MOLECULAR DOCKING STUDIES OF CHROMENE ANALOGUES ON TRYPANOTHIONE REDUCTASE FOR TARGETING LEISHMANIASIS

MOLECULAR DOCKING STUDIES OF CHROMENE ANALOGUES

ON TRYPANOTHIONE REDUCTASE FOR TARGETING

LEISHMANIASIS

Jeevan Patra*, Harshadeep Garewal1 and Nripendra Singh Sengar2

*Birla Institute of Technology & Science, Pilani, Rajasthan, India.

1

SPP SPTM NMIMS University, Mumbai, India.

2

SIRTP, RGPV, Bhopal, Madhya Pradesh, India.

ABSTRACT

Leishmaniasis parasitic disease is one of the neglected and are an

epidemic in various countries, and these parasites are developing

resistance against drugs available in market. Thus, discovery and

development of new potent drugs against Leishmaniasis is an open

area of investigation for a researcher. To perform these challenges, a

series of chromene analogues have been designed and docked into the

active site of Trypanothione Reductase (TryR) enzyme required to

balance redox of the parasite. The potent ligands were screened (hits)

based on the search algorithm MolDock score by docking and

subjected to ADMET test to identify the suitable lead compound against leishmaniasis. In

total 18 compounds out of which compounds 11, 12, 14 were found to be the most active

among the tested compounds. Although the compounds showing moderate antileishmanial

activity, they identifies a chemical space to design and develop drugs based on these

chromene derivatives against the Leishmania parasite. Toxicology studies revealed

compound 14 as a nontoxic compound. Molecular Docking studies showed that compound 14

showed greater affinity towards TryR due to presence of hydrogen bonding formation exactly

at aforementioned positions. In this study we reported the molecular interaction mechanism

between chromene analogues and TRP using molecular docking and identified the compound

14 as potential lead compound against leishmaniasis. Further study on compound 14

analogues, lead optimization and validation such as increasing in bond length or replacing

halogen to –NO2, addition of bis-chromene, naphthyl etc. may lead to novel drug as lead

compounds against Leishmaniasis.

Volume 8, Issue 8, 659-673. Research Article ISSN 2277– 7105

Article Received on 25 April 2019,

Revised on 15 May 2019, Accepted on 05 June 2019,

DOI: 10.20959/wjpr20198-15243

*Corresponding Author Jeevan Patra

Birla Institute of Technology

& Science, Pilani, Rajasthan,

KEYWORD: Trypanothione Reductase, Molegro Virtual Docker 4.0, ADMET Test, Drug

Likenesses, Protein Data Bank: 2JK6.

INTRODUCTION

Encompassing a complex group of diseases, leishmaniasis is one of the neglected disease

which is caused by unicellular eukaryotic obligatory intracellular protozoa of the genus spp.

Leishmania and primarily affects to the host’s reticuloendothelial system. Leishmaniasis is a

parasitic infectious disease which is spread by the bite of female sand flies (phlebotomine)

and it is caused by the genus Leishmania. Around 20 species of Leishmania parasites are

pathogenic for humans while 30 species of sand fly act as a vector.[1] Leishmania having

three clinical forms are present: cutaneous, mucocutaneous and visceral leishmaniasis.

Among these above three clinical forms cutaneous leishmaniasis is a major concern because

it occurs as a co infection with AIDS.[2] Leishmaniasis patients usually suffer from fever, low

RBC count, skin ulcer and an enlarged liver.[3]

As per WHO epidemiology more than 12 million people in around 88 countries are known to

be infected with leishmaniasis and expected to rise at a progressive rate, but still the true

burden remains largely hidden. Two million new cases 1.5 million of cutaneous

leishmaniasis, 500,000 of the visceral leishmaniasis occurs annually. The declaration of this

disease is only compulsory in 32 countries and a substantial number of cases are never

recorded.[4] Approximately 20,000-50,000 deaths occurs every year. The disease usually

common in most of the continents like Asia, Central America, southern Europe and Africa

and around 200 million people live in these regions.[5] Out of several forms, most severe form

of leishmaniasis is visceral Leishmaniasis (Kala Azar) which is caused by L. donovani

complex which includes three species – L.donovani, L.infactum and L.chagas. Visceral

leishmaniasis (Kala Azar) found in India is caused by Leishmania donovani. As of 2019, no

successful vaccine was developed for leishmaniasis.[6]

