Journal of Drug Targeting, 2011; 19(3): 179–188 © 2011 Informa UK, Ltd. ISSN 1061-186X print/ISSN 1029-2330 online DOI: 10.3109/10611861003801867
ORIGINAL ARTICLE
Insights into antifolate activity of phytochemicals against Pseudomonas aeruginosa Premkumar Jayaraman1,2, Kishore R. Sakharkar1,3, Lim Chu Sing1,2, Vincent T.K. Chow4, and Meena K. Sakharkar1,2 1
Biomedical Engineering Research Centre, Nanyang Technological University, Singapore, 2Advanced Design and Modeling Lab, Nanyang Technological University, Singapore, 3OmicsVista, Singapore, and 4Department of Microbiology, National University of Singapore, Singapore
Abstract Pseudomonas aeruginosa is an opportunistic drug resistant pathogen. Drug interaction studies for phytochemicals (protocatechuic acid (PA), gallic acid (GA), quercetin (QUER), and myricetin (MYR)) in combination with antifolates (sulfamethoxazole (SMX) and trimethoprim (TMP)) are presented. Our results show that the combinations of SMX and phytochemicals are synergistic, whereas TMP in combination with phytochemicals results in additive mode of interaction. Molecular docking of phytochemicals in the active site of modeled P. aeruginosa dihydrofolate reductase (DHFR), an important enzyme in the folic acid biosynthesis pathway, shows that the phytochemicals QUER and MYR dock in the active site of P. aeruginosa DHFR with promoted binding at the NADP site, PA, and GA dock in the active site of P. aeruginosa DHFR with promoted binding at the folate binding site. Possible mode of action of these phytochemicals as anti-DHFR compounds in this bacterium is suggested. Taken together, the above findings provide novel insights to mode of interactions of these phytochemicals with antibiotics and may have significance as prospective leads in the development of antipseudomonal drug developments. Keywords: Synergy, molecular modeling, phytochemicals, drug resistance
Introduction
inhibitor (drugs like trimethoprim (TMP) and sulfonamides) out of the cell (Lister et al., 2009). Furthermore, the swarming behavior associated with the biofilm formation by this pathogen accounts for its higher resistance to different families of antimicrobial agents (Lai et al., 2009). Conventionally, cotrimoxazole, a synergistic combination (sulfamethoxazole (SMX) and TMP) is used to treat infections caused by this pathogen (Hill et al., 1985). TMP inhibits dihydrofolate reductase (DHFR) enzyme, which catalyses the NADPH-dependent reduction of dihydrofolate to tetrahydrofolate, an important cofactor involved in supplying one carbon for the synthesis of purines, pyrimidines, methionine, and many other amino acids. On the other hand, SMX (a sulfonamide), competitively inhibit the binding of para aminobenzoic acid to the enzyme dihydropteroate synthase (DHPS) that catalyses the formation of dihydrofolate (Huovinen,
Multidrug resistant and major nosocomial infection causing pathogen Pseudomonas aeruginosa is a major concern for immunocompromised and cystic fibrosis patients. It establishes chronic infection at the lower respiratory tract resulting in increased morbidity and mortality. The infections caused by P. aeruginosa are both invasive and toxigenic (Rubin & Yu, 1988; Stern, 1990; Nicotra et al., 1995; Obritsch et al., 2005; Wang et al., 2005; Kipnis et al., 2006). This bacterium has low susceptibility profile to several antibiotics because of its intrinsic and acquired resistance mechanisms (Hancock, 1997; Strateva & Yordanov, 2009). Although, folic acid biosynthesis inhibitors are used for treatment of infections caused by P. aeruginosa, the multidrug efflux pumps present in the resistant pathogen have the capability to pump folic acid biosynthesis
Address for Correspondence: Meena K. Sakharkar, N3-2C-113B, Nanyang Technological University, Singapore. E-mail:
[email protected]. sg;
[email protected] (Received 06 February 2010; revised 10 March 2010; accepted 16 March 2010)
179
180 Premkumar Jayaraman et al. 2001). Here, it must be mentioned that nearly all prokaryotes must synthesize folate compounds de novo, starting with GTP and utilizing several different enzymes in a multistep pathway, whereas eukaryotes (including human) are able to utilize the dietary folates by uptake through a carrier-mediated transport system (Achari et al., 1997). Hence, DHPS and DHFR are good targets for antifolates (Hawser et al., 2006). Not surprisingly, strains of P. aeruginosa resistant to cotrimoxazole are also reported (Brown & Izundu, 2004; McGowan Jr, 2006; Litzow et al., 2009). Given these challenges, the primary focus of this work is to find novel treatment strategies for infections caused by this drug resistant opportunistic pathogen. Several studies have proposed that natural compounds (phytochemicals) from plants in combination with antibiotics are a new strategy for developing therapies for infections caused by bacterial species and that natural plant products can potentiate the activity of antibiotics when used in combination (Garo et al., 2007; Coutinho et al., 2008; Coutinho et al., 2009). Multiple drug targets, mutual interference, improved solubility, suppression of resistance mechanisms and neutralization are the reported synergistic effects of combination of phytochemical-antibiotic combinations (Hemaiswarya et al., 2008; Ulrich-Merzenich et al., 2009; Wagner & Ulrich-Merzenich, 2009). Here, we investigate the phytochemicals-antibiotic interactions of four phytochemicals (gallic acid (GA), myricetin (MYR), protocatechuic acid (PA), and quercetin (QUER)) in combination with two folic acid biosynthesis inhibitors (antibiotics) (TMP and SMX). Further on, we give some insights on the binding modes of these phytochemicals in the P. aeruginosa DHFR active site by computational methods using molecular docking. The results of our analysis are presented.
