles, eigenvalues, variance, covariance matrix, and elastic network model. The geometries of the shortlisted protein-ligand complexes were uploaded to the iMODS server (https://bio.tools/imods). The results obtained from main-chain deformability were likely visualized using GraphPad Prism 5 software (GraphPad Software, San Diego, CA, USA).

2.7 In Silico prediction of toxicity

To assess the potential safety profile of the T. foenumgraecum-derived compounds alongside their pharmacokinetic properties, we employed the ProTox-II web server (https://tox-new.charite.de/protoxII/index.php?site=compound_input) (Daina et al., 2017; Banerjee et al., 2018) for in silico prediction of toxicity. This online platform offers a comprehensive suite of models for various toxicological endpoints. Legends were converted into the SMILES format before being uploaded to the server.

3. Results

3.1 Molecular docking analysis of ligands with target proteins

Utilizing docking simulations, the study of gamma-tocopherol showed the strongest predicted binding to all proteins (Table 1) (more negative scores indicating stronger interactions, a more stable complex). Among T. foenumgraecum components, gamma-tocopherol stood out as the lead candidate for AcrB modulation based on its exceptional docking score of -7.9 kcal/mol (Fig. 1). Its predicted binding mode involves non-conventional hydrogen bonds with LEU137, LEU293, ALA39, ALA299, SER135, ILE38, and MET862 in E. coli, forming alkyl and pi-sigma, and a noteworthy positive-positive interaction, potentially influencing complex stability (Fig. 1).

Table 1. Binding energy (kcal/mol) of Trigonella foenumgraecum compounds.
Compound name 1T9Y* 1EK9** 4RHB*** 5D0O****
Phenol, Phenol, 2-methoxy-3-(2-propenyl) -5.1 -5.5 -5.7 -6.7
palmitic acid -6.4 -5.2 -5.7 -5.8
linolenic acid -5.6 -6 -6.1 -6.5
9,12-Octadecadienoic acid -6 -5.8 -5.8 -6.3
butyl linoleate -5.3 -5.8 -6.7 -5.6
trimethylsilyl(9Z,12Z)-octadeca-9, 12-dienoate -5.6 -5.9 -5.8 -6
3H,6H-Thieno [3,4-c]isoxazole -5.1 -5.5 -6.5 -5.7
E,Z-1,3,12-Nonadecatriene -5.7 -5.6 -6.6 -5.8
gamma.-Tocopherol -7.9 -7.7 -8.4 -7.8

Proteins: *: AcrB; **: TolC; ***: LPS assembly protein (LptD); ****: Outer membrane protein assembly factor (BamD).

Predicted binding modes for AcrB-ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the AcrB protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of AcrB (1T9Y) protein with gamma-tocopherol.
Fig. 1.
Predicted binding modes for AcrB-ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the AcrB protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of AcrB (1T9Y) protein with gamma-tocopherol.

The most effective gamma tocopherol-TolC binding pose is shown in Fig. 2 with different interactions for amino acids, including alkyl and pi-alkyl bonds with PHE201, LEU398, LEU407, LEU415, LYS401, ALA401, and pi-sigma with ALA418. Key intermolecular contacts contributing to gamma-tocopherol’s predicted LptD binding, identified through docking, include alkyl and pi-alkyl bonds with LEU532, ALA553, TYR584, ILA595, and TRP597, and a pi-pi-T-shaped, pi-anion with TRP597, ASP593, respectively (Fig. 3).

Predicted binding modes for TolC-ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the TolC protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of TolC (1EK9) protein with gamma-tocopherol
Fig. 2.
Predicted binding modes for TolC-ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the TolC protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of TolC (1EK9) protein with gamma-tocopherol
Predicted binding modes for LptD–ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the LptD protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of LptD (4RHB) protein with gamma-tocopherol.
Fig. 3.
Predicted binding modes for LptD–ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the LptD protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of LptD (4RHB) protein with gamma-tocopherol.

