ISSN: 0975-766X CODEN: IJPTFI Available Online through ... · is currently targeted by methotrexate...

Archana Moon*et al. /International Journal of Pharmacy & Technology

IJPT| April-2017| Vol. 9 | Issue No.1 | 28816-28829 Page 28816

ISSN: 0975-766X

CODEN: IJPTFI

Available Online through Research Article

www.ijptonline.com IN SILICO STUDIES OF INHIBITORS OF DIHYDROFOLATE REDUCTASE AND DIHYDROPTEROATE

SYNTHASE OF E.COLI

Archana Moon1, Deeba Khan

2, Pranjali Gajbhiye

3 & Monali Jariya

4

1,2,3&4 University Department of Biochemistry, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur -440033.

Email: [email protected]

Received on: 10-02-2017 Accepted on: 22-03-2017

Abstract:

In the past two decades, antibiotic resistance has become an increasingly severe health problem. Bacterial infections

caused by resistant strains are problematic in numerous hospitals around the world, especially in patients compromised

by age, illness, and treated with immune-suppressant drugs. Antibiotics have a distinct mechanism of action capable of

modifying microbial metabolism and physiological processes such as translation, DNA replication and cell wall

biosynthesis. In this context, it is essential to increase the understanding of resistance mechanisms in order to develop

drugs with potential activity against these pathogens. Escherichia coli is the most common causative agent of urinary

tract infection (UTI), and diagnosing this infection usually relies on bacteriologic methods. Urinary tract infection (UTI)

is the second most common bacterial infection after respiratory tract infection. Approximately 75-95% of UTIs are

caused by Escherichia coli. Sulfonamides are competitive inhibitors of dihydropteroate synthase, the bacterial enzyme

responsible for the incorporation of para-aminobenzoic acid (PABA) into dihydropteroic acid, the immediate precursor

of folic acid.

Trimethoprim exerts a synergistic effect with sulfonamides. It is a potent and selective competitive inhibitor of

microbial dihydrofolate reductase, the enzyme that reduces dihydrofolate to tetrahydrofolate. Docking studies are

molecular modelling studies aimed at finding a proper fit between ligand and its binding site. The present paper deals

with studies to corrobarate the microbial and molecular studies to treat MDR resistant bacterial infections. Autodock

Suite, version 1.5 6rC2 for Docking has been utilized in this study.

Keywords: Dihydrofolate reductase(DHFR), Dihydropteroate synthase (DHPS), Docking, E.coli, Multidrug

resistant(MDR).

http://www.ijptonline.com/

mailto:[email protected]


IJPT| April-2017| Vol. 9 | Issue No.1 | 28816-28829 8817

Introduction:

UTI is a serious health problem affecting millions of people each year. Infections of the urinary tract are the second most

common type of infection. These are one of the most common bacterial infections affecting humans throughout their

lifespan. These infections are more common in females than in males (1). It is caused by Gram-negative bacteria such as

Escherichia coli, Klebsiella species, Enterobacter species, Proteus species and Gram-positive bacteria like Enterococcus

species, and Staphylococcus saprophyticus. Studies from various parts of India have shown occurrence of high rates of

antimicrobial resistance among E coli. The resistance rates of uropathogenic E. coli to various antibiotics such as beta-

lactams (57.4%), co-trimoxazole (48.5%), quinolones (74.5%), gentamicin (58.2%), amikacin (33.4%), cefuroxime

(56%), nalidixic acid (77.7%) have been reported (2). UTI due to multi drug resistant (MDR) E. coli increases the cost of

treatment, morbidity and mortality especially in developing countries like India (2). The infection caused by MDR

bacteria leads to limited treatment options (3). Antibiotic resistance is a worldwide problem threatening the ability to

treat infections (4). Despite advancements of higher generations of antibiotics, these antibacterial agents have not been

up to the mark in eradicating these infectious diseases. One of the possible reasons responsible for this decline in

therapeutic control of the disease is antibiotic resistance. The MDR bacteria due to continued mismanaged selective

pressure have been credited for being responsible for genetic response to antibacterial therapy (5).

