Odhar H. A, Odhar Z. A, Muhi M. R. Screening of Traditional Chinese Medicine Library Against Penicillin-binding Protein 2a for Methicillin-resistant Staphylococcus aureus by Molecular Docking, Dynamics Simulation and In vitro Antimicrobial Activity. Biomed Pharmacol J 2025;18(1).

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Manuscript received on :14-12-2024
Manuscript accepted on :17-02-2025
Published online on: 20-03-2025

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Plagiarism Check: Yes
Reviewed by: Dr. Rajani Vallepu
Second Review by: Dr. Samara Sameer
Final Approval by: Dr. Mariia Shanaida

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Hasanain Abdulhameed Odhar^1*, Zanan Abdulhameed Odhar²and Mustafa Raed Muhi³

¹Department of pharmacy, Al-Zahrawi University College, Karbala, Iraq.

²Department of gynecology, Al Mahmoudiya General Hospital, Baghdad, Iraq.

³Department of general surgery, Al Mahmoudiya General Hospital, Baghdad, Iraq.

Corresponding author E-mail: hodhar3@gmail.com

DOI : https://dx.doi.org/10.13005/bpj/3132

Abstract

The methicillin-resistant Staphylococcus aureus (MRSA) is considered a public health threat that can increase both treatment duration and cost. Currently, the MRSA strain has developed resistance to many penicillins and cephalosporins due to the expression of insensitive penicillin-binding protein 2a (PBP2a). This transpeptidase variant, PBP2a, has a low binding affinity toward the β-lactam ring. As such, the active site of the PBP2a enzyme is now regarded as a potential molecular target for developing new anti-MRSA therapeutics. Many of the available antibiotics were developed from microbial sources but the herbal sources are still to be explored. Therefore, the aim of this in silico study is to virtually screen a library of Traditional Chinese Medicine (TCM) compounds against the active site of PBP2a to identify possible anti-MRSA phytomedicines. For this purpose, both molecular docking and dynamics simulation were employed in this study. Moreover, the agar well diffusion method was used to assess the in vitro antimicrobial activity of final hit compounds against MRSA cultured colonies. The results of the molecular dynamics (MD) study indicate that both sciadopitysin and plantamajoside can maintain a close proximity to the PBP2a active site during 50 nanoseconds simulation. Additionally, the most preferred molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) binding energy was reported to be -24.09 Kcal/ mol for sciadopitysin. While docking study results point to the possible hydrogen bond interaction of sciadopitysin and plantamajoside with Serine 403 active site residue. Further, the agar well diffusion study refers to the fact that both sciadopitysin and plantamajoside are effective in inhibiting the growth of MRSA culture with a measured zone of inhibition: 12.5 ± 0.7 and 9.0 ± 1.4 mm respectively. In conclusion, it is predicted that the phenolic compounds sciadopitysin and plantamajoside from the TCM library are potential inhibitors of the MRSA PBP2a enzyme.

Keywords

Antimicrobial Activity; Docking; Dynamics Simulation; Methicillin-resistant Staphylococcus aureus; Penicillin-binding protein 2a; Phytochemical compounds

Introduction

Staphylococcus aureus (S. aureus) is a gram-positive coccoid bacterium that is found in about 30% of the human population as part of skin and nasal normal flora.^1,2 Clinically, S. aureus has an adverse impact on human health as it can cause a wide spectrum of infective diseases like endocarditis, bacteremia, pneumonia and osteomyelitis.³ Fortunately, these infective diseases were greatly controlled with the advent of penicillin antibiotics. However, the wide use of penicillin antibiotics had subsequently forced some strains of S. aureus to produce penicillinase enzyme. The production of this hydrolytic enzyme enables S. aureus to resist various penicillin antibiotics by targeting β-lactam ring.⁴ Then, methicillin was introduced as a semi-synthetic penicillin antibiotic that resists hydrolysis by penicillinase enzyme and thereby can control infections by these resistant S. aureus strains.⁵ Eventually, the development of resistance against this antibiotic led to the emergence of methicillin-resistant S. aureus (MRSA) strain.⁶

Currently, MRSA is considered a severe threat to public health that can result in both community and hospital-acquired resistant S. aureus infections.⁷ Based on a recent meta-analysis study, the global prevalence of MRSA in elderly care centers was 14.69% but the infection rate is believed to be gradually increasing.^8,9 The treatment of MRSA infection is challenging because this strain is resistant to many penicillin and cephalosporin antibiotics, and even the last resort antibiotics like vancomycin are no longer applicable.¹⁰ As such, MRSA infection is usually associated with longer hospitalization, more treatment costs and higher hospital mortality.¹¹