The interactions with the target protein revealed non-conventional hydrogen bonds with Tyr60, Pro249, Val286, and Leu326, as well as one unfavorably electrostatic interaction involving the Tyr60 amino acid (Fig. 4). Meanwhile, glamour-tocopherol showed the highest blocking activity against BamD with a binding affinity of -7.8 kcal/mol (Fig. 4). The highest binding for this compound was represented in separate root-mean-square deviation (RMSD), lower-bound (l.b.), and up-per-bound (u.b.) values for both the RMSD u.b. and RMSD l.b. groups (Table S2).

Table S2
Predicted binding modes for BamD-ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the BamD protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of BamD (5D0O) protein with gamma-tocopherol
Fig. 4.
Predicted binding modes for BamD-ligand docked complexes. (a) Pose view of the interaction of gamma-tocopherol with the BamD protein, (b) 2D interaction of gamma-tocopherol with key residues, (c) Box plot depicting binding affinity scores for predictions of BamD (5D0O) protein with gamma-tocopherol

3.2 In silico prediction of ADME property of selected ligands

We applied Lipinski’s Rule of Five (RO5) to assess the drug-likeness of the plant-derived compounds. This rule suggests specific criteria for molecules that have good oral bioavailability: molecular weight below 500, less than five hydrogen bond donors, less than 10 hydrogen bond acceptors, a Log P value (partition coefficient) below 5, and a molar refractivity within the range of 40-130. The results showed that compounds with the lowest binding energies to the target proteins met Lipinski’s RO5 criteria (Table 2).

Table 2. Physicochemical properties, lipophilicity, and drug-likeness of Trigonella foenumgraecum compounds from the SwissADME web server.
Compound name Molecular weight (g/mol) Hydrogen bonds
Log P* (iLogPo/w) Molar refractivity RO5 violation**
Donor Acceptor
Phenol, Phenol, 2-methoxy-3-(2-propenyl) 164.2 1 2 2.01 49.06 0
palmitic acid 256.42 1 2 4.19 80.8 1
linolenic acid 278.43 1 2 6.46 88.99 1
9,12-Octadecadienoic acid 280.45 1 2 4.47 89.46 1
butyl linoleate 336.55 0 2 N/C*** 108.21 N/C
trimethylsilyl(9Z,12Z)-octadeca-9,12-dienoate 352.63 0 2 5.15 111.27 1
3H,6H-Thieno [3,4-c]isoxazole 171.26 0 2 1.57 52.03 0
E,Z-1,3,12-Nonadecatriene 262.47 0 0 5.89 92.03 1
gamma.-Tocopherol 416.68 1 2 5.94 134.31 1

*: octanol–water partition coefficient; **: Lipinski rule of five; ***: not calculated.

3.3 In silico prediction of toxicity parameters of selected ligands

In silico analysis showed a favorable safety profile for all T. foenumgraecum compounds. Most compounds belonged to toxicity class 6 (indicating low concern), suggesting minimal toxicity (Table 3). All compounds displayed potential for gastrointestinal tract absorption except limitations predicted for blood-brain barrier (BBB) permeability. Specifically, 3H,6H-Thieno [3,4-c]isoxazole, and gamma-tocopherol were predicted to have limited BBB permeability (Table S3). Detailed organ toxicity prediction (Table S4) showed most compounds to be nontoxic, except butyl linoleate and 3H,6H-Thieno [3,4-c]isoxazole, which were predicted to have potential carcinogenicity. Analysis of nuclear receptor signalling pathways (Table S5) revealed minimal predicted off-target effects, except for 9,12-Octadecadienoic acid, which might activate the peroxisome proliferator-activated receptor gamma pathway.

Table S3

Table S4

Table S5
Table 3. Predicted acute oral toxicity of Trigonella foenum-graecum compounds from the ProTox-II web server.
Compound name LD50 (mg/kg) Predicted toxicity class* Average similarity (%) Prediction accuracy (%)
Phenol, Phenol, 2-methoxy-3-(2-propenyl) 1230 4 75.44 69.26
palmitic acid 900 4 100 100
linolenic acid 10000 6 100 100
9,12-Octadecadienoic acid 10000 6 100 100
butyl linoleate 20000 6 93.06 72.9
trimethylsilyl(9Z,12Z)-octadeca-9,12-dienoate 20000 6 70 68.07
3H,6H-Thieno [3,4-c]isoxazole 2676 5 37.51 23
E,Z-1,3,12-Nonadecatriene 5000 5 84.98 70.97
gamma.-Tocopherol 5000 5 79.32 69.26

* Class 1: fatal if swallowed (LD50 ≤ 5); Class 2: fatal if swallowed (5 < LD50 ≤ 50); Class 3: toxic if swallowed (50 < LD50 ≤ 300); Class 4: harmful if swallowed (300 < LD50 ≤ 2000); Class 5: may be harmful if swallowed (2000 < LD50 ≤ 5000); Class 6: nontoxic (LD50 > 5000).