Materials and Methods Antimicrobial agents Standard powders of SMX (potency 98%), TMP (potency 98%), PA (potency 98%), GA (potency 98%), QUER (potency 98%), and MYR (potency 96%) were obtained from Sigma-Aldrich, Singapore. Stock solutions of the above drugs were prepared using respective solvents according to Clinical and Laboratory Standards Institute (CLSI) standards and manufacturer’s recommendations and thereafter diluted in Iso-sensitest broth.
Bacterial strain Pseudomonas aeruginosa PA01 strain (University of Geneva, Switzerland) was used for this investigation. Individual colonies were selected from overnight growth plate and suspended in 5 mL of Iso-sensitest broth. Tube was incubated at 35°C for 2–3 h resulting in ~1 × 108 CFU/ mL and the suspension was then diluted to 106 CFU/mL with the Iso-sensitest broth.
Antimicrobial susceptibility test The MICs (Minimal Inhibitory Concentration) of SMX, TMP, PA, GA, QUER, and MYR were determined by the broth microdilution method, according to CLSI guidelines (1992). The microtiter well was placed with serial twofold concentration for all drugs with 100 µL final volume, which ranged from 1 µM–2 mM for western antibiotics to 50 µM–20 mM for phytochemicals. Test strain was inoculated with the bacterial density ~1 × 106 CFU/ mL of log phase inoculum. MIC, defined as the lowest concentration of the drug that limits the visible bacterial growth after 20 h incubation at 35°C was recorded. Checkerboard procedure was followed for the combination assay. Combinations of SMX-PA, SMX-GA, SMX-QUER, SMX-MYR, TMP-PA, TMP-GA, TMP-QUER, and TMP-MYR were evaluated. Western drugs with concentration 4× MIC (four times MIC) were serially diluted in microtiter plates with Iso-sensitest broth from x-axis and phytochemicals with 4× MIC was serially diluted from y-axis. Diluted bacterial test strain was inoculated and the growth was monitored after 20 h of incubation at 35°C. Growth control and sterility control were maintained for all the experiments. Readings were taken in triplicate for all the assays. Synergism by the checkerboard method is defined as a Fractional inhibitory concentration (FIC) index of < 0.5, additivity is defined as a FIC index of > 0.5 and ≤ 4, and antagonism is defined as a FIC index of > 4. The (FIC index) for all the combinations was determined using the following formula: FICindex FIC A FIC B
FIC A
MIC A combination , MIC A alone
FIC B
MIC A combination MIC A alone
where FICA and FICB represent FIC of drug A and B, respectively. MICA, MICB represent minimum inhibitory concentration of drug A (antibiotic) and B (phytochemical), respectively.
Template selection and alignment Protein sequence for the P. aeruginosa DHFR was retrieved from National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov). Homologous sequences of P. aeruginosa DHFR were obtained from NCBI by Basic Local Alignment Search Tool (BLASTP) search against Protein Data Bank (PDB) using P. aeruginosa DHFR as the query sequence. E. coli DHFR (PDB code: 1RA2) was chosen as the template with high sequence similarity (44%) from the homologue blast sequences to model the 3D structure of P. aeruginosa DHFR. The alignment of the P. aeruginosa DHFR protein sequence and template structure E. coli DHFR Journal of Drug Targeting
Phytochemical-antibiotic combinations as folate inhibitors (1RA2) protein sequence was performed using CLUSTAL W2 (http://www.ebi.ac.uk/Tools/clustalw2/index.html).
