Computational and experimental investigation of natural antimicrobials targeting Vibrio parahaemolyticus DNA gyrase: In silico and in vitro evaluation

Introduction

Aquaculture has evolved into a multimillion-dollar sector over the years, with shrimp aquaculture driving much of this growth. Shrimp is the most farmed crustacean worldwide, making up 65% of the global production in 2020, according to the FAO (2022) [6] . As a rich source of nutrients, seafood offers various health benefits (Iwamoto et al., 2010) [10] . However, the improper use of antibiotics in shrimp farming has led to the rise of antimicrobial resistance (AMR) among both harmful and beneficial bacteria (Prestinaci et al., 2015) [18] . Significant pathogens in shrimp aquaculture include various Vibrio species such as V. alginolyticus, V. anguillarum, V. parahaemolyticus, V. harveyi, and V.vulnificus, which cause severe economic losses (Karunasagar et al., 1994) [11] . V. parahaemolyticus, in particular, is known for causing the most frequent disease outbreaks, underlining the need for careful pond management. The frequency of disease outbreaks in shrimp aquaculture associated with V. parahaemolyticus is more than any other bacterial pathogen and serious attention is invested in pond management to avoid such outbreaks. The current management practices are mainly based on the application of probiotics and antibiotics. The use of antimicrobial compounds is highly unregulated in aquaculture and invites serious problems in the form of the development of antimicrobial resistance in pathogenic as well as non-pathogenic bacteria. Such a situation also favors the spread of the AMR gene between the bacterial species through horizontal gene transfer and leads to the widespread prevalence of AMR. Aquaculture sediments include a diverse range of active bacterial communities, and there is evidence to suggest that they may be a significant source of infections and antibiotic resistance. In order to facilitate the transmission of AMR genes, sediment systems constitute a crucial environmental matrix. The growing resistance to existing antibiotics is pushing researchers to explore new antimicrobial agents. Computational methods have become prominent in the drug discovery process using artificial intelligence Computer-Aided Drug Design (CADD). This approach involves various computational techniques such as molecular modeling and rational drug design, which streamline and accelerate the drug development process, making it faster, cheaper, and more efficient (Yu and MacKerell, 2016) [22] . Molecular docking is used to find ligands/compounds that bind strongly to target proteins, such as DNA gyrase as well as essential proteins required for their life cycle. DNA gyrase is an essential enzyme present in prokaryotes but absent in eukaryotes, making it an ideal drug target. DNA gyrase plays a critical role in DNA topology during recombination, transcription, and replication by creating temporary breaks in DNA strands (Durcik et al., 2018) [5] . Many inhibitors of DNA gyrase, including quinolones and aminocoumarins, have been thoroughly investigated (Maxwell, 1997) [17] . Addressing the pressing need for new drugs to fight these pathogens to overcome the spread of AMR is vital. Drug discovery and development are intricate processes, but using computational drug design can quickly identify potential drug molecules against pathogenic Vibrios, offering a swift solution for disease management in aquaculture (Malathi et al., 2018) [16] . Recent findings also underscore the necessity for new treatments and preventive measures for pathogenic V. parahaemolyticus strains.

Materials and methods

Target selection

The choice to focus on DNA gyrase as a drug target as it is an important enzyme in the life cycle of V. parahaemolyticus. The 3D structure of this protein was retrieved from AlphaFold database (Varadi et al., 2021), identified by the AlphaFold ID: A0A656SKS8_VIBPH. This protein was selected due to its critical importance to the organism's survival and its frequent mention in reports on antibacterial drug screenings.

Preparation of ligand library

Ligands were retrieved from the ZINC database 15 (Sterling and Irwin, 2015) [20] and the PubChem database (Kim et al., 2022) [12] . A total of 800 ligands were curated for use in the molecular docking experiments.

Physicochemical characterization of the selected target protein:

The physicochemical properties of the target protein were analyzed using the ExPASy ProtParam tool. This analysis included parameters such as amino acid composition, molecular weight, extinction coefficient, theoretical isoelectric point (pI), instability index, grand average of hydropathicity (GRAVY), aliphatic index, and the total count of positively and negatively charged residues (Gasteiger et al., 2003) [7] .

Validation of the protein 3d structure

The 3D structure's quality was validated using the SAVES server, employing tools like VERIFY 3D (Bowie et al., 1991; Lüthy et al., 1992) [2,15] , PROCHECK (Laskowski et al., 1993) [14] , and ERRAT (Colovos and Yeates, 1993) [4] . The protein structure was analyzed in.pdb format.