Resistance in Gram-negative bacteria has been increasing, particularly over the last 6 years. Many of the isolates

producing these enzymes are also resistant to trimethoprim, quinolones and aminoglycosides. Novel combinations of

antibiotics are being used in the community and broad-spectrum agents such as carbapenems are being used increasingly

as empirical treatment for severe infections (6). Microorganisms use various mechanisms to develop drug resistance,

such as recombination of foreign DNA in bacterial chromosome, horizontal gene transfer and alteration in genetic

material (7). The folate metabolic pathway leads to synthesis of required precursors for cellular function and contains a

critical node, dihydrofolate reductase (DHFR), which is shared between prokaryotes and eukaryotes. The DHFR enzyme

is currently targeted by methotrexate in anti-cancer therapies, by trimethoprim for antibacterial uses, and by

pyrimethamine for anti-protozoal applications. An additional anti-folate target is dihyropteroate synthase (DHPS), which

is unique to prokaryotes as they cannot acquire folate through dietary means. It has been demonstrated as a primary

target for the longest standing antibiotic class, the sulfonamides, which act synergistically with DHFR inhibitors.



Investigations have revealed most DHPS enzymes possess the ability to utilize sulfa drugs metabolically, producing

alternate products that presumably inhibit downstream enzymes requiring the produced dihydropteroate. These inhibitors

are also likely to interact with the enzymatic neighbors in the folate pathway that bind products of the DHFR or DHPS

enzymes and/or substrates of similar substructure (8) Fig (1). Commonly used sulfa drug is co-trimoxazole, an

association of two antifolate agents, sulfamethoxazole and trimethoprim (9). Dihydrofolate reductase (DHFR) is a

ubiquitous enzyme present in almost all eukaryotic and prokaryotic cells (11). Inhibition of DHFR results in a depletion

of the reduced folate pool, inhibition of RNA and DNA synthesis, and cell death. For this reason, DHFR has been a

critically important therapeutic drug target. DHFR inhibitors targeting the FH2 binding site have been used in the

treatment of cancer, autoimmune diseases and bacterial and fungal infections (10). Most microorganisms must synthesize

folate denovo since they lack the active transport system of higher vertebrate cells that allows these organisms to use

dietary folates. DHPS (Gene folP) is the target of sulphonamides, which are substrate analogues that compete with para-

aminobenzoic acid. Molecular docking has become an increasingly important tool for drug discovery (12). Detailed

analysis was performed for a better understanding of the molecular interactions between the ligands and target DHFR &

DHPS proteins of E. coli based on their efficiency to bind the active sites on the receptor utilizing Autodock (version 1.5

6rC2). The docking exhibits different binding poses out of which the one with minimum binding energy was selected.

The favourable conformation was analysed with hydrogen bonding with the active site residues of DHFR & DHPS (13).

Fig(1): Folate Pathway In Bacteria (20).



Materials & Methods:

In silico studies

Molecular docking is an important tool to study the interaction of ligands with active site residues of the receptor [14,

15]. The docking involves the use of sampling algorithm and a scoring function to evaluate the proper orientation and

pose of ligand molecule in relation to the binding energy. The correct identification of this binding pose of one or more

related ligands is important in establishing a structure-activity relationship in lead optimization. The second use of

scoring functions is to rank different ligands to predict their relative experimental activity [15-17].

In silico studies were performed using Autodock 4 suite (version 1.5 6rC2). The ligands viz, Chlorogenic acid, Ellagic

acid, Gallic Acid, Hippuric acid, Quercetin and Standard Antibiotics viz, Clavulanic acid, Cephalosporin, Cephalosporin

C, Penicillin, Sulfamethoxazole and Trimethoprim were docked with DHFR & DHPS enzymes of E.coli. The structure

of DHFR of E.coli was downloaded from PDB (protein data base) with PDB Id 2ANO (X ray diffraction structure,

2.6A0) & PDB Id 1AJ0 for DHPS of E.coli ( X ray diffraction structure, 2.0A

0). Refer Fig (2). The PubSum database,

utilizes 4 characters, as inputs, to get the ligands with their Ligplots. Ligplots indicate the interacting sites of the protein

of interest i.e DHFR & DHPS Fig(3,4). Next a Ramachandran Plot Fig(5) to verify the protein structure was plotted. The

structure of the ligands were downloaded from Pubchem (chemical structure data base) online portal and drawn in

Marvin Sketch version 5.8.1. Fig(6,7). Docking was performed for DHFR & DHPS of E.coli with ligands (Chlorogenic

acid, Ellagic acid, Gallic Acid, Hippuric acid and Quercetin and Standard Antibiotics (Clavulanic acid, Cephalosporin

Cephalosporin C, Penicillin, Sulfamethoxazole and Trimethoprim). The docking results were analyzed on the basis of

their binding energy and their interactions (13).