3.4 Molecular dynamics simulation

Molecular dynamics (MD) simulations provided a detailed, atomic-level view of the protein’s hinge regions and how they behaved upon ligand binding. The analysis of main-chain deformability revealed that most residues within the hinge regions between the ligand and protein were medium to highly flexible, indicating their ability to bend or twist easily (Figs. 5, S1a, S1b, and S1c). Interestingly, the docked LptD-gamma-tocopherol complex exhibited the lowest eigenvalues, a stiffness of a molecule’s motion, signifying the least deformability and energy required for any shape changes within the complex (Fig. S2). This suggests a highly stable interaction between gamma-tocopherol and the LptD protein.

Figure S1

Figure S2
AcrB-γ-Tocopherol complex: molecular dynamics simulation. (a) Deformability, (b) Eigenvalues, (c) Variance (Blue: individual variances, green: cumulative variances), (d) Co-variance map (residues with correlated motions in red, uncorrelated motions in white, and anti-correlated motions in blue), (e) Elastic network analysis
Fig. 5.
AcrB-γ-Tocopherol complex: molecular dynamics simulation. (a) Deformability, (b) Eigenvalues, (c) Variance (Blue: individual variances, green: cumulative variances), (d) Co-variance map (residues with correlated motions in red, uncorrelated motions in white, and anti-correlated motions in blue), (e) Elastic network analysis

The analysis of variance provided insights into the dynamic fluctuations within the protein-ligand complexes after docking simulations. (Fig. 5) differentiates between individual and cumulative contributions to these fluctuations.

The TolC-gamma-tocopherol complex displayed the lowest overall variance (Fig. S1c). In contrast, the variance plot revealed that the LptD-gamma-tocopherol complex exhibited a high level of individual variance (48%) (Fig. S2c), indicating significant mobility within the complex.

Visualized through covariance matrices (Fig. 5), the covariance analysis assessed the correlated motions between amino acid residues within the protein-ligand complexes. These matrices indicated predominantly strong positive correlations (red color) between residues, signifying coordinated movements. Conversely, several blue-colored areas represented anti-correlations, where residues moved in opposing directions. White-coloured regions suggested no correlation in motion between residues. Overall, these findings suggest that ligand binding induced coordinated movements within the protein structures.

The elastic network models (Figs. 5, S1a, S1b, and S1c) depicted the flexibility of the proteins after ligand binding. These models represent amino acid residues as interconnected nodes and analyze their relative movements. In the AcrB-gamma-tocopherol complex (Fig. 5), the connections between residues were shown as light gray springs, indicating a high degree of flexibility within the protein. This suggests that AcrB can easily deform upon binding gamma-tocopherol.

3.5 FPocketWeb analysis of binding pocket properties

FPocketWeb analysis (Fig. S4 and Table S6) shows significant variation in druggability scores and active pocket properties across the four outer membrane proteins, with AcrB exhibiting the highest druggability score (0.470) and LPS assembly protein having the largest pocket volume (4182.982 Å3) and surface area.

Figure S3

Figure S4

Table S6

4. Discussion

Infectious diseases of highly resistant Gram-negative bacteria lead to multiple health problems worldwide. Concerted efforts are required to eliminate these infections, such as developing effective therapies, increasing the efficiency of current therapies, implementing effective antibiotic stewardship programs, and applying the necessary regulations to combat bacterial infections and prevent their spread (Bassetti and Garau, 2021). Among highly resistant Gram-negative bacteria is E. coli, which we targeted in this study due to it has many antibiotic-resistance mechanisms, such as drug efflux pumps, virulence factors like hemolysis and biofilm formation to promote survival (Majumder et al., 2021). Our previous work explored fenugreek antibacterial and biofilm inhibition against MDR bacteria (Alenazy, 2023). Here, we complement our previous research for identifying potential E. coli EPIs; besides, it could offer a novel strategy for E. coli infection control and other highly resistant Gram-negative bacteria species.