Protein preparation

The protein was prepared for molecular docking using BIOVIA Discovery Studio 2021. This preparation involved removing side chains and heteroatoms, adding hydrogen molecules, and converting the structure into the required PDB format. The analysis of the N-terminal and C-terminal ends was performed using Chimera v1.17.3 software.

Molecular docking of protein-ligand

Molecular docking was executed using PyRx 0.8 software (2016) and AutoDock Vina 1.5.7. This involved converting the protein molecule from PDB to PDBQT format and minimizing the energy of the ligand molecules. Ligands were then shortlisted based on their binding affinity, local availability, and cost-effectiveness.

Physicochemical properties and toxicity analysis

The shortlisted compounds underwent an in-depth analysis of their physicochemical properties and potential toxicity using the pkCSM platform (Douglas et al., 2015). This step was essential to assess the compounds' safety and identify any toxicological risks.

Visualization of protein-ligand interaction

The interactions between the protein and the selected ligand were visualized using BIOVIA Discovery Studio 2021. This visualization helped to elucidate how the compound binds at the molecular level, offering insights into its potential therapeutic efficacy.

Molecular dynamic simulation

Following the molecular docking results, a molecular dynamics simulation was conducted to evaluate the stability of the protein/ligand complex. Techniques such as vibrational analysis and motion animations were utilized interactively using iMODS, which facilitated an enhanced understanding of domain dynamics and the effects of ligand binding on DNA gyrase from V. parahaemolyticus (Kovacs et al., 2004; López-Blanco et al., 2011). This simulation helped in verifying the compound's efficacy by analyzing several parameters, including deformability, B-factor, and eigenvalue.

Ethanolic extraction of compound present in selected natural sources for in vitro testing

The locally available natural compounds were collected for further extract preparation. The leaves were washed properly using distilled water and dried at room temperature. Fine powders were made using a grinder. A weight of 10 gm of powder was measured. A clean bottle was taken and 100 ml of ethanol and the powder were added. It was mixed properly and placed on a rocker for 96 hours. The extract was filtered using a muslin cloth. The supernatant was collected from the filtrate after centrifugation at 3500 rpm for 5 minutes. The supernatant was further filtered using Whatman filter paper no. 1 and placed in a vacuum desiccator for drying. The dry matter was weighed and dissolved in 10% DMSO and further diluted in the same solvent for preparation of the required concentration for antibacterial efficacy. This solution was centrifuged at 3500 rpm for 5 minutes to remove any undissolved particles and the supernatant was filter sterilized using a syringe filter (0.2 micron) for further analysis.

In vitro antibacterial assay against MDR Vibrio parahaemolyticus:

The colonies that were resistant to 6-7 antibiotics were selected. The colony was inoculated in Mueller Hinton broth and incubated at 30°C for 5-6 hours. In a 0.5 ml sterile tube, 150 µl culture and 150 µl of the compound of specific concentration were added. The tubes were incubated at room temperature for 2-3 hours and postincubation 100 µl culture was spread on TCBS plates using a sterile spreader. The plates were incubated at 30°C for 18-20 hours and CFU was counted for further analysis.

Result Physicochemical characterization of the target protein

Extensive physicochemical characterization is commonly employed to identify the specific surface areas responsible for exceptional catalytic activity. The 3D structure of the DNA gyrase from V. parahaemolyticus was retrieved using AlphaFold, with the specific AlphaFold ID: A0A656SKS8_VIBPH. This structure was analyzed to determine its physicochemical properties. The instability index of the protein is 31.86, indicating stability according to Guruprasad et al. (1990) [8] . Additional physicochemical parameters are detailed in Table 1.

Quality analysis of target protein 3d structure for molecular docking: DNA gyrase of V. parahaemolyticus used as a potential drug target for the identification of putative ligands using molecular docking its ribbon structure and indication of C and N terminal in figure 1. The 3D structure of DNA gyrase proteins was analyzed using a Ramachandran plot analysis shown in figure 2. The percentage of residue in the favored region was more than 95% in the protein structures showing the quality of the 3D structure of protein shown in table 2.

Validation of protein 3D structure

Quality analysis of protein 3D structure using SAVES 6.0 server. VERIFY 3D and ERRAT used for quality analysis of DNA gyrase protein shown in figure 3 andfigure 4.