Fig(2): PDB Structure of DHFR and DHPS Protein.



Fig(3): Ligplot of DHFR E.coli Ligand: A)Ligand NDP- (Ala7, Ile14, Arg44, Thr46, Ser63, Ser64, Gly97, Arg98,

Gln102) &B) Ligand 817 – Asp27 & Thr113 interaction are shown by green dashed line.

Fig(4): Ligplot of DHPS E.coli Ligand: A)Ligand SO4 284 –Arg255, Asn22, Arg63, His257 B) Ligand PH2 559-

Thr62, Lys221, Asn115, Asp96 & C) San561 – SER219 interaction are shown by green dashed line.



Fig (5): The Ramachandran plot shows the phi-psi torsion angles for all residues in the structure. Glycine residues

are separately identified by triangles as these are not restricted to the regions of the plot appropriate to the other

sidechain types. The colouring/shading on the plot represents the different regions: the darkest areas (here shown

in red) correspond to the "core" regions representing the most favourable combinations of phi-psi values.

Fig(6): INHIBITORS - (A) Chlorogenic acid,(B) Ellagic acid, (C) Gallic acid, (D) Hippuric acid and (E)

Quercetin.

Fig(7): ANTIBIOTICS AS LIGANDS- (A)Clavulanic acid, (B) Cephalosporin,(C) CephalosporinC, (D) Penicillin,

(E) Sulfamethoxazole and (F) Trimethoprim

Preparation of Proteins and Ligands:

The Ligands that exhibited prominent antibacterial activity towards isolated multidrug-resistant bacteria were selected

for molecular docking analysis. The structure of DHFR & DHPS was opened in Biovia Discovery Studio 2016 version



16.1.0.15350. The structure of protein was cleared (i.e. the extra groups which includes water molecules, ligand groups

were removed) by deleting the heteroatoms present in the protein (18). Only the protein and active site for docking is

required. Hence was saved in the PDB format. The structure of ligands were downloaded from Pubchem and drawn in

Marvin Sketch view version 5.8.1 and cleaned in 2D and 3D. This clears the 2 dimensional and 3 dimensional structure

of the ligand. For docking, the protein structure was obtained in PDB format and ligands in tripos-Mol format or PDB

format (18).

Grid formation by Autodock:

Grid points generate the coordinates or interaction points where the ligand is docked. The grid box was generated at

60x60x60 A0

to cover all the active site residues, and allowed the flexible rotation of ligands. The GA (genetic

algorithm) and number of generation were set to 10 and 27000 for DHFR 60 and 27000 for DHPS respectively. The

Lamarckian genetic algorithm was followed for ligand confirmation. All the above parameters decide the different

confirmation of ligand in which the ligand will be docked. Other parameters for example, free energy (after docking is

complete we get the value of free energy), rotatable bonds (number of rotatable bonds varies according to the ligand

structure), number of torsions (18) etc were used as default (18).

Result:

Docking studies revealed the interaction of the protein with the ligand, binding energy, type of interaction and amino

acids involved in interactions. Binding energy should be negative. More negative the binding energy, better the binding

affinity of ligand and protein (18). Table 1 & 2 give the binding energy of ligands with DHFR & DHPS respectively.

Table No.1: Binding Energy of Legends with DHFR Protein of E.COLI.