3D model building The PDB structure for E. coli DHFR (1RA2) (1.60 Å resolution) in complex with folic acid and nicotinamide adenine dinucleotide phosphate was used to generate the 3D model of P. aeruginosa DHFR using Modeller™ 9v7. Modeller™ 9v7 generates 3D model by satisfying spatial restraints (Eswar et al., 2008). Modeller™ aligned the target sequence in ALI format with the template structure 1RA2 and five models were built using the alignment output file in PIR format. From the models generated the one with the highest DOPE score was selected for advanced modeling. The selected model showed loop region conformation problems when aligned with the template structure sequence using Gnuplot. Therefore, the model was subjected to loop refinement and evaluated to identify any decrease or increase in model energy in accordance with the template structure energy and then validated again using Gnuplot. Ten models were generated for each round of loop modeling, which were further validated using Gnuplot. The model with the best model energy when compared with the template structure energy was identified and the model showing the best Gnuplot was then subjected to structural validation using SWISS-MODEL structure assessment tool (Arnold et al., 2006). Along with this, further validation of the modeled protein structure was carried out using: PROCHECK (http://www.biochem.ucl.ac.uk/~roman/ procheck/procheck.html) WHAT_CHECK (http://swift.cmbi.kun.nl/gv/whatcheck/) and ANOLEA (http://protein.bio.puc.cl/cardex/servers/ anolea/index.html)
Molecular docking Docking studies were carried out using MolDock™ (Molegro virtual docker) which is based on a new heuristic search algorithm that combines differential evolution with a cavity prediction algorithm (Thomsen & Christensen, 2006). The ligands from the crystal structure of E. coli DHFR were transferred into the workspace keeping the orientation as a control and were subsequently energy minimized and were kept as reference ligand. The model protein sequence with the ligands was maintained throughout the molecular dockings. The ligand binding modes were assumed to be similar in both target and template structure. Hydrogens were added to the ligand and protein molecules using the preparation wizard in the Molegro workspace. All structural water molecules were removed from the protein molecules using protein preparation wizard. During the import of the 3D structure of the ligands, charges, bond orders were assigned and the torsional angle of the 3D structure was also determined. Binding sites in the electrostatic © 2011 Informa UK, Ltd.
181
surface of the protein were identified using the grid based cavity prediction algorithm. A total of five cavities were detected and the prepositioned ligand in the active site cavity was identified and the docking was constrained to the predicted active site cavity. MolDock™ scoring function is responsible for evaluating the energy between the ligand and the protein target. Grid resolution, number of runs, population size, maximum iterations, scaling factor, and cross over rate were set as 0.30Å, 10, 50, 2000, 0.5, 0.9, respectively, for each run. Multiple poses were returned for each run with the Root Mean Square Deviation (RMSD) threshold set to 1.00Å. The pose with the highest rerank and MolDock score was retained in the workspace for detailed evaluation of the ligand binding at the active site cavity. MVD was installed in Windows vista operating system on an Intel Pentium IV processer with 2GB RAM.
Results Assessment of interactions of antibiotics and phytochemicals The above study evaluated the antimicrobial activities of the phytochemicals alone and in combination with antifolate drugs—SMX and TMP against P. aeruginosa PA01 strain. The organism was found to be susceptible to SMX and TMP. Also, all the phytochemicals investigated show significant inhibitory effects against the test strain. Among the phytochemicals tested, PA (13 mM) and GA (11.8 mM) show higher MIC than QUER (1.65 mM) and MYR (1.55 mM). The MIC are listed in Table 1. The curves with the effects of high to low levels (dose dependent) of drugs are presented in Figure 1A–F along with IC50 value for each drug (Table 1). The combinations of SMX and phytochemicals show synergistic mode of interaction, whereas the combination of TMP and phytochemicals show additivite mode of interaction. It is noteworthy that none of the antibiotic—phytochemical combinations are antagonistic. The FIC indexes of all the combinations tested are listed in Table 2.
Sequence alignment and homology model validation The sequence alignment of P. aeruginosa DHFR and the template structure E. coli DHFR (1RA2) are shown in Figure 2. The homology model generated with Modeller and the best probable structure was chosen based on minimum molpdfs and DOPE score. The energy value of the selected P. aeruginosa model was −17079.17 cal/mol and closely resembles to the template structure E. coli DHFR (1RA2) energy value of −18343.56 cal/mol. The 3D model of the P. aeruginosa DHFR in complex with NADP and folate is shown in Figure 3A. The final 3D model in complex with NADP and with a total number of 168 residues was validated using Ramachandran plot. From Ramachandran plot (Figure 4), it is observed that, 95.1% of residues are in the most favored regions, 4.9% of residues are in the additional allowed regions and there are no residues in the disallowed regions.