Prediction of active site in protein

CASTp 3.0 used for the prediction of active site, a total of 18 pockets were generated. Among these, pocket ID 1 stood out with an area (SA) measuring 12541.475 and a volume (SA) of 7423.537. Consequently, it was chosen as the primary active site for subsequent docking analysis.

Molecular docking and identification of alternative antimicrobial against V. parahaemolyticus: Molecular docking results demonstrate the binding of the compounds

to DNA gyrase B as shown in Table 3. These findings provide valuable insights into the molecular mechanisms underlying the strong binding affinity between DNA gyrase B and its selectivity in terms of antibacterial drug efficacy. The molecular docking of 800 ligand molecules of different category including the natural origin were performed against DNA gyrase of V. parahaemolyticus. The ligands were shortlisted based on the binding strength and local availability of compounds. The docked image of target and shortlisted ligand visualized in Biovia Discovery studio as shown in figure 5 to figure 14.

ADMET analysis of shortlisted compounds

ADMET analysis is crucial for evaluating the pharmacokinetics of a drug, encompassing Absorption, Distribution, Metabolism, Excretion, and Toxicity. This analysis examines the potential side effects of a drug within the body, focusing on its oral bioavailability and absorption rate in the gastrointestinal tract. These evaluations are crucial aspects of drug discovery. Inadequate absorption can negatively impact the drug's distribution and metabolism, potentially resulting in complications such as neurotoxicity and nephrotoxicity (Flores-Holguín et al., 2021). The shortlisted ligands were used for ADMET analysis as shown in the table 4.

Molecular dynamic simulation

The iMODS server was utilized to analyze the molecular interactions of V. parahaemolyticus DNA gyrase with querciturone and aloesin. The complexes of DNA gyrase with querciturone and aloesin were evaluated through Normal Mode Analysis (NMA) to simulate and assess the internal coordinates of the system's complexity. The trajectory analysis helped determine the system's deformability, with results depicted in Figures 15 and16, illustrating the molecular dynamics simulations of the ligand-target interactions. The trajectory analysis of these complexes showed minimal deformation within a range of 0 to 1 Å, indicating stable binding with low deformation (Figures 15a and16a). The network plot within the figures uses each dot to represent a spring, color-coded based on the stiffness relative to the atomic pairs, with grey-colored spring models indicating the compactness and stability of the binding complex system (Figures 15c and16c). Figures 15d and16d display the integration of the complexes, where the model's elastic network analysis identifies pairs of atomic coordinates through distance-based spring analysis. NMR traces detected some atomic fluctuations in the system trajectory of the DNA gyrase interactions with querciturone and aloesin. Figures 15f and16f present the computed eigen scores of 9.693x10 -6 and 9.694x10 -6 , respectively. Furthermore, covariance matrix analysis of the DNA gyrasequerciturone and DNA gyrase-aloesin atomic pairs highlighted the correlated segments in red, non-correlated in blue, and uncorrelated segments in white. These findings underscore the stable binding and complex rigidity of DNA gyrase, accompanied by a low deformation index and some atomic fluctuations, contributing to our understanding of the interaction dynamics within these complexes. Additionally, iMOD server was used to explore the docked complex physical movement and stability through Normal mode analysis (figure 15 and16) incorporating deformability and B-factor. The deformability and B-factors of the DNA gyrase-Querciturone and DNA gyrase-aloesin complexes showed the peaks matching to deformable sites in the proteins, with the largest peaks representing high deformability regions. The B-factor plots provide a comparison of the complexes' NMA and PDB fields. The eigenvalue and variance graphs (individual variance through purple shade and cumulative variance by green colour) of DNA gyrase-Querciturone and DNA gyrase-aloesin complexes, respectively. Whereas the eigenvalue and variance graphs of DNA gyrase-Querciturone (9.693069e-06) and DNA gyrase-aloesin (9.694764e-06) complexess are provided in figure 15F and 16F respectively. The covariance matrix of DNA gyrase-Querciturone and DNA gyrasealoesin complex shows the relationships between residues (red colour indicates good correlation while white colour represents uncorrelated motion and blue shade represents anticorrelations). The docked complex elastic maps show the relationships between the atoms, with darker-gray regions represent stiffer regions.

In vitro antibacterial assay of shortlisted compounds

The natural source of shortlisted ligands were procured and extract were prepared for the antibacterial efficacy study against the multidrug-resistant V. parahaemolyticus. The final list of selected chemicals/extracts is presented in Table 5.

The ethanolic extracts were prepared as per the protocol explained in materials and methods and all the shortlisted chemicals/extracts were analyzed using agar well assay and TPC count post-treatment with the formulations at particular concentrations.