The chemotherapeutic treatments those are currently available in market have a number of

limitations due to poor efficacy, unacceptable host toxicity and drug resistance, and new drug

targets are required. Newer serological test for determining leishmaniasis infection (ELISA)

do not function as well in immune compromised patients who aren't making antibodies to

infections. In these situations, two or more test must be used making the diagnostic procedure

di-sulfide oxidoreductase family of enzymes that presents as an ideal target for structure based

inhibitor drug design.[8]

The aim of our work is to identify the lead compound against leishmaniasis by virtual

screening of ligands. These ligands may have the property of inhibiting the TryR enzyme

thereby reducing the symptoms caused by leishmaniasis. Virtual screening is usually carried

out in two ways viz., Ligand-based drug design and structure based drug design.

In this research study we have performed drug discovery by choosing structure-based drug

design to identify the lead compound. Molecular Docking or Molecular Modelling is a

structure based drug design which has the ability to predict protein-ligand interaction[9] which

is a key tool in structural molecular biology and computer assisted drug design. The ligands

selected are chromene analogues. The evaluation of ADME and toxicological properties of a

drug is vital for successful drug development. Along with ADMET test is done to ensure the

drug cause no harm to leishmaniasis patients.[10] Evaluation of ADME is based on Lipinski's

rule of five (Pfizer's rule of five) and drug likeness score.

MATERIALS AND METHODS

Target Selection

Trypanothione Reductase (TryR) belongs to the di-sulfide oxidoreductase family of enzymes

and also identified as a NADPH dependent flavoprotein unique to protozoan parasites such as

Trypanosoma and Leishmania spp. As these protozoans doesn’t possess Glutathione

Reductase, so the enzymes such as Trypanothione, N – glutathionyl - spermidine and

auxiliary enzyme trypanothione reductase maintains the intracellular level of dihydro

trypanothione and eventually results in the maintenance of reducing environment in the

protozoan host.[11] The Trypanothione function was found to be essential for protozoan

survival because of the dithiol trypanothione play vital role in the synthesis of DNA

precursors, ascorbate homeostasis, hydroperoxides detoxification, and thiol conjugates

export. The major peroxidases that eliminates the reactive oxygen species (ROS) generated

during the aerobic metabolism are trypanothione dependent. So, Enzymes such as

Trypanothione, N – glutathionyl - spermidine and auxiliary enzyme trypanothione reductase

was identified as a potential target for developing drugs against Leishmaniasis, because these

enzymes are essential for the survival of protozoan parasites and it is absent in mammals. In

this study Trypanothione reductase (TryR) is used as a potential target for structure based

drug design.

Retrieval and preparation of receptor model

The three-dimensional structure of the Homology-Modelled Structure of Trypanothione

Reductase of Leishmania donovani was obtained from Protein Data Bank

(https://www.rcsb.org/). The protein preparation was automatically done by using protein

preparation tool that is Molegro Virtual Docker tool. During this preparation process it

automatically assigns the missing bonds, flexible torsions, bond orders, and charges to the

protein structure and make it available for the docking studies.

Retrieval and preparation of ligand

In this study, the screening of ligands is done by virtual screening. About 18 molecules were

finally selected for docking studies. From the reported research article Verma et al, 2012 we

retrieved most active chromene structure as ligand of our interest (Figure: 2). The ligands

used in this study are the three dimensional structure was retrieved from swisssimilarity

(www.swisssimilarity.ch/). The compounds were prepared by using same molecule module

assign bond order and hybridization, detect flexible torsions, create hydrogens explicity and

finally the minimized energy structures was obtained.

