2021 Volume 12 Issue 2

Molecular Modeling of HEV Core Protein and Active Compounds from Northeast Folk Medicine

 

Nibadita Das, Partha Pratim Kalita, Manash Pratim Sarma*, Minakshi Bhattacharjee


Abstract

The main etiological agent, which is considered to cause acute hepatitis is the Hepatitis E virus. Northeast India has a huge reservoir of medicinal plants for treating jaundice using folk medicine (ITK).  The current study focuses on model 32 sequences of HEV core protein submitted in GenBank (KJ879461-KJ879492) and to evaluate the docking pattern with 10 selected active compounds (Glycyrrhizin, Lignans, Piperine, Wedelolactone, Galactomannan, Zingerone, Cajanin, Catechin, Gallic acid, Vasicinone) which are found in various medicinal plants species. Using Open Babel, the protein sequences, as well as the structures, were first converted to PDB format. The Gene Bank provided these sequences [protein sequence id: AIH14833-AIH14864]. The sequences were analyzed by PROTPARAM for chemical compositions and RaptorX for structure. Finally, PASS was applied for toxicity determination and ADME for screening the safety. The Raptor X and PROTPARAM analysis showed stable protein structures of HEV core protein. The analysis categorically showed the composition of C, H, N, O, and S in the studies sequences in a ratio of 108: 171: 35: 36: 1. However, the best results were found in Bhui-amla (Lignans) with the highest docking score of 6944 against sequence ID AIH14838. Lipinski Rule was carried out for all the active compounds and was found to be excellent. The docking score and minimum energy associated show efficient activity of the studied compounds against HEV protein and generates baseline scientific data on the use of folk medicine and the possibility of their commercial utilization.

Keywords: HEV core protein North East India, Folk medicine, RAMPAGE, PROTPARAM, RaptorX, Rasmol


Introduction

The main etiological agent, which is considered to cause acute hepatitis is the Hepatitis E virus (Narayana et al., 2020; Albureikan, 2020). Annually and worldwide, it was estimated that 20 million cases occur, causing the rates of mortality in pregnant women to reach 28%. Hepatitis E is increasing nowadays. HAV and HEV are constantly present at a high rate among the general public and affect all age groups equally. Globally, it is estimated that 2.3 billion people are infected by Hepatitis E virus (HEV), which is a significant international public health problem (Das, 2014). During the third trimester, high mortality among pregnant women is the significant difference between HEV and other causes of acute viral hepatitis (Smith et al., 2016).

HEV belongs to the family Hepeviridae and genus Orthohepevirus. Four of the species that have been defined are the ones that infect carnivores (Orthohepevirus C), soricomorphs, rodents and birds (Orthohepevirus B), and bats (Orthohepevirus D) (Knowles et al., 2011). The Orthohepevirus A comprises seven genotypes that infect human (HEV 1, 2, 3, 4 & 7), wild boar (HEV-3, 4, 5 & 6), pig (HEV- 3 & 4), deer (HEV-3), rabbit (HEV-3), mongoose (HEV-3), yak (HEV-4) and camel (HEV-7) (Sridhar et al., 2017). Annually, it was estimated that 2 million cases of hepatitis E occur in India alone in comparison with the estimated 1.4 million cases of hepatitis A. There have been consistent epidemiological characters of Hepatitis E since its first reported outbreak in New Delhi. The prevalence was found to be highest in young adults and women were reported to have high mortality rates especially in the third trimester of pregnancy (Smith et al., 2014).

Northeast India is showing a shift in hepatitis A viral seroepidemiology. Adults are affected equally by hepatitis E. Unknown herbal medications and non-ABCE AVH and ALF are very common in this region (Hughes et al., 2010). Major viral causes are constituted by HAV and HEV. Higher Mortality level can be found in females and the young ones that belong to the productive section of the society (Das, 2014; Das et al., 2016). Northeast India has a huge reservoir for treating Jaundice by folk Medicine (ITK). It is important to understand the effectiveness of the active compounds of these traditional medicines and their potential use.

Table 1. List of active compounds against HEV core protein and their source

Sl. No.