Discussion

Computer-Aided Drug Design (CADD) is instrumental in identifying and developing new drug candidates. DNA gyrase, critical in regulating DNA's three-dimensional structure during key cellular processes like transcription, replication, and recombination, facilitates these processes by introducing temporary breaks in both strands of the DNA molecule. During replication, it introduces negative supercoils into the DNA, managing its topology and alleviating torsional stress that accumulates during these complex processes. Acting as a molecular architect, DNA gyrase shapes the DNA molecule to support essential cellular functions while maintaining its structural integrity. Molecular docking techniques, used to explore interactions with various ligands, provide insights into potential drugs that could modulate its activity. This research enhances our understanding of fundamental cellular processes and opens avenues for therapeutic interventions. Given its indispensable role in prokaryotes and absence in eukaryotes, DNA gyrase is an appealing drug development target. Several studies highlight the significance of DNA gyrase as a drug target. Collin et al. (2011) [3] underscored the urgent need for new medications due to rising drug resistance, utilizing DNA gyrase as a promising target. Salve et al. (2021) synthesized analogs of 3-((7-chloroquinolin-4yl)amino) thiazolidin-4-one to inhibit Mycobacterium tuberculosis DNA gyrase, evaluating them through in vitro methods and molecular docking with Mycobacterium smegmatis GyrB, demonstrating significant inhibitory effects. Kumar et al. (2022) [13] [23] compared the efficacy of isolated compounds to ciprofloxacin in inhibiting E. coli DNA gyrase B, demonstrating strong binding affinities. Herbal-based formulations are promising alternatives to conventional antibiotics, addressing antimicrobial resistance effectively. Compounds like quercetin, recognized for their anti-inflammatory, antioxidant, antibacterial, and anticancer properties, also play roles in inhibiting quorum sensing systems, enhancing food quality and safety (Kim et al., 2022; Hossain et al., 2021) [9,12] . Phenolic compounds from plants disrupt quorum sensing in various bacteria (Quecan et al., 2019) [19] . Babayi et al., 2004 reported that methanolic extract of Eucalyptus leaves are effective against Bacillus subtilis, Candida albicans, Staphylococcus aureus (ATCC & Clinical) at a concentration of 2000µg/ml. We have also reported the inhibitory effect of eucalyptus leaves and aloe vera root ethanolic extract against V. parahaemolyticus at concentration of 11.04% and 2.6% was 0 cfu/ml respectively. Also found ashwagandha powder extract was effective at 5.5% concentration on Vibrio parahaemolyticus was 7x10 3 compared to control TNTC. Conclusions: In this study, we conducted a molecular docking analysis targeting the DNA Gyrase protein. A total of 800 ligands were retrieved from the ZINC and PubChem databases and employed for molecular docking studies, facilitated by PyRx software. This research yielded promising results, identifying numerous compounds sourced from both natural and chemical origins that displayed favorable interactions with the protein target associated with V. parahaemolyticus. Notably, among the selected ligands, several were derived from readily available and costeffective natural sources. Remarkably, compounds such as Curcumin, Secoisolariciresinol diglucoside, Nobiletin, Quercetin, Methyl folate, Honokiol, Piperine, Withanolide A, Aloesin, and Querciturone were found in turmeric, flaxseed, oranges, lotus, sweet chili pepper, star fruit, black pepper, ashwagandha, aloe vera, and eucalyptus shows tremendous binding affinity with DNA gyrase protein in V. parahaemolyticus. These compounds demonstrated robust binding affinities toward the DNA Gyrase protein. To gain a more profound understanding of these extracts and potentially isolate specific bioactive compounds, further comprehensive analyses will be indispensable. This in-depth exploration holds the potential to unveil novel solutions for addressing the challenges faced in the shrimp farming sector, with the added benefit of reducing reliance on antibiotics while promoting sustainable and cost-effective practices. However, further in vivo studies are needed to confirm that this natural compound displays much better clinical efficiency toward resistant bacteria than existing drugs.