When considering the molecular mechanism of resistance acquired by MRSA, it has been observed that this stain can evade β-lactam antibiotics inhibitory effect through expression of β-lactam insensitive penicillin-binding protein 2a (PBP2a). The PBP2a is a transpeptidase enzyme encoded by mecA gene, this gene is believed to be acquired from a non-S. aureus source.¹² The penicillin-binding proteins (PBPs), also known as transpeptidases, are enzymes located on bacterial cell membrane. In S. aureus, four types of these transpeptidases were identified and these are: PBP1, PBP2, PBP3 and PBP4. Moreover, MRSA strain can express another variant known as PBP2a. The catalytic role of these PBPs is essential for the integrity of bacterial cell walls by crosslinking the peptide side chains of adjacent glycan strands.^13,14 Thus, the bactericidal effect of β-lactam antibiotics is produced by the irreversible binding of β-lactam ring with the active site in PBPs. As a result, the inactivated PBPs will no longer able to crosslink peptidoglycan in the cell wall leading to bacterial lysis.¹⁵ Unfortunately, the affinity of β-lactam antibiotics towards PBP2a is very low. As a result, MRSA is considered insensitive to the bactericidal effect of many penicillin and cephalosporin antibiotics.¹⁶ It is worth to mention that new broad spectrum cephalosporins were introduced to the clinical application with a significant activity against MRSA. These new cephalosporins, ceftaroline and ceftobiprole, can bind and inhibit PBP2a.^17,18

Despite the introduction of novel antimicrobials, the rate of new antibiotics development is still slower than the speed by which bacterial resistance is emerging to pharmacotherapy. In this regard, most of the available antibiotics were derived and developed from microbial sources but herbal sources have not yet been explored.¹⁹ Therefore, the aim of this in silico study is to virtually screen a library of Traditional Chinese Medicine (TCM) against the active site of PBP2a crystal. For this purpose, both molecular docking and dynamics simulation were implemented in the screening process to identify new phytomedicines capable of inhibiting MRSA. Then, the agar well diffusion method was used to evaluate the antimicrobial activity of final hits against MRSA cultured colonies.

Materials and Methods

Setting up virtual screening outlines

The main stages of this computational project are summarized in Figure 1. In brief, a library of Traditional Chinese Medicine (TCM) was first screened by docking approach against target crystal of MRSA PBP2a. Then, the best ten phytomedicines with least docking energy were subjected to a prediction of the chemical, pharmacokinetics and toxicity characteristics. After that, the selected ten phytomedicines were submitted to molecular dynamics simulation. In this step, both ligand proximity to PBP2a active site and binding energy were reported as a function of simulation duration. Finally, only those hit compounds with best dynamics simulation results were evaluated in vitro for their antimicrobial activity against cultured MRSA.

Figure 1: A schematic representation of main stages of this in silico study.Click here to view Figure

Molecular docking

For this step, the DrugRep server was employed to carry out molecular docking of the TCM library of compounds against MRSA PBP2a enzyme.²⁰ The DrugRep online server harnesses both AutoDock Vina version 1.1.2 and AutoDockTools (ADT) version 1.5.6 to perform docking operations.^21,22 It is also worth noting that the used TCM library contains 2,390 compounds from about 800 traditional Chinese medicines.²⁰ These TCM compounds were screened against only chain A of PBP2a crystal with PDB code 4DKI,¹⁵ UCSF Chimera version 1.18 was used to extract only chain A and remove co-crystalized ligand from target crystal.²³ During the docking process, the following coordinates of the target active site were applied: X = 27, Y = 28 and Z = 81. While the docking grid box size was 20*20*20 Angstrom. After the complete of docking step, only the best ten phytomedicines with least energy of binding were picked for further evaluation. For each docking complex of these ten phytomedicines, the orientation with the least binding energy pose was visualized and assessed by the protein-ligand interaction profiler (PLIP) web tool.²⁴ Additionally, the following web-based servers: Molsoft L.L.C, SwissADME, pkCSM and ProTox 3.0 were used to predict several chemical, pharmacokinetics and toxicological properties for the best ten phytochemical compounds.^25–28