LIGANDS Binding Energy of DHFR E.coli

INHIBITORS

Chlorogenic acid -8.70

Ellagic acid -7.90

Gallic acid -5.93

Hippuric acid -6.45

Quercetin -7.73

ANTIBIOTICS

Clavulanic acid -6.41

Cephalosporin -8.48

Cephalosporin C -9.10

Penicillin -9.11

Sulfamethoxazole -7.50

Trimethoprim -7.91



Inhibitors (Chlorogenic acid, Ellagic acid, Gallic Acid, Hippuric acid and Quercetin) and Standard Antibiotics

(Clavulanic acid, Cephalosporin, Cephalosporin C, Penicillin, Sulfamethoxazole and Trimethoprim) were docked and the

results obtained provide a comparative insight into the potency of inhibitors and Standard Antibiotics through analysis of

their binding capacities. The binding energies of DHFR of E.coli with Penicillin, Cephalosporin C & Chlorogenic acid

are better than other ligands. From table no.1 it is clear that Standard Antibiotics like Penicillin and Cephalosporin C are

more effective than the inhibitors docked. Table No.2:

Table No.2: Binding Energy of Legends with DHPS Protein of E.COLI.

The binding energies of DHPS of E.coli with Clavulanic acid, Gallic acid, Hippuric acid and Trimethoprim are (-6.57,-

6.25,-5.91 and -5.58). From table no.2 it is clear that Standard Antibiotics like Clavulanic acid are more effective than

the inhibitor i.e Gallic acid and Hippuric acid for the DHPS protein.

Table No.3: Interaction of ligands with dhfr and dhps protein i.e. Hydrogen bond length and name and amino

acid involved in interaction.

LIGANDS DHFR E.coli DHPS E.coli

Hydrogen

Bond Length

In A°

Hydrogen

Bond Name

Interactin

g Sites

Hydrogen

Bond Length

In A°

Hydrogen

Bond Name

Interacting

Sites

Chlorogenic 2.202 Thr46 Ala7 1.969 Asn115 Asn115

LIGANDS Binding Energy of DHPS E.coli

INHIBITORS

Chlorogenic acid +4.98

Ellagic acid -2.31

Gallic acid -6.25

Hippuric acid -5.91

Quercetin -4.43

ANTIBIOTICS

Clavulanic acid -6.57

Cephalosporin +8.94

Cephalosporin C +0.42

Penicillin +6.13

Sulfamethoxazole -3.99

Trimethoprim -5.58



acid 2.083

1.846

1.888

2.205

Thr46

Gly97

-

Ala7

1.824 - Arg255

Ellagic acid 2.125

1.79

2.173

2.233

-

-

-

Ser49

Thr46

Ala7

2.143 - -

Gallic acid 1.838

2.018

1.993

-

-

Ala7

Asp27 1.959 - -

Hippuric acid 2.148 Ala7 Thr113

Ala7

1.978 - -

Quercetin 1.725

1.963

Gly97

Thr123

Ser64

Gln102

Arg98

1.727

1.782

-

Arg255

Lys221

Clavulanic acid 1.978

2.212

-

Ala7

Ala7 2.035

1.655

2.11

1.83

Asn115

Lys221

Phe188

-

Lys221

Asp185

Cephalosporin 2.242

2.146

Gly97

Ala7

Ala7 1.738 Ser94 Thr62

Cephalosporin

C

2.1

2.135

Arg98

Asn18

Gly97

Arg98

- No -

Penicillin 2.171

1.907

Ala7

Gly97

Thr46

Gly97

1.693 Gly191 -



Ala7

Sulfamethoxaz

ole

2.127

1.938

-

Ala7

Thr46

Ala7

1.919 Met223 -

Trimethoprim 1.878

1.835

-

-

Ala7 1.827 - -

Table 3 give the interaction of various ligands with DHFR & DHPS i.e. hydrogen bond length, hydrogen bond name and

amino acid involved in the interaction. As these ligands/ inhibitors have proven antibacterial, antimicrobial and

anticancer activity, these ligands can be further used as lead compounds in treatment of multidrug resistant urinary tract

infection caused by E.coli.

Inhibitors (EA, GA, HA & Q) & Standard Antibiotics (Cep C, Pen, SMX &TMP) show no interaction with DHPS. This

indicates that the ligands do not bind to the active site of the protein. Cep C shows no hydrogen bonding, which indicates

improper docking.



Fig (8): Interacting Sites of DHFR with Inhibitors i.e. (A) Chlorogenic acid,(B) Ellagic acid, (C) Gallic acid, (D)

Hippuric acid and (E) Quercetin.