Molecular docking

The molecular docking was performed using Molegro Virtual Docker 4.0.0 (MVD), which

involves two major steps (1) the addition of molecular surface and (2) predicting of binding

sites. The molecular surface was added to the protein based on the default settings, which

results in the formation of a double colored surface according to electrostatic properties. The

potential binding sites for receptor protein was predicted using cavity prediction algorithm.[12]

This search algorithm predicts the exact location of cavities in receptor protein model and

makes it visualizes to the user in green color. The parameters were set by default to the

molecular surface with expanded Van der Waals and number of cavities to five. The

molecular docking further carried out which was based on MolDock Simplex Evolution

search algorithm with having a grid resolution at 30Å for grid generation and selects the

predicted cavities as the origin of the binding site. We used MolDock SE as a search

algorithm, many runs set to 10, maximum population 50 and maximum iteration 1500. The

energy minimization was carried out before docking process by using Chem3D professional

software as a designing tool for ligands. We docked all screened compounds using MVD 4.0

and binding efficiency is evaluated using the MolDock score. After docking the ADME,

Drug likeness test, Toxicity test was performed to check whether screened compounds (Hits)

with the good MolDock score are suitable to use as a lead compound.[13]

RESULTS AND DISCUSSIONS

After reviewing through the reported article chromene analogues those targeted with

trypanothione reductase we focused on an article reported by Rajiv et al, 2012 as ‘Molecular

Docking and in Vitro Antileishmanial Evaluation of Chromene-2-thione Analogues’. Below

Figure 2: Reported potent compounds retrieved from Rajiv et al, 2012.

Now we designed 18 compounds (Table: 1) from the reported potent compounds by help of

chemical modification. Pharmacophore modelling such as bioisostere part of chemical

modification. We replaced sulphur atom with oxygen atom followed by side ring extension

and modification such as replacement of sulphur atom with oxygen atom (compound 1,2,3);

replacing carbonyl group to methylene group (compound 4,5,6); addition of methylene group

(compound 7,8,9); addition of two methylene groups (compound 10,11,12); addition of -NH-

and piperidine (compound 13,14,15); addition of –NH (compound 16,17,18).

Table 1: Designed compounds by chemical modifications from Rajiv et al, 2012.

Compound Designed Structure

Compound 1

Compound 2

Compound 3

Compound 4

Compound 6

Compound 7

Compound 8

Compound 9

Compound 10

Compound 11

Compound 12

Compound 13

Compound 15

Compound 16

Compound 17

Compound 18

Grid Validation was performed to get confirmed and be assure whether the reported PDB

having co-crystallized ligand matches with better pose for docking within RMSD 2.0 Å

(Figure: 2). First of all we find the interactions of amino residues with co- crystallized ligand

(FAD_B) (Figure- 9). After docking the 18 compounds with our targeted protein (PDB:

2JK6), we found following MolDock score (Table: 3) and possible interactions (Table: 4).

Then we matched residues with our designed compounds with co - crystal ligand. We found

all 18 compounds matched with few amino residues that present in co- crystal ligand. Then

we focused on MolDock score. MolDock score of Co-crystal ligand was -141.115 kcal/mol.

Only three compound (compound 11, 12, 14) which having MolDock score more than that of

co- crystallized ligand.

ADME and Drug Likeness Prediction

The compounds with the good MolDock score (≥ -141.115) were identified as potential Hits.

In our study we found three hit compounds which were identified and subjected to ADME

test to compute drug likeness and to identify whether the identified compounds follow

Lipinski rule of five, which is considered as an important parameter for selection of any

compounds as a lead compound. The ADME test was performed using SwissADME

(www.swissadme.ch/) online tool. This tool predicts all molecular properties i.e. molecular

(HBA), partition coefficient (Log Po/w), polar surface area (PSA), , and Drug likeness score

(Table 5).