References

1. Abishad P, Niveditha P, Unni V, Vergis J, Kurkure NV, Chaudhari SP, et al. In silico molecular docking and in vitro antimicrobial efficacy of phytochemicals against multi-drug-resistant enteroaggregative Escherichia coli and non-typhoidal Salmonella spp. Gut Pathog. 2021;13(1). DOI:10.1186/s13099-021-00443-3
2. Bowie JU, Lüthy R, Eisenberg D. A method to identify protein sequences that fold into a known threedimensional structure. Science. 1991;253(5016):164170. DOI:10.1126/science.1853201
3. Collin F, Karkare S, Maxwell A. Exploiting bacterial DNA gyrase as a drug target: current state and perspectives. Appl Microbiol Biotechnol. 2011;92(3):479-497. DOI:10.1007/s00253-011-3557-z
4. Colovos C, Yeates T. Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci. 1993;2(9):1511-1519. DOI:10.1002/pro.5560020916
5. Durcik M, Lovison D, Skok Z, Cruz CD, Tammela P, Tomasic T, et al. New N-phenylpyrrolamide DNA gyrase B inhibitors: optimization of efficacy and antibacterial activity. Eur J Med Chem. 2018;154:117132. DOI:10.1016/j.ejmech.2018.05.011
6. FAO. The state of world fisheries and aquaculture 2022: towards blue transformation. Rome: FAO; 2022. DOI:10.4060/cc0461en
7. Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel RD, Bairoch AM. ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003;31(13):3784-3788. DOI:10.1093/nar/gkg563
8. Guruprasad K, Reddy BV, Pandit MW. Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng. 1990;4(2):155-161. DOI:10.1093/protein/4.2.155
9. Hossain I, Kim K, Mizan MFR, Toushik SH, Ashrafudoulla M, Roy PK, et al. Comprehensive molecular, probiotic, and quorum-sensing characterization of anti-listerial lactic acid bacteria, and application as bioprotective in a food (milk) model. J Dairy Sci. 2021;104(6):6516-6534. DOI:10.3168/jds.2020-19034
10. Iwamoto M, Ayers T, Mahon BE, Swerdlow DL. Epidemiology of seafood-associated infections in the United States. Clin Microbiol Rev. 2010;23(2):399-411. DOI:10.1128/cmr.00059-09
11. Karunasagar I, R P, Malathi G. Mass mortality of Penaeus monodon larvae due to antibiotic-resistant Vibrio harveyi infection. Aquaculture. 1994;128(34):203-209. DOI:10.1016/0044-8486(94)90309-3
12. Kim YS, Roy PK, Ashrafudoulla M, Nahar S, Ha S, Hossain I, et al. Antibiofilm effects of quercetin against Salmonella enterica biofilm formation and virulence, stress response, and quorum-sensing gene expression. Food Control. 2022;137:108964. DOI:10.1016/j.foodcont.2022.108964
13. Kumar A, Prasun C, Rathi E, Nair MS, Kini SG. Identification of potential DNA gyrase inhibitors: virtual screening, extra-precision docking and molecular dynamics simulation study. bioRxiv. 2022. DOI:10.1101/2022.11.06.515362
14. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr. 1993;26(2):283-291. DOI:10.1107/s0021889892009944
15. Lüthy R, Bowie JU, Eisenberg D. Assessment of protein models with three-dimensional profiles. Nature. 1992;356(6364):83-85. DOI:10.1038/356083a0
16. Malathi K, Ramaiah S. Bioinformatics approaches for new drug discovery: a review. Biotechnol Genet Eng Rev. 2018;34(2):243-260. DOI:10.1080/02648725.2018.1502984
17. Prestinaci F, Pezzotti P, Pantosti A. Antimicrobial resistance: a global multifaceted phenomenon. Pathog Glob Health. 2015;109(7):309-318. DOI:10.1179/2047773215y.0000000030
18. Quecan BXV, Santos JBD, Rivera MLC, Hassimotto NMA, De Almeida FA, Pinto UM. Effect of quercetin rich onion extracts on bacterial quorum sensing. Front Microbiol. 2019;10. DOI:10.3389/fmicb.2019.00867
19. Sterling T, Irwin JJ. ZINC 15 -ligand discovery for everyone. J Chem Inf Model. 2015;55(11):2324-2337. DOI:10.1021/acs.jcim.5b00559
20. Tomasic T, Masic LP. Prospects for developing new antibacterials targeting bacterial type IIA topoisomerases. Curr Top Med Chem. 2013;14(1):130151. DOI:10.2174/1568026613666131113153251
21. Yu W, MacKerell AD. Computer-aided drug design methods. Methods Mol Biol. 2016;85-106. DOI:10.1007/978-1-4939-6634-9_5
22. Anza M, Garbisu C, Salazar O, Epelde L, Alkorta I, Martínez-Santos M. Acidification alters the functionality of metal polluted soils. Applied Soil Ecology. 2021 Jul 1;163:103920.