Scientific Name

Common name

Active compounds

1

Glycyrrhiza glabra

Liquorice

Glycyrrhizin

2

Phyllanthus niruri

Bhui-amla

Lignans

3

Piper longum

Long pepper

Piperine

4

Trigonella foenum graecum

Fenugreek seeds

Galactomannan

5

Eclipta  alba

Bhringraj

Wedelolactone

6

Cajanus  cajan

Pigeon pea, Arhar

Cajanin

7

Camellia sinensis

Green tea

Catechin

8

Lawsonia inermis

Henna leaf

Gallic acid

9

Justicia adhatoda

Malabur nut

Vasicinone

10

Zingiber officinale

Ginger

Zingerone

We have selected a list of active compounds against HEV core protein and their source as shown in Table 1. Glycyrrhizin is a glycoside obtained from roots and stolon of Liquorice (Glycyrrhiza glabra). It helps the liver to detoxify drugs and is used for the treatment of liver disease. Glycyrrhizin exhibits activities like antihepatotoxic activity (Amagaya et al., 1984; Cosmetic Ingredient Review Expert Panel, 2007) while phyllanthin and hypophyllanthin belong to the lignan (Phyllantus niruri) category and have been shown to possess hepatoprotective and anti-genotoxic activities (Dahanayake et al., 2020). The major plant alkaloid Piperine, which is found in P. longum Linn (Long pepper) has bioavailability enhancing activity for some drugs nutritional and some substances and is known to exhibit a hepatoprotective activity apart from exhibiting a toxic effect against hepatocytes (Panahi et al., 2015; Matsuda et al., 2008; Shukla et al., 2011). Wedelolactone (7-methoxy-5, 11, 12-trihydroxy-coumestan) is a natural plant product, which is primarily synthesized by the members of the Asteraceae family (Ding et al., 2017; Kaushik-Basu et al., 2008). WDL is abundantly found in the plant genus Eclipta (or Bhringaraj). It is an acrid, bitter herb medicine traditionally used extensively for the prevention of liver damage due to alcohol overdose and jaundice and for hair and skin health (Singh et al., 2001; Patel et al., 2008; Roy et al., 2008). Also, in India, it was also used for the treatment of infective hepatitis (Singh et al., 2001; Patel et al., 2008; Roy et al., 2008). Cajanus cajan is a perennial member of the family Fabaceae with the presence of two globulins, cajanin, and concajanin (Zu et al., 2010). It has been used widely for many years for treating dysentery, sores, skin irritations, measles, jaundice, diabetes, hepatitis and many other illnesses; for expelling bladder stones and stabilizing menstrual period (Zu et al., 2010). Likewise, the rare risk of hepatotoxicity in a few individuals have been associated with Catechins of green tea extract (Teschke et al., 2014). On the other hand, in many regions, Lawsonia inermis (Henna) is a shrub or small tree cultivated as commercial dye crop and an ornamental (Muthumani et al., 2010) is as astringent, hypertensive, jaundice, and against a headache, sedative, and leprosy (Muthumani et al., 2010; Saadabi, 2007). Vasicinone was isolated from the leaves of Justicia adhatoda and its crude extract has been reported to have hepatoprotective activity (Sarkar et al., 2014)The major pungent compounds in Zingiber officinale (Ginger) of rhizome extract consists of potentially active gingerols, which can be converted to shogaols, zingerone, and paradol (Govindarajan and Connell, 1983; Jolad et al., 2004). Lastly, hepatoprotective activity were noticed in the Seeds of fenugreek, which were annual herbs (Kaviarasan et al., 2007).

In the discovery of new mechanism-or structure-based drugs, drug design assisted by computer have allowed many success stories by new molecular modeling approaches, which are driven by these fast-developing computational platforms (De Ruyck et al., 2016). Molecular modeling tools are extensively used in drug designing. These tools consider 3D molecular structures and their relevant physicochemical properties. The research work aimed to investigate the efficacy of the prevalent medicines against the HEV virus using CADD(www.bioinfo3d.cs.tau.ac.il) (Computer-aided drug designing and to comment on the promising compound of NE folk for future use.

Materials and Methods      

Retrieving the Gene bank HEV Sequences

A total of 32 HEV sequences which were submitted by the author of this manuscript [KJ879461-92[1]] were converted into FASTA and the protein sequences were converted into PDB format using open babel.