Toxicity Test

After docking identified ligands were further subjected to toxicity tests to identify whether

they possess any carcinogenic, skin sensitizing or hERG blocking properties. Toxicity test

was conducted for each property separately by using these specialized tools: Pred – Skin Web

1.0 (skin sensitizer predictor) and hERG – Pred 4.0 (hERG blockage predictor). Pred-hERG

is a predictive machine learning based QSAR models for prediction of hERG blockage which

contains around 16,932 associated bioactivity records for the hERG K+ channel. The

compound 11, 12 and 14 have the valid MolDock Score (-142.796, -142.336,-147.368

respectively) and Drug Likeness (0.55 with all three compounds) and was selected and

subjected to toxicity test. Compound 14 was found to be most effective as compared to rest

two compound (11 & 12). The strength of interaction in between the ligands and the protein

mostly depends on the number of H-bonds and the binding energy. When the analysing the

hydrogen bond interactions between the compound 14 and amino acids present on the active

site of the receptor protein i.e Ala 293, Leu 294, Thr 160, Leu 10, Val 36, Asp 35, Gly 11,

Arg 290, Thr 51 revealed that there are two hydrogen bonding interaction between them.

From analyzing the docking scores, hydrogen bond interaction data and toxicity test, it is

clearly evident that Compound 14 has the best binding affinity towards receptor protein with

least energy as compared to other ligands and doesn’t possess any toxicity and can be used as

lead compound against Leishmaniasis.

Table 2: Grid Validation of Co-Crystal ligand.

Name MolDock Score RMSD

Table 3: MolDock Score of designed 18 compounds.

Compounds MolDock Score (kcal/mol)

Compound 1 -125.241

Compound 2 -123.22

Compound 3 -124.336

Compound 4 -130.385

Compound 5 -126.12

Compound 6 -131.774

Compound 7 -132.132

Compound 8 -129.136

Compound 9 -136.621

Compound 10 -126.711

Compound 11 -142.796

Compound 12 -142.336

Compound 13 -137.881

Compound 14 -147.368

Compound 15 -136.019

Compound 16 -114.82

Compound 17 -130.523

Compound 18 -126.522

Table 4: Interactions of Co- crystallized ligand and designed 18 compounds.

Compounds Interactions

Co- Crystallized (FAD_B)

Asp 35, Gly 11, Gly 13, Ala 293, Ala 12, Ala 159, Ser 14, Thr 160, Thr 51, Trp 163, Arg 290, Glu 141, Ser 291, Gln 292

Compound 1 Ala 159, Gly 11, Ala 293

Compound 2 Val 34, Gly 11, Thr 160, Ala 293, Glu 141, Gly 127

Compound 3 Val 34, Thr 160, Glu 141

Compound 4 Gly 11, Thr 51, Gly 125, Gly 127, Gln 292

Compound 5 Gly 11, Gly 127,

Compound 6 Gly 11, Gly 127, Trp 163

Compound 7 Gly 127, Val 36, Arg 290, Thr 51, Gly 11, Val 34, Gln 292, Ala 293

Compound 8 Val 36, Arg 290, Gly 127

Compound 9 Arg 290, Gly 127

Compound 10 Gly 127, Arg 138, Glu 141, Gly 11, Asp 35, Thr 160

Compound 11 Gly 11, Arg 290, Gly 127, Ala 293

Compound 13 Ala 293, Gly 127, Phe 126, Thr 160, Asp 35, Ala 159, Thr 51, Arg 290

Compound 14 Ala 293, Leu 294, Thr 160, Leu 10, Val 36, Asp 35, Gly 11, Arg 290, Thr 51

Compound 15 Gln 292, Thr 160, Leu 10, Val 36, Gly 11, Asp 35, Ser 162, Thr 51, Asp 290, Gly 125, Val 34

Compound 16 Ala 293, Gly 127, Phe 126, Arg 290, Gly 50, Gly 13, Ala 159

Compound 17 Gly 127, Phe 126, Trp 163, Gly 13

Compound 18 Gly 50, Ala 159, Gly 11, Gly 127, Phe 126, Ala 293

Table 5: Results of potent compounds after analysing through docking.