182 Premkumar Jayaraman et al. interactions with the side chain of Arg67 on the other side. In addition the adenine ring contacts many other amino acid residues which include Gln108, Ser65, Arg67, Gln68, Ala80, and Gly46. The amide group of nicotinamide ring forms three H-bonds with main chain atoms of Ile19, Asp 20, and Asn21. The pteridine moiety of the folate in the active site cavity interacts strongly with P. aeruginosa DHFR forming three H-bonds with the side chains of Ala10, Ile104, and Tyr110 (Figure 3D). The para amino benzoic acid in folate involve in strong hydrogen bonding with Arg55 side chain. The glutamate moiety in folate contacts the protein through three H-bonds which include Arg55, Lys35, and Leu31. The interaction residues of the cofactor NADP and the ligand folate are given in Table 3.
Molecular docking analysis NADP and folate binding to P. aeruginosa DHFR As expected, the cofactor NADP was bound to the P. aeruginosa DHFR enzyme in an extended conformation with the nicotinamide ring inserted into a cleft formed by the β sheet shown in Figure 3A. The pyrophosphate moiety of NADP binds favorably to the helix dipoles by binding to the amino ends of Gly46, Lys48, Thr49, and Ala107 (Figure 3C). The pyrophosphate also forms salt bridge with Arg47 and its side chain is stabilized by interacting with Gln108. The O2’-phosphate of the adenosyl ring interacts strongly with P. aeruginosa DHFR through five H-bonds involving the side chains of Ser66, Arg47, Gln68, and the main chain of Arg67. The adenine ring contacts the protein with strong hydrophobic interactions involving residues Val65 and Leu109 on one side and through stacking
TRI binding to P. aeruginosa DHFR TRI binds to the active site of P. aeruginosa DHFR with its trimethoxy phenyl side chain extending out toward the entrance of the binding pocket making Van der Waals contacts with the residues from α strands (Figure 3B). The pyrimidine ring of TMP is being held in the interior of a deep cleft at the active site cavity through Van der Waals and hydrogen bond interactions. The pyrimidine ring contacts the protein through three H-bond interactions with the residues Thr49, Ile104, and Tyr110. The trimethoxy phenyl side chain is in Van der Waals contact
Table 1. Minimum inhibitory concentration of all the drugs against P. aeruginosa PA01 used in this study. Antibiotics / MIC IC50 (doseSpecies phytochemicals (mM) response) (mM) 0.5 0.14 Pseudomonas Sulfamethoxazole aeruginosa Trimethoprim 0.11 0.0887 (PA01) Protocatechuic acid 13 10.73 Gallic acid 11.8 9.62 Quercetin 1.65 0.595 Myricetin 1.55 0.52
120 100 80 60 40 20 0 0.5
(B) 140 120 100 80 60 40 20 0 0.11 0.03 Viable bacteria (%)
Viable bacteria (%)
(A) 140
0.25
0.125
0.06
Concentration of SMX in mM (D) 140 120 100 80 60 40 20 0 11.8 0.81
6.5
3.25
1.63
Concentration of PA in mM
0.01
0.007
5.9 2.95 1.48 Concentration of GA in mM
0.74
Viable bacteria (%)
(F) 120
Viable bacteria (%)
(E) 140 120 100 80 60 40 20 0 1.55
0.03
Viable bacteria (%)
Viable bacteria (%)
(C) 140 120 100 80 60 40 20 0 13
0.05
Concentration of TMP in mM
0.78
0.39
0.19
Concentration of MYR in mM
0.1
100 80 60 40 20 0 1.65
0.83
0.41
0.21
0.1
Concentration of QUER in mM
Figure 1. Effects of high to low levels (dose dependent) of drugs (A–F). Journal of Drug Targeting
Phytochemical-antibiotic combinations as folate inhibitors with residues Lys48, Gly106, Ala107, and Gln108 at the entrance of the binding pocket and the inhibitor also contacts NADP cofactor binding at the active site cavity. TMP lies in the proximity of the folate binding site and forms Van der Waals interactions at the folate site. Modeling of phytochemicals into the active site cavity of P. aeruginosa DHFR. The structures of all the inhibitors used in this study are shown in Table 4. All the five inhibitors used in this docking study showed similar docking mode in the active site of P. aeruginosa DHFR. Most of the active site residues interacting with the inhibitors were the same as those interacting with the pyrimidine inhibitor, TRI. The major interactions with the active site residues involving hydrogen bonding and hydrophobic interactions are listed in Table 3. The target residues involved in an interaction with the docked pose of all the inhibitors are located at the NADP and folate bound active site cavity. The aromatic ring component of all the inhibitors are found buried deep inside the hydrophobic pocket of the active site and involve in strong hydrogen bonding with the target residues. In addition to the H-bond interactions of the inhibitors at the target residues the axial OH-group of PA (Figure 5A) interacts with His33, Leu31, and the pteridine moiety of the folate. Similar to PA, GA also interacts with the same target residues in addition to Table 2. Fractional inhibitory concentration (FIC) indexes for the in vitro antibiotic-phytochemical combinations. Antibiotics + Phytochemical Organism combinations FIC index Pseudomonas Sulfamethoxazole + 0.25 (S) aeruginosa (PA01) Protocatechuic acid Sulfamethoxazole + Gallic acid 0.38 (S) Sulfamethoxazole + Quercetin 0.38 (S) Sulfamethoxazole + Myricetin 0.38 (S) Trimethoprim + 1 (I) Protocatechuic acid Trimethoprim + Gallic acid 1 (I) Trimethoprim + Quercetin 2 (I) Trimethoprim + Myricetin 2 (I) S, synergy; I, additivity.