Drug efflux pumps are considered the main antibiotic resistance mechanism in E. coli, and utilizing natural compounds as inhibitors to disrupt the actions of these pumps is considered a promising approach to combat these pathogens. Prior research has shown synergy between certain phytochemicals and antibiotics against NorA efflux pump-expressing Staphylococcus aureus, a Gram-positive bacterium (Stermitz et al., 2001; Stermitz et al., 2000). Continued research on understanding the mechanisms of efflux pumps for Gram-negative pathogens and the outer membrane permeability is crucial. Overcoming the combined effect of the outer membrane barrier and efflux pump activity makes discovering effective EPIs particularly challenging, embedded in their outer membrane.

EPIs that could directly target the action of drug efflux pumps are considered an effective approach, leading to an increase in the accumulation of antimicrobials required to eliminate bacteria, contributing to the reversal of multidrug resistance in many highly resistant pathogenic bacteria. Moreover, EPIs could lead to the non-emergence or development of new highly antibiotic-resistant microbial strains in clinically relevant pathogenic bacteria and also contribute to enhancing the activity and effectiveness of currently used antibiotics. This research explores a promising strategy of EPIs to combat antibiotic resistance in E. coli. Nine compounds previously identified from our work on fenugreeks were selected for in silico evaluation of their EPI potential in E. coli. Studies by Aparna et al. suggest that EPI can enhance intracellular drug accumulation, thereby lowering the minimal inhibitory concentration needed to eliminate resistant bacteria (Aparna et al., 2014). The AcrB efflux pump’s binding sites exhibit a unique combination of hydrophobicity and a large surface area (Nikaido and Pagès, 2012), characteristics that make it easier for structurally different substrates and possible inhibitors to fit together. Abul et al. employed molecular docking to screen 19 phyto-compounds for their potential to inhibit the AcrB efflux pump in E. coli. (Samreen et al., 2022). Our in silico investigated AcrB has the highest druggability score of all the proteins we looked at, which is interesting because it shows that it could be a good target for making EPIs. Furthermore, we revealed a promising EPI potential within key fenugreeks derivatives. These compounds demonstrated the ability to inhibit efflux pumps in antibiotic-resistant bacteria. In silico docking, the analysis predicted favorable binding energy and interactions between gamma-tocopherol and key amino acid residues (LEU137, LEU293, ALA39, ALA299, SER135, ILE38, and MET862) within the E. coli efflux pump. These interactions included alkyl and pi-sigma bonds. In our docking analysis, γ-tocopherol was accommodated within a predominantly hydrophobic pocket of AcrB, where stabilization was mediated largely by aliphatic residues (ALA, LEU, VAL, ILE, PRO) with additional contributions from polar contacts (SER, THR, GLN). This contrasts with the crystal structures reported by Edward et al. (Yu et al., 2005), who demonstrated that diverse substrates, including ethidium and ciprofloxacin, preferentially interact within the periplasmic binding depression formed by the C-terminal loop, engaging key residues such as PHE664, PHE666, GLU673, and ASN109. These aromatic and polar residues were shown to be critical for ligand specificity and efflux activity, as their substitution significantly reduced minimum inhibitory concentration (MIC) values. The difference in residue profiles suggests that γ-tocopherol may occupy a more hydrophobic cavity distinct from the periplasmic depression, reflecting either an alternative binding mode or a non-specific accommodation site within AcrB’s large substrate-binding pocket. Taken together, our findings complement the structural insights of Edward et al., highlighting the adaptability of AcrB in recognizing chemically diverse ligands through multiple binding regions.