Compounds MolDock Score

(kcal/mol) Interactions

Co- Crystal ligand

[00] FAD_1490 [B] -141.115

Asp 35, Gly 11, Gly 13, Ala 293, Ala 12, Ala 159, Ser 14, Thr 160, Thr 51, Trp 163, Pro 43, Arg 290, Glu 141, Ser 291, Gln 292

Compound 14 -147.368 Ala 293, Leu 294, Thr 160, Leu 10, Val 36, Asp 35, Gly 11, Arg 290, Thr 51

Compound 11 -142.796 Gly 11, Arg 290, Gly 127, Ala 293

Compound 12 -142.336 Ala 159, Gly 13, Arg 290, Gly 127, Gly 125, Phe 126, Ala 293, Thr 160

Table 6: ADME and Drug Likeness properties of potent antileishmanial compounds.

Parameters Compound 11 Compound 12 Compound 14

Formula C18H18O4 C19H15ClO4 C19H19N3O5

Molecular Weight 298.33 g/mol 342.77 g/mol 369.37 g/mol

No. of rotatable bonds 6 5 5

No. of H-bond acceptors 4 4 6

No. of H-bond donors 0 0 1

Molar Refractivity 83.58 93.47 105.21

TPSA 48.67Å 56.51Å 88.16Å

Lipophilicity (Log Po/w) 2.99 3.98 1.97

Solubility (Log S) -3.17 (Soluble) -4.71 (Moderately Soluble) -3.84 (Soluble) Drug Likeness

(Bioavailability Score) 0.55 0.55 0.55

Figure 2: (A) PDB 2JK6; chain A magneta colour and chain B blue colour both depicts

the active site with red encircled; (B) Showing best pose of co crystal ligand [00]

FAD_1490 [B] of RMSD 0.561.

Figure 3: (A) Interactions of co crystal ligand; H-Bond (Blue), Electrostatic (Green),

Steric (Red); (B) Showing interactions of potent compound 14.

Figure 4: (A) The computational simulated model of hERG – ligand interaction for

compound 14; (B) The computational simulated model of murine local lymph node

assay for compound 14.

A

B

A

B

CONCLUSION

As per our understanding from literature review we studied the basic of leishmania parasite

infection disease, its epidemiology, life cycle, currently available marketed drugs and

potential drug targets. We selected as trypanothione reductase protein as target of our interest.

From reported papers we sort out several PDBs such as 2JK6, 2WOH, 2X50. From them with

better resolution we targeted PDB- 2JK6. In search of ligands we focused on chromene

derivatives as it having a redox oxidant potential in which it can destabilize parasites during

transformation from promastigote to amstigotes in celluler level. From the reported paper

Rajiv K Verma et al chromene 2 thione analogues. By keeping in concern with those potent

compounds 3b, 3c, 3h reported in that paper. Then we did chemical modifications from that

and finally came with molecular docking studies. From our designed 18 compounds

compound 11, 12, 14 shown potent leishmanial activity through computational approach.

Further we can go for optimization of these three compounds by increasing in bond length or

replacing halogen to –NO2, addition of bis-chromene, naphthyl etc. so we can have better

therapeutic activity.

The enzyme trypanothione reductase plays a vital role in the thiol metabolism and therefore it

is considered one of the most important targeted protein in the life cycle of L. donovani. The

inhibition of this targeted protein with chemotherapeutic drugs found be the best way to treat

Leishmaniasis. The major drawback in the drug discovery and development is the longevity

of the process in lead identification. Virtual screening may act as a vital alternative in lead

identification, thereby speeding up the process involved in drug discovery. In future it may

involve bringing out a cost-effective drug into the commercial market.

ACKNOWLEDGEMENT

We cordially thankful to Birla Institute of Technology & Science, Pilani, Rajasthan, India for

providing us the research facilities.

ABBREVIATIONS USED

TRP: Trypanothione Reductase

ADMET: Adsorption, Distribution, Metabolism, Excretion and Toxicity

MVD: Molegro Virtual Docker

M.Wt: Molecular weight

PSA: Polar Surface Area

QSAR: Quantitative Structure Activity Relationship

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