183
the H-bonds. The axial OH-group of GA (Figure 5B) contacts the target residues Leu31 and Phe162. The equatorial OH-group interacts with Ala9, Ala10, Ile104, Leu122, Tyr110, and Tyr121. The equatorial 7-hydroxyl group in trihydroxychromen of QUER (Figure 5C) interacts with Ala133, Asp132, Gly18, the axial 5-hydroxyl group interacts with Lys48 and the axial 3-hydroxyl group interacts with Arg47, Gly105, Met45, and Leu109. The axial 3-hydroxyl group in dihydroxyphenyl interacts with Arg22, Asp20, Leu23, and Ser 52 residues. Similar to QUER, MYR (Figure 5D) which has an additional hydroxyl group also interacts with the same target residues. The docked poses of all the inhibitors in both P. aeruginosa are ranked based on the rerank score and MolDock score and the best pose with the docking scores, interaction energy, H-bond energy, torsions which is the number of chosen rotatable bonds in the pose, ligand efficiency 1 (LE1): MolDock score/heavy atoms count, (LE3): Rerank score/heavy atoms count, are listed in Table 5.
Discussion The folate pathway is a potential antimicrobial drug target, because of its presence in many pathogenic microorganisms and absence in mammals (Bermingham & Derrick, 2002). TMP and analogs are reported to bind to the folate and NADP binding cleft of DHFR and inhibit folic acid biosynthesis (Huovinen, 2001). Although, TMP-SMX (cotrimoxazole) combination is a first-line therapy for various infections, the increasing resistance and severe toxicity profiles require the use of alternative strategies for treating infections caused by drug resistant pathogens (Masters et al., 2003). From the experimental investigation, it is observed that all the combinations of SMX and phytochemicals under investigation result in synergistic mode of interaction. This suggests that SMX and phytochemicals act on different enzymes and inhibit different steps in the same pathway or different pathway, thereby resulting in synergistic mode of action. Docking analysis confirms that the binding site of the phytochemicals (GA, MYR, PA, and QUER) is DHFR. SMX has been earlier reported to inhibit the DHPS enzyme (Huovinen, 2001). Hence our results suggest that SMX and
Figure 2. Sequence alignment of P. aeruginosa DHFR with the template E. coli (1RA2) DHFR. Score = 140 bits (354), expect = 9 × 10−39, method: compositional matrix adjust. Identities = 74/165 (44%), positives = 103/165 (62%), gaps = 8/165 (4%) © 2011 Informa UK, Ltd.
184 Premkumar Jayaraman et al. (A)
(B)
(C)
(D)
Figure 3. (A) Structure of P. aeruginosa DHFR. Schematic ribbon diagram, showing the overall fold of P. aeruginosa DHFR. NADP and folate are in yellow stick model with molecular surface in transparent grey colour; (B) structure of P. aeruginosa DHFR in complex with trimethoprim. NADP and folate as yellow stick (thin) and trimethoprim is shown as stick model; (C) the cofactor binding site of P. aeruginosa DHFR with NADP shown as yellow colour stick (thin) model; (D) the folate ligand binding site of P. aeruginosa DHFR with folate shown as yellow colour stick (thin) model. The residues are shown in wireframe and the hydrogen bonds in dotted green lines.