LPS is one of the main components of the bacterial outer membrane. (Villa et al., 2013). It is located on the outer leaflet, playing a main role in protecting bacteria from entering harmful compounds such as antibiotics (Ruiz et al., 2006). LPS is essential for bacterial growth. Inhibiting LPS activity using natural plant compounds presents a potential strategy for developing new antibiotics against multidrug-resistant Gram-negative bacteria. By targeting LptD, which is a protein from LPS, its function is to assemble OM proteins and contribute to bacterial growth in E. coli, we could achieve the benefits of increased membrane permeability for improved antibiotic efficacy. The LptDE complex, involving membrane protein LptD and the LptE, plays an important role in LPS transport (final stage). It acts as a gate, allowing the passage of LPS molecules from the inner pathway to the outer leaflet of the outer membrane. Within the LptD protein’s structure, LptE functions as a plug that fits inside the barrel (Qiao et al., 2014; Dong et al., 2012). In E. coli, LptD is one of eight proteins crucial for the proper assembly of LPS following biosynthesis (Okuda et al., 2016). Svanberg et al. recently identified LptD protein as a potential target for novel antimicrobial drugs specifically effective against E. coli and Klebsiella pneumonia (Svanberg et al., 2021). Our docking results complement the findings of (Collet et al., 2020), who modeled the LptD-LptE complex using the 4RHB structure and highlighted critical disulfide-linked residues (CYS31, CYS173, CYS724, CYS725) essential for folding. In our study, γ-tocopherol showed stable binding within the β-barrel cavity, forming interactions with residues such as ASP101, TYR54, and SER55, which lie in proximity to the structurally important regions reported by Jean-François et al. The overlap between these functional domains and our predicted binding pocket supports the relevance of γ-tocopherol as a potential LptD-targeting ligand. Gamma tocopherol could decrease the Lpt protein and LPS levels in E. coli. However, further in vitro and in vivo studies are necessary to elucidate the precise mechanisms of action.

Damaging the OM of bacteria presents a promising strategy to combat antibiotic resistance (MacNair and Brown, 2020). The BAM is a crucial system in Gram-negative bacteria that facilitates the proper integration of β-barrel proteins into the outer membrane. To explore the significance of efflux pumps beyond the well-characterized AcrAB-TolC system, we targeted BamD, a protein crucial for assembling OM proteins and bacterial growth. A previous study by Ambastha et al. revealed that the extracts from Butea monosperma have shown promise against a variety of Gram-positive and Gram-negative bacteria, including E. coli (Surabhi et al., 2023). This study suggests potential antimicrobial, anti-cancer, and antioxidant properties due to the presence of high levels of hexadecanoic acid and gamma-tocopherol. Here, we found that all small molecules derived from T. foenumgraecum bind and could disrupt the bacterial cell wall assembly pathways BAM and the Lpt system could offer a two-pronged attack against infections. Given its previously established anti-cancerous, anti-tumor, antioxidant, cardioprotective, and hypocholesterolemic properties (Gysin et al., 2002; Boussaada et al., 2007). The antimicrobial activity of gamma-tocopherol observed in this study aligns with its broad biological effects. These compounds might not only kill bacteria directly but also sensitize them to antibiotics, making existing treatments more effective.

Vitamin E is a tocochromanols molecule. Tocochromanols consist mainly of four types (α, β, γ, and δ) of both tocopherols and tocotrienols (Górna´s et al., 2014). The safety of tocopherols has been well known, with long-standing research indicating no adverse health effects (Gysin et al., 2002; Boussaada et al., 2007). Gamma-tocopherol (E 308) exhibits significant biological activity among tocopherols. This is attributed to its antioxidant capabilities, which effectively reduce the rate of lipid peroxidation (Scientific Opinion, 2015). Gamma-tocopherol might possess additional benefits beyond its free radical scavenging properties; what is more, it might act as a unique antibacterial agent by targeting BamD in bacteria.

Lipinski’s Rule (Ro5) is widely used in drug discovery (Tomassi and Silano, 1981). The identified components from fenugreek were evaluated for drug-likeness using Ro5 and ADMET analysis, respectively. Gamma-tocopherol demonstrated favorable drug-likeness based on Ro5 criteria, with molecular weight, hydrogen bond donors, and rotatable bonds within the ranges. ADMET analysis predicted low toxicity for the identified phytochemical constituents of fenugreek. Conversely, these components satisfied the criteria for drug-likeness based on in silico prediction through the PROTOX II server. The combined analysis of drug-likeness, ADMET properties, and predicted toxicity for these EPI candidates from fenugreeks paves the way for the development of safe and effective formulations combining phytochemicals with antibiotics.