Molecular dynamics (MD) simulation

In this step, the best ten phytochemical compounds were subjected into two consecutive runs of MD simulation for durations of 25 and 50 nanoseconds respectively. For this purpose, YASARA Dynamics version 20.12.24 was used to execute these two runs of MD study.²⁹ During these MD simulations, the ligand proximity to PBP2a active site was estimated as Root Mean Square Deviation (RMSD). In the first MD run, each docking complex with least binding energy pose was subjected to simulation for 25 nanoseconds. Then, only these phytomedicine-PBP2a complexes with mean ligand proximity RMSD value of no more than 4 Angstrom were submitted to the second MD run. Throughout the second MD simulation of 50 nanoseconds, the cutoff value of no more than 4 Angstrom for mean ligand proximity RMSD was used again to choose the final hit compounds. Additionally, in the second MD simulation, average Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) binding energy was computed by employing AMBER14 force field.³⁰ The detailed procedure and options employed to execute these two MD simulations are the same as what we have applied in previously published in silico studies.^31–33 Briefly, NaCl was used during this simulation with a concentration of 0.9% and an extra amount of either sodium or chloride ions was applied to ensure the neutralization of phytomedicine-PBP2a complex. Also, the hydrogen bonding network was optimized to increase solute stability. Then, pKa anticipation was applied to fine-tune the protonation state of protein residues at physiological pH of 7.4. For this MD study, AMBER14 forcefield was used for the solute while AM1BCC and GAFF2 forcefields were applied for the ligand. Moreover, water molecules were subjected to TIP3P forcefield.^30,34,35

In vitro antimicrobial activity

Only those hits, with the best MD simulation results, were then subjected to the in vitro assessment of their antimicrobial activity against cultured MRSA. In this step, the agar well diffusion approach was used to evaluate the in vitro anti-MRSA activity for the final hits.³⁶ For this purpose, a standard strain of MRSA (ATCC 33591) was cultivated first in Mueller-Hinton II broth (Sigma-Aldrich, India) and incubated overnight at a temperature of 37 °C. After that, the turbidity of the growth was set to 0.5 McFarland standard. Then, 100 µL of the MRSA growth was transferred and spread into a 150 mm Petri dish filled with Mueller-Hinton II agar (Sigma-Aldrich, India). By using a metal cork-borer, five wells of 6 mm diameter were made in the agar.

A 0.5 mg/ mL solution of each selected hit compound was prepared by using dimethyl sulfoxide (DMSO) solvent. These selected compounds were purchased from MedChemExpress web store. Then, 100 µL of each prepared solution was filled into one of the wells and incubated overnight at 37 °C. For this test, the solvent DMSO was employed as a negative control and this test was repeated as a duplicate.

Results

In Table 1, the top ten hits are listed for the structure-based virtual screening of TCM library against MRSA PBP2a monomer. These best hits, in Table 1, are ranked based on their least energy of binding to PBP2a chain A. As seen in this table, the natural sources and pharmacological effects for each hit compound are enlisted.

Table 1: A list for natural sources and pharmacological activities of the top hit compounds in this in silico screening study. These hits were ranked based on their minimum docking energy to enzyme crystal.

Then, various chemical characteristics were predicted for these ten phytomedicines. The predicted chemical properties for these ten compounds along with their docking energy are presented in Table 2. As can be noted from the chemical formula in Table 2, the two phytomedicines, daurisoline and isoliensinine, are alkaloids while other compounds are polyphenolic with no nitrogen-based structure. Moreover, the only hit compound that comply with Lipinski’s rule of five is silydianin. However, the anticipated polar surface area (PSA) for silydianin is still greater than 140 squared Angstrom.

Table 2: Chemical features for the best ten compounds generated by in silico screening of traditional Chinese medicine (TCM) library against chain A of penicillin-binding protein 2a (PBP2a). These hits were arranged based on their least docking energy to the transpeptidase crystal.

M.W.: molecular weight; HBD: hydrogen bond donor; HBA: hydrogen bond acceptor; Log P: logarithm of partition coefficient; TPSA: topological polar surface area; Å: angstrom.

After that, several pharmacokinetics and toxicological features were anticipated for these top phytomedicines. These predicted features are presented along with drug-likeness score for each compound in Table 3. According to Table 3, all these compounds have good drug-likeness score except sciadopitysin, mirificin, plantamajoside. Also, all the listed hits have good or moderate water solubility with the exception of daurisoline, sciadopitysin and isoliensinine. As such, these three compounds with poor water solubility are also predicted to have high intestinal absorption but low volume of distribution. Finally, the only hit that may have a mutagenic potential in Table 3 is the alkaloid daurisoline according to AMES toxicity; while the lowest median lethal dose (LD₅₀) was reported for mirificin and lithospermic acid. Consequently, these three hit compounds: daurisoline, mirificin and lithospermic acid are expected to be unsafe.