phytochemicals inhibit different enzymes and are hence synergistic in their mode of action. On the other hand indifferent/additive action of TMP and phytochemicals (GA, MYR, PA, and QUER) suggests that the binding site of these two compounds is the same enzyme (either same site on same enzyme or different sites on same enzyme). The docking analysis confirms the binding of all four phytochemicals (GA, MYR, PA, and QUER) to DHFR. It is also observed that TMP and the phytochemicals under investigation act at independent sites in the active site cavity of the same enzyme i.e., DHFR, interacting with common target residues. TMP is reported as a slow tight-binding inhibitor of the enzyme (Navarro-Martínez et al., 2005), hence at subinhibitory concentration the binding efficiency of this inhibitor is reduced. Moreover, in combination of the phytochemicals at subinhibitory concentration the binding affinity at the same cavity will possibly lead to competitive inhibition resulting in no inhibition of cell growth. It is noteworthy that the FIC indexes for TMP plus QUER (TMP + QUER) and TMP plus MYR (TMP + MYR) is higher and additivity is observed even at a combination
concentration of (1MIC × 1MIC). This can be explained based on the fact that, QUER and MYR dock at the active binding site cavity with eleven H-bonds and TMP with nine H-bond interactions at the same site, hence, there is a possibility that the competitive inhibition in these cases is further amplified. Also, QUER and MYR have higher interaction energy than PA and GA for P. aeruginosa DHFR supplementing the data on higher binding affinities of these inhibitors at the active site. Earlier reports on mechanism of action of epigallocatechin gallate show that it binds both to the folate and NADP binding site in the active site cavity of DHFR with a promoted binding on the NADP site (Spina et al., 2008). Further evidence on the inhibition mechanism of epigallocatechin gallate in S. maltophilia DHFR, an important nosocomial pathogen similar to P. aeruginosa is by competitive with respect to dihydrofolate and reversible in a fast process which is similar to that of TMP and it is also reported that epigallocatechin gallate could represent as an alternative drug in combination with SMX for the treatment of S. maltophilia infections (Navarro-Martínez et al., 2005). Because PA, GA, MYR, and QUER are Journal of Drug Targeting
Phytochemical-antibiotic combinations as folate inhibitors
185
180
Y0
4 PRO
180
180
0 F
180
General/pre-pro/proline favoured
General/pre-pro/proline allowed
Glycine favoured
Glycine allowed
Figure 4. Ramachandran plot of homology-modeled P. aeruginosa DHFR, derived by using rampage. All the labeled residues are in allowed regions. Table 3. List of major residues involved in hydrogen bonding and hydrophobic interactions with the inhibitors. Ligands Residues involved in hydrogen bonding and hydrophobic interactions Protocatechuic acid Ile8, Ala9, Ala10, Asp30, Ile104, Tyr110, Thr123, Phe34 Gallic acid Ile8, Asp30, His33, Phe34, Thr123 Quercetin Ile17, Ile19, Asn21, Gly46, Thr49, Gly106, Ala107, Gln108 Myricetin Ile17, Ile19, Asp20, Asn21, Lys48, Thr49, Gly106 Trimethoprim Lys48, Thr49, Ile104, Gly106, Ala107, Gln108, Tyr110 Folic acid Ala10, Lys32, Lys35, Arg55, Ile104, Tyr110 NADP Ile19, Asp20, Asn21, Arg47, Lys48, Thr49, Ser66, Gln68, Ala80, Gly106, Ala107, Gln108, Leu109, Asp132
structural analogs of Epigallocatechin gallate (EGCG) and TRI, the results presented in this article suggest for similar mechanisms of actions for these phytochemicals. Since new antibiotics are lacking in the market, and the pharmaceutical industry is reluctant to introduce new antimicrobial drugs, there is a need to develop new strategies for treating resistant bacteria. Possibly, existent antibiotics for which bacteria have developed resistance could be repositioned. Also, previously it is suggested that decreased usage of antibiotics can limit resistance development and prevent or delay the emergence of resistance (Amyes et al., 2007). The present investigation is a step forward in this direction. © 2011 Informa UK, Ltd.
Conclusion Dietary polyphenols are abundant in our diet such as tea, coffee, fruits, vegetables, and cereals making it beneficiary for human health. These polyphenols have been reported to have therapeutic potential for the prevention of some diseases and are also antimicrobial in action (El Gharras, 2009). Though there are many novel antimicrobials from plants, to the best of our knowledge, there are no single entity plant-derived antimicrobials used in the clinical settings till date. The anti-DHFR activities of the some plant polyphenols are presented in this article and validated by both experimental and docking studies. The
186 Premkumar Jayaraman et al. Table 4. List of all the inhibitors used for molecular docking study. Ligand CID no. Molecular IUPAC number Molecular weight H-bond donor/ formula (g/mol) Acceptor 154.12014 3/4 Protocatechuic 72 C7H6O4 3,4acid dihydroxybenzoic acid
Structure H O
H
O
O O
Gallic acid
370
C7H6O5
3,4,5trihydroxybenzoic acid
170.11954
4/5
H H
O H
O
O
O H
Quercetin
5280343
C15H10O7
2-(3,4dihydroxyphenyl)3,5,7trihydroxychromen4-one
302.2357
5/7
H
O
O
H
HO O
O
H
O H O
Myricetin
5281672
C15H10O8
3,5,7-trihydroxy2-(3,4,5trihydroxyphenyl) chromen-4-one
318.2351
6/8
O
O
H
H
H O
OH
O O H O H O
Trimethoprim
5578
C14H18N4O3
5-[(3,4,5trimethoxyphenyl) methyl]pyrimidine2,4-diamine
290.31772
2/7
O
H
O O
O
N H
N H
mechanism of action of the phytochemicals is suggested to be similar to that of TMP, that of, inhibiting the bacterial DHFR by competitive and reversible inhibition and they are synergistic in combination with SMX. The experimental findings are in good agreement with the computationally predicted binding affinities showing the potential of this study in antimicrobial drug discovery. Investigations are underway on biochemical analysis coupled with enzyme kinetic assays to further validate these interesting findings.