Fig(9): Interacting Sites of DHFR with Standard Antibiotics i.e. (A) Clavulanic acid, (B) Cephalosporin,(C)

CephalosporinC, (D) Penicillin, (E) Sulfamethoxazole and (F) Trimethoprim.

Fig(10): Interacting Sites of DHPS with Inhibitors and Standard Antibiotics: (A) Chlorogenic acid, (B) Quercetin,

(c) Clavulanic acid and (D) Cephalosporin.



Discussion:

Urinary tract infections (UTIs) are among the most common infections in humans. The majority of cases are caused by a

limited number of bacterial genera; E. coli strains in particular are responsible for 80% of the UTI cases seen in

outpatient clinics. These strains are found in the normal flora of the intestinal tract, skin, and vagina.(19)

Insilico studies with DHFR & DHPS showed various hydrogen interactions with inhibitors viz., Chlorogenic acid,

Ellagic acid, Gallic Acid, Hippuric acid and Quercetin and Standard Antibiotics viz., Clavulanic acid, Cephalosporin,

Cephalosporin C, Penicillin, Sulfamethoxazole and Trimethoprim.

From the results, it is clear that the inhibitors CGA, EA, GA, HA and Q show negative/higher binding affinity. These

were analysed for their binding efficiency to the active site of DHFR of E.coli. As compared to inhibitors particularly

CGA, antibiotics show higher binding results, such as Penicillin & Cephalosporin C, thereby contributing towards higher

interactions with the DHFR of E.coli.

Our study reveals that inhibitors like Clavalunic acid and Gallic acid were analysed for their binding efficiency to the

active site DHPS of E.coli. Clavalunic acid and Gallic acid have the highest binding affinity to the ligand binding pocket

of DHPS of E.coli. As compared to inhibitors i.e Gallic acid and Hippuric acid, antibiotics like Clavalunic acid and

Trimethoprim show higher interactions towards DHPS of E.coli.

Protein binding with various ligands, indicate that various inhibitors of DHFR can be utilized for the treatment of MDR-

UTI after due invivo, invitro and ADMET testing.

Conclusion:

In spite of the enormous success of antibiotics as antibacterial agents, the widespread and uncontrolled use of antibiotics

has led to the emergence of multidrug-resistant (MDR) bacteria (13). Emergence of multidrug resistant (MDR) bacteria

provides with limited treatment options along with increased mortality. Hence, there is an urgent need to search for a

new antibacterial agent. The molecular docking programs aid to establish new ligands/inhibitors for the selected target

receptor proteins from the different available databases, based on their efficiency to bind the active sites on the receptor

(13). Our study shows that Penicillin and clavulanic acid of DHFR and DHPS show higher binding affinity to the

proteins of the folate synthesis pathway of E.coli. These In silico Studies supported with invivo, invitro and ADMET

testing will certainly help towards developing candidates for treatment of MDR-UTI in the future.



Acknowledgements:

We acknowledge the grant received from R&I Technology Transfer Project funded by RUSA, Maharashtra Government

India for Rs.35 lacs, June 2016, (Sanction No. RUSA/order/R&I/2016-17/273) Dt. 18/6/2016.

References:

1. Seema Rawat*. Urinary Tract Infections: Etiology and Management. Vol 5| Issue 3| 2015 | 163-169.

2. Niranjan V. & Malini A. Antimicrobial resistance pattern in Escherichia coli causing urinary tract infection among

inpatients, Indian J Med Res 139, June 2014, pp 945-948.

3. Pallavi Sahare†, Archana Moon*, Tanvee Pardeshi†† and Sameer Chpudhary††† . The analysis of inhibitory activity

of Phyto-Ligands against TEM β Lactamase from multidrug resistant Escherichia coli. Archana Moon* et al.

International Journal Of Pharmacy & Technology.