The NMA results indicated gamma tocopherol forming a stable interaction with the target proteins. The interaction between AcrB and gamma-tocopherol could be particularly steady with minimal internal motion, exhibit flexibility, and it might be necessary for ligand binding and protein function. Our in silico analyses suggest gamma-tocopherol’s potential as a dual inhibitor of efflux pumps and LPS transport.

This study highlights the potential of fenugreeks and it is derived compounds as EPIs. This study is based on in silico simulations, and further in vitro and in vivo studies are warranted. Importantly, this study shows for the first time an investigation of gamma-tocopherol’s activity against efflux pumps in E. coli. Given the increasing incidence of drug-resistant E. coli, combination therapy of antibiotics with these phytochemicals presents a promising strategy to combat MDR.

5. Conclusions

Multidrug efflux pump AcrAB-TolC from E. coli is an ideal representative of many drug efflux pumps in Gram-negative bacteria species due to their high similarity in functional and chemical structures and the abundance of their data, for this reason, it has been chosen to be studied deeply for getting a clear understanding of MDR in Gram-negative bacteria and attempting to find suitable ways to be utilized in disrupting the functions of these pumps. This tripartite complex AcrAB-TolC contains AcrB, an inner membrane pump; TolC, an outer membrane channel; and the periplasmic adaptor protein AcrA linking the two. AcrB and TolC play a main role in multidrug resistance, giving them a higher importance in this research to target their inhibition. Inhibition of one of the subunits of the AcrAB-TolC complex leads to inhibition of the entire complex function. Moreover, AcrB possesses a hydrophobic trap playing a crucial role in the conformational change mechanism of AcrB; also, it contains the amino acid PHE178, which is the main player in binding inhibitors. In this study, we recommend that future work on potential inhibitors should be paid attention to directly targeting the hydrophobic trap by tight binding the inhibitors to the amino acid PHE178. Generally, Gram-negative bacteria contain an outer membrane composed of LPS, which is essential for the survival of bacteria in the presence of life-threatening environments. Targeting LPS with suitable inhibitors that inhibit its growth is considered a promising project to eliminate the problem of multidrug resistance in many Gram-negative bacteria species. The study also recommends that future studies should focus on the length of potential inhibitors and have suitable chemical elongation to bind effectively to the targeted binding sites, either on pumps or LPS. Moreover, the potential inhibitors should have a specific mechanism of action, targeting drug efflux pumps and LPS directly, having suitable solubility inside the bacterial cell without causing undesirable side effects such as disruption of the bacterial membranes or toxic effects on mammalian cells. Moreover, these inhibitors should be broad-spectrum, not only on E. coli but also on a variety of Gram-negative bacteria species. Interestingly, this study discovered promising natural inhibitors (EPI candidates) from Fenugreek seeds. These natural ‘‘fighters’’ might work by blocking pumps that eliminate antibiotics in resistant bacteria like E. coli. They might also mess with how the bacteria build their outer membrane and stop a protein they need to grow. Interestingly, Fenugreek is a medicinal plant with fewer side effects, so scientists are excited about exploring these natural options. While computer simulations have their limits, our findings suggest a specific compound in Fenugreek (gamma-tocopherol) might fit into the pumps like competitively binding to the binding pocket, potentially explaining how it blocks them. More wet lab and animal studies are needed to confirm these observations and determine if these fenugreek fighters could become treatments.

Acknowledgment

The author would like to thank the Deanship of Scientific Research at Shaqra University for supporting this work.

CRediT authorship contribution statement

Rawaf Alenazy: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data duration, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Declaration of Generative AI and AI-assisted technologies in the writing process

The authors confirm that there was no use of Artificial Intelligence (AI)-Assisted Technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Supplementary materials

The following supporting information can be downloaded at https://dx.doi.org/10.25259/JKSUS_114_2024.

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