Table 3: A summary of drug-likeness score, pharmacokinetics, and toxicity characteristics for the top hit compounds. These hit compounds were listed according to their least docking energy to the PBP2a crystal.

VDss: steady state volume of distribution; LD₅₀: median lethal dose.

The results of MD simulation study are shown in Table 4 for the top ten compounds. These tabulated results are reported for the two runs of 25 and 50 nanoseconds intervals. When considering the ligand proximity to PBP2a active site, only four phytomedicines were able to record mean ligand movement RMSD value of less than 4 Angstrom during 25 nanoseconds interval. These four phytomedicines with low mean ligand movement RMSD are: sciadopitysin, mirificin, plantamajoside, lithospermic acid. Then, only these four compounds were subjected to the second MD run of 50 nanoseconds. During this extended simulation run, only three compounds were able to maintain mean ligand movement RMSD value that didn’t exceed 4 Angstrom. These three compounds are: sciadopitysin, plantamajoside and lithospermic acid as seen in Table 4. Interestingly, the best average MM-PBSA binding energy was computed for the compound sciadopitysin of -24.09 Kcal/ mol during 50 nanoseconds interval.

Table 4: A tabular summary for molecular dynamics (MD) simulation results of the top ten compounds.

MD: Molecular dynamics; RMSD: Root mean square deviation; Å: Angstrom; MM-PBSA: Molecular mechanics-Poisson Boltzmann surface area.

A detailed plot can be seen in Figure 2 for the ligand movement RMSD as a function of 50 nanoseconds simulation duration. It is very clear from this plot that both sciadopitysin and plantamajoside were able to record a close proximity to PBP2a active site during simulation, as compared to the other two compounds. Also, it is evident from the plot in Figure 2 that only plantamajoside was able to keep a ligand movement RMSD that did never exceed 4 Angstrom value.

Figure 2: A detailed plot of ligand movement RMSD versus MD simulation interval. Click here to view Figure

A close view for the binding orientation and possible interactions for both sciadopitysin and plantamajoside with PBP2a active site can be seen in Figure 3 for the docking complexes. The careful evaluation of docking images can be helpful in explaining any difference in the in silico and in vitro activities of sciadopitysin and plantamajoside against PBP2a.

Figure 3: An illustration for the binding orientation and potential interactions for both sciadopitysin and plantamajoside with PBP2a active site.Click here to view Figure

Finally, the in vitro anti-MRSA activity evaluation showed that both sciadopitysin and plantamajoside were effective during the agar well diffusion testing as presented in Figure 4. In this in vitro analysis, the measured zone of inhibition diameter was higher for sciadopitysin (12.5 ± 0.7 mm) as compared to plantamajoside (9.0 ± 1.4 mm).

Figure 4: Agar well diffusion assessment for sciadopitysin and plantamajoside against cultured MRSA. Click here to view Figure

Discussion

The wide and incorrect use of antibiotics like penicillin compounds is driving the development of bacterial resistance to these drugs. Of these resistant strains, MRSA is considered a real public health threat that can increase both the length and cost of infection treatment.¹¹ Despite this health threat, the speed of developing new and effective antibiotics is still behind the rate of bacterial resistance emergence.¹⁹ The mechanism behind MRSA resistance appears to be related to the bacterial expression of a membrane protein called PBP2a that has a low affinity to β-lactam antibiotics.¹² Consequently, the active site of the PBP2a enzyme represents a valuable molecular target towards the development of novel antibiotics against MRSA strain. Therefore, it was of our interest to computationally screen a library of herbal compounds against PBP2a monomer to identify potential inhibitors. Then, these identified hits were evaluated in vitro for their antimicrobial activity against MRSA.

When considering the pharmacological activities of the top hit compounds in Table 1 of the screening results, it is easy to note that many of the hit compounds have antioxidant, anti-inflammatory and anticancer effects. Also, it is expected that all the listed phytomedicines in Table 2 do have poor oral bioavailability due to the violation of the predicted chemical characteristics to Lipinski’s rule of five and/ or Veber’s rule.^52,53 Moreover, the predicted features in both Table 2 and Table 3 point to the fact that these top hits are hydrophilic with the exception of daurisoline, sciadopitysin and isoliensinine. The hydrophilic nature of these hit compounds can be deduced by the low partition coefficient and high polar surface area as predicted in Table 2. As a result, this predicted hydrophilicity will lead to better water solubility, higher volume of distribution and poor penetration through biological barriers for these hits as seen in Table 3.