4. Neetu Sharma*, Anita Gupta, Geeta Walia, Rupinder Bakhshi, Pattern of Antimicrobial Resistance of Escherichia

coli Isolates from Urinary Tract Infection Patients: A Three Year Retrospective Study, Journal of Applied

Pharmaceutical Science Vol. 6 (01), pp. 062-065, January, 2016

5. Abha Kumari1, Santosh Kumar

2, Sandeep Kumar

3,Observation on Prevalence and Mechanism of Multi Drug

Resistant Escherichia Coli Causing Uncomplicated Urinary Tract Infection in Female

6. Ann Pallett 1* and Kieran Hand

2Complicated urinary tract infections: practical solutions for the treatment of

multiresistant Gram-negative bacteria J Antimicrob Chemother 2010; 65 Suppl 3: iii25–33

7. Sumera Sabir1, Aftab Ahmad Anjum

2, Tayyaba Ijaz

3, Muhammad Asad Ali

4, Muti ur Rehman Khan

5, Muhammad

Nawaz6 Isolation and antibiotic susceptibility of E. coli from urinary tract infections in a tertiary care hospital.

8. Christina R. Bourne † Utility of the Biosynthetic Folate Pathway for Targets in Antimicrobial Discovery ,

Antibiotics 2014, 3, 1-28; doi:10.3390/antibiotics3010001.

9. S. Latouche*, P. Lacube*, E. Maury, J. Bolognini*, M. Develoux, PM. Girard§, C. Godet, MG. Lebrette**, C.

Mayaud, J. Guillot & P. Roux*, Pneumocystis jirovecii dihydropteroate synthase genotypes in French patients with

pneumocystosis: a 1998-2001 prospective study, Medical Mycology December 2003, 41, 533-537.

10. Yi-Ching Hsieh, Philip Tedeschi, Rialnat AdeBisi Lawal, Debabrata Banerjee, Kathleen Scotto, John E. Kerrigan,

Kuo-Chieh Lee, Nadine Johnson-Farley, Joseph R. Bertino, and Emine Ercikan Abali Enhanced Degradation of



Dihydrofolate Reductase through Inhibition of NAD Kinase by Nicotinamide Analogs Mol Pharmacol 83:339–353,

February 2013.

11. Shinde GH*, Pekamwar SS and Wadher SJ An overview on dihydrofolate reductase inhibitors International Journal

of Chemical and Pharmaceutical Sciences 2013, June., Vol. 4 (2).

12. Xuan-Yu Meng1,2

, Hong-Xing Zhang1,*

, Mihaly Mezei3, and Meng Cui

2,* Molecular Docking: A powerful approach

for structure-based drug discovery Curr Comput Aided Drug Des. 2011 June 1; 7(2): 146–157.

13. Pallavi Sahare11

, Archana Moon. In silico modelling of β-lactam resistant Enterococcus faecalis PBP4 and its

interactions with various phyto-ligands.. International Journal of Pharmacy and Pharmaceutical Sciences, Vol 8,

Issue 7, 2016.

14. Brooijmans N, Kuntz I. Molecular recognition and docking algorithms. Annu Rev Biophys Biomol Struct

2003;32:335-73.

15. Kitchen D, Decornez H, Furr J, Bajorath J. Docking and scoring in virtual screening for drug discovery: methods

and applications. Nat Rev Drug Discovery 2004;3:935-49.

16. Hartshorn M, Murray C, Cleasby A, Frederickson M, Tickle I, Jhoti H. Fragment-based lead discovery using X-ray

crystallography. J Med Chem 2005;48:403-13.

17. David E, Stephen N. Virtual screening of DNA minor groove binders. J Med Chem 2006;49:4232-8.

18. P. Sahare and A. Moon * In-silico docking studies of phyto-ligands against E. Coli PBP3: approach Towards novel

antibacterial therapeutic agent IJPSR, 2016; Vol. 7(9): 3703-3711. International Journal of Pharmaceutical Sciences

and Research.

19. Myriam T. N. Campanhã,1 Sumie Hoshino-Shimizu,

2 and Marina Baquerizo Martinez

1.Urinary tract infection:

detection of Escherichia coli antigens in human urine with an ELIEDA immunoenzymatic assay.

20. Brody's Human Pharmacology: With Student Consult Chapter 48 Bacterial Folate Antagonists, Fluoroquinolones,

and Other Antibacterial Agents.

ISSN: 0975-766X CODEN: IJPTFI Available Online through ... · is currently targeted by methotrexate...

Documents

Transcript of ISSN: 0975-766X CODEN: IJPTFI Available Online through ... · is currently targeted by methotrexate...