Declaration of interest This work was funded by a seed grant from Biopharmaceutical Engineering Cluster and an AcRF
N
N H
H
Tier 1 grant from Nanyang Technological University, Singapore.
References CLSI guidelines. (1992). Methods for Determining Bactericidal Activity of Antimicrobial Agents: Tentative Guideline M26-T. Methods for Determining Bactericidal Activity of Antimicrobial Agents. Achari A, Somers DO, Champness JN, Bryant PK, Rosemond J, Stammers DK. (1997). Crystal structure of the anti-bacterial sulfonamide drug target dihydropteroate synthase. Nat Struct Biol, 4, 490–497. Amyes SG, Walsh FM, Bradley JS. (2007). Best in class: a good principle for antibiotic usage to limit resistance development? J Antimicrob Chemother, 59, 825–826. Journal of Drug Targeting
Phytochemical-antibiotic combinations as folate inhibitors (A)
(B)
(C)
(D)
187
Figure 5. (A) Protocatechuic acid; (B) gallic acid; (C) quercetin; (D) myricetin; docked at the active site of P. aeruginosa DHFR. NADP and folate are shown in yellow stick (thin). The residues are shown in wireframe and the hydrogen bonds are indicated as dotted green lines.
Table 5. Docking scores, interaction energy and H-bond energy between inhibitors and P. aeruginosa DHFR. Torsions Ligand (no. of chosen Interaction efficiency rotatable bonds energy MolDock (LE1) in the pose) H-bond Ligand score Rerank score (Kcal/mol) Protocatechuic −70.206 −60.813 −77.9648 1 −7.03 −6.38 acid Gallic acid −74.4306 −66.073 −86.0814 1 −7.82 −6.2 Quercetin −88.146 −74.78 −108.819 1 −10.49 −4 Myricetin −86.367 −78.995 −108.234 1 −11.4 −3.76 Trimethoprim −101.1 −81.461 −117.861 5 −8.44 −4.81 Arnold K, Bordoli L, Kopp J, Schwede T. (2006). The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics, 22, 195–201. Bermingham A, Derrick JP. (2002). The folic acid biosynthesis pathway in bacteria: evaluation of potential for antibacterial drug discovery. Bioessays, 24, 637–648. Brown PD, Izundu A. (2004). Antibiotic resistance in clinical isolates of Pseudomonas aeruginosa in Jamaica. Rev Panam Salud Publica, 16, 125–130. Coutinho HDM, Costa JGM, Lima EO, Falcão-Silva VS, Siqueira Jr JP. (2009). Herbal therapy associated with antibiotic therapy: Potentiation of the antibiotic activity against methicillin - Resistant Staphylococcus aureus by Turnera ulmifolia L. BMC Complement Altern Med, 9, 13. © 2011 Informa UK, Ltd.
Ligand efficiency (LE3) −5.53
Docking score −79.4554
−5.51 −3.39 −3.43 −3.88
−77.3821 −96.413 −94.983 −105.162
Coutinho HD, Costa JG, Lima EO, Falcão-Silva VS, Siqueira-Júnior JP. (2008). Enhancement of the antibiotic activity against a multiresistant Escherichia coli by Mentha arvensis L. and chlorpromazine. Chemotherapy, 54, 328–330. El Gharras H. (2009). Polyphenols: Food sources, properties and applications - A review. Int J Food Sci and Tech, 44, 2512–2518. Eswar N, Eramian D, Webb B, Shen MY, Sali A. (2008). Protein structure modeling with MODELLER. Methods Mol Biol, 426, 145–159. Garo E, Eldridge GR, Goering MG, DeLancey Pulcini E, Hamilton MA, Costerton JW, James GA. (2007). Asiatic acid and corosolic acid enhance the susceptibility of Pseudomonas aeruginosa biofilms to tobramycin. Antimicrob Agents Chemother, 51, 1813–1817.