It is well-known that low ligand movement RMSD during simulation study usually refer to closer proximity of the ligand to enzyme active site, thus stronger binding can be concluded.⁵⁴ Also, according to YASARA dynamics guideline, the more positive MM-PBSA binding energy points to stronger interaction between ligand and target crystal.²⁹ As such, both sciadopitysin and plantamajoside are expected to be potential inhibitors of PBP2a when considering ligand proximity and binding energy parameters in both Table 4 and Figure 2 throughout simulation interval.

Analysis of docking images in Figure 3 refers to the possibility that the two compounds, sciadopitysin and plantamajoside, occupied different locations within PBP2a active site but both of them were able to interact with the nucleophile Serine 403 residue by a hydrogen bond interaction. As noted from Figure 3, the compound plantamajoside is involved in higher number of hydrogen bond interactions with PBP2a active site residues as compared to sciadopitysin. However, the binding location of sciadopitysin seems to be very similar to the co-crystalized ceftobiprole antibiotic. Also, the compound sciadopitysin is engaged in two hydrogen bond interactions with Serine 403 active site residue as compared to only one interaction in case of plantamajoside. Moreover, the length of these hydrogen bonds between sciadopitysin and Serine 403 active site residue is shorter than that predicted for plantamajoside (2.28 and 2.75 versus 3.27 Angstrom). Thus, despite the fact that plantamajoside can form many hydrogen bond interactions with transpeptidase active site residues but the binding location, orientation and length of the hydrogen bonds in case of sciadopitysin looks to be more favorable.

These in silico findings were then further confirmed in vitro by measuring the zone of inhibition diameter produced by these two phytomedicines against cultured MRSA. Records from agar well-diffusion experiment in Figure 4 points to the fact that the compound sciadopitysin can produce larger zone of inhibition as compared to plantamajoside.   

Conclusion

In this in silico study, the phenolic compounds sciadopitysin and plantamajoside are predicted to be potential inhibitors of penicillin-binding protein 2a (PBP2a). Thus, these two phytomedicines can be used toward the development of new antibiotics against methicillin-resistant Staphylococcus aureus (MRSA). Docking study indicates that the energy of binding to PBP2a active site is -9.1 and -8.2 Kcal/ mol for sciadopitysin and plantamajoside respectively. As compared to sciadopitysin docking complex, the glycoside plantamajoside is involved in a higher number of hydrogen bonds with PBP2a active site residues. However, the flavonoid sciadopitysin is engaged in two hydrogen bonds with Serine 403 active site residue while plantamajoside is involved in only one hydrogen bond with this residue. Also, the length of these two hydrogen bonds formed by sciadopitysin is shorter when compared to plantamajoside. Then, molecular dynamics (MD) simulation points to the fact that these two compounds can maintain a close proximity to PBP2a active site throughout 50 nanoseconds interval. Further, the best MM-PBSA binding energy was calculated for sciadopitysin during simulation analysis. Finally, agar well diffusion study showed that both compounds are effective in inhibiting the growth of MRSA culture and the zone of inhibition was larger for sciadopitysin. However, the physicochemical properties of both sciadopitysin and plantamajoside should be modified to enhance compounds’ drug-likeness score and pharmacokinetics.

Acknowledgment

The authors would like to thanks the department of pharmacy, Al-Zahrawi University College for their support of this work.

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of interest

The author(s) do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials

Author Contributions

• Hasanain Abdulhameed Odhar: Conceptualization, Methodology, Data collection, Analysis, Writing – Original Draft.
• Zanan Abdulhameed Odhar: Writing – Review & Editing, Supervision.
• Mustafa Raed Muhi: Writing – Review, Supervision.

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List of Abbreviations

A: Angstrom

LD₅₀: Median lethal dose

MD: Molecular dynamics

MM-PBSA: Molecular mechanics-Poisson Boltzmann surface area

MRSA: Methicillin-resistant Staphylococcus aureus

PBP2a: Penicillin-binding protein 2a

RMSD: Root mean square deviation

TCM: Traditional Chinese Medicine