188 Premkumar Jayaraman et al. Hancock REW. (1997). The bacterial outer membrane as a drug barrier. Trends Microbiol, 5, 37–42. Hawser S, Lociuro S, Islam K. (2006). Dihydrofolate reductase inhibitors as antibacterial agents. Biochem Pharmacol, 71, 941–948. Hemaiswarya S, Kruthiventi AK, Doble M. (2008). Synergism between natural products and antibiotics against infectious diseases. Phytomedicine, 15, 639–652. Hill SF, Haldane DJ, Ngui-Yen JH, Smith JA. (1985). In vitro susceptibility of Pseudomonas species to carbenicillin and trimethoprimsulfamethoxazole. J Clin Microbiol, 22, 465–466. Huovinen P. (2001). Resistance to trimethoprim-sulfamethoxazole. Clin Infect Dis, 32, 1608–1614. Kipnis E, Sawa T, Wiener-Kronish J. (2006). Targeting mechanisms of Pseudomonas aeruginosa pathogenesis. Med Mal Infect, 36, 78–91. Lai S, Tremblay J, Déziel E. (2009). Swarming motility: a multicellular behaviour conferring antimicrobial resistance. Environ Microbiol, 11, 126–136. Lister PD, Wolter DJ, Hanson ND. (2009). Antibacterial-resistant Pseudomonas aeruginosa: clinical impact and complex regulation of chromosomally encoded resistance mechanisms. Clin Microbiol Rev, 22, 582–610. Litzow JM, Gill CJ, Mantaring JB, Fox MP, MacLeod WB, Mendoza M, Mendoza S, Scobie R, Huskins CW, Goldman DA, Hamer DH. (2009). High frequency of multidrug-resistant gram-negative rods in 2 neonatal intensive care units in the Philippines. Infect Control Hosp Epidemiol, 30, 543–549. Masters PA, O’Bryan TA, Zurlo J, Miller DQ, Joshi N. (2003). Trimethoprim-sulfamethoxazole revisit. ed. Arch Intern Med, 163, 402–410. McGowan JE Jr. (2006). Resistance in nonfermenting gram-negative bacteria: multidrug resistance to the maximum. Am J Infect Control, 34, S29–37; discussion S64.
Navarro-Martínez MD, Navarro-Perán E, Cabezas-Herrera J, RuizGómez J, García-Cánovas F, Rodríguez-López JN. (2005). Antifolate activity of epigallocatechin gallate against Stenotrophomonas maltophilia. Antimicrob Agents Chemother, 49, 2914– 2920. Nicotra MB, Rivera M, Dale AM, Shepherd R, Carter R. (1995). Clinical, pathophysiologic, and microbiologic characterization of bronchiectasis in an aging cohort. Chest, 108, 955–961. Obritsch MD, Fish DN, MacLaren R, Jung R. (2005). Nosocomial infections due to multidrug-resistant Pseudomonas aeruginosa: epidemiology and treatment options. Pharmacotherapy, 25, 1353–1364. Rubin J, Yu VL. (1988). Malignant external otitis: insights into pathogenesis, clinical manifestations, diagnosis, and therapy. Am J Med, 85, 391–398. Spina M, Cuccioloni M, Mozzicafreddo M, Montecchia F, Pucciarelli S, Eleuteri AM, Fioretti E, Angeletti M. (2008). Mechanism of inhibition of wt-dihydrofolate reductase from E. coli by tea epigallocatechin-gallate. Proteins, 72, 240–251. Stern GA. (1990). Pseudomonas keratitis and contact lens wear: the lens/eye is at fault. Cornea, 9 Suppl 1, S36–8; discussion S39. Strateva T, Yordanov D. (2009). Pseudomonas aeruginosa - a phenomenon of bacterial resistance. J Med Microbiol, 58, 1133–1148. Thomsen R, Christensen MH. (2006). MolDock: a new technique for high-accuracy molecular docking. J Med Chem, 49, 3315–3321. Ulrich-Merzenich G, Panek D, Zeitler H, Wagner H, Vetter H. (2009). New perspectives for synergy research with the “omic”technologies. Phytomedicine, 16, 495–508. Wagner H, Ulrich-Merzenich G. (2009). Synergy research: approaching a new generation of phytopharmaceuticals. Phytomedicine, 16, 97–110. Wang MC, Liu CY, Shiao AS, Wang T. (2005). Ear problems in swimmers. J Chin Med Assoc, 68, 347–352.
Journal of Drug Targeting