Selection of active compounds

A total of 10 active compounds were selected which are present in the folk medicine used to treat jaundice in North East India and whose source parts are abundant in nature. The 2D structures of these active compounds were retrieved in SDF form using NCBI and were further converted mol2, mol, and pdb format.

Structure prediction

RaptorX was carried out for predicting the structures of HEV protein sequences. Protparam was done for computing the physical and chemical parameters of these protein sequences.[2]

3D structure analysis

RASMOL was used for visualization of 3D structures of the studied protein. Using Rampage, to understand the stability of these proteins, Further Ramachandran plots were accessed.[3]

Molecular Docking

Molecular docking was carried out by the PATCHDOCK server where the PDB format of protein sequences and selected active compounds was taken.

Toxicity test

PASS (Prediction of activity spectra for substances) was carried out for prediction of toxicity of selected active compounds while ADME for screening the safety of the selected active compounds (active compounds were in mol format). 

Potentiality as Drug

Lipinski Rule of 5 was done to evaluate drug-likeness. Results were displayed using RASMOL.

Results and Discussion

Table 2. Docking Profile of All the Active Compounds (De Ruyck et al., 2016)

Common name

Scientific name

Active compounds

Protein ID

Best score

Liquorice

Glycyrrhiza glabra

Glycyrrhizin

AIH14839

5464

Bhui-amla

Phyllanthus niruri

Lignans

AIH14838

6944

Long pepper

Piper longum

Piperine

AIH14839

5606

Fenugreek seeds

Trigonella foenum graecum

Galactomannan

AIH14834

3170

Bhringraj

Eclipta  alba

Wedelolactone

AIH14839

6728

Pigeon pea, Arhar

Cajanus  cajan

Cajanin

AIH14846

6756

Green tea

Camellia sinensis

Catechin

AIH14853

5388

Henna leaf

Lawsonia inermis

Gallic acid

AIH14842

2290

Malabur nut

Justicia adhatoda

Vasicinone

AIH14863

6132

Ginger

Zingiber officinale

Zingerone

AIH14839

3368

 

Table 2 shows the best result found from molecular docking of the active compounds against the proteins sequence which were collected from Gene Bank carried out using Patch DOCK. The best result was seen in Bhui-amla (Lignans) with the highest docking score of 6944. A table of docking profile of Bhui-amla against all the protein sequences is given in Table 3.

 

 

 

Table 3. Docking Profile of Lignans (Bhui-amla) against Studied Proteins

Sl No.

Protein   Id

Receptor

Score

Area

Ace

Transformation

1.

AIH14833

302746

5648

739.80

-32.25

-2.53 -0.19 0.51 2.61 -9.79 36.36

2.

AIH14834

302747

5530

703.00

-210.62

2.43 -0.00 -3.07 15.51 -5.29 -6.45

3.

AIH14835

302748

5146

578.70

-123.17

1.69 -0.09 -2.36 21.35 8.25 4.24

4.

AIH14836

302749

5562

709.00

-113.13

1.61 0.96 0.81 -11.85 6.03 3.89

5.

AIH14837

302752

6108

825.90

-260.98

1.31 0.71 -3.01 12.88 1.16 -9.33

6.

AIH14838

302753

6944

831.50

-114.26

-1.99 -0.31 -1.46 -6.10 9.99 2.38

7.

AIH14839

302754

6340

884.60

-333.88

1.63 0.30 1.22 0.59 -4.97 20.89

8.

AIH14840

302810

5186

744.10

-74.80

-0.36 -0.46 -1.76 -7.58 12.69 9.78

9.

AIH14841

303094

5820

759.60

-45.67

-2.54 1.39 -1.38 -3.86 10.31 11.80

10.

AIH14842

303095

6260

838.30

-251.68

1.67 1.29 -2.98 10.70 -19.85 6.95

11.

AIH14843

303096

6236

766.60

-171.93

-1.12 -0.40 -2.98 2.93 1.19 11.87

12.

AIH14844

303097

5360

695.80

-148.29

0.21 1.34 -2.27 2.43 -9.77 1.37

13.

AIH14845

303098

5614

836.40

-240.54

0.72 0.41 -1.83 13.59 12.30 29.08

14.

AIH14846

303100

6034

793.40

-152.09

-0.53 -0.79 -3.11 14.23 8.76 9.75

15.

AIH14847

303101

4840

570.80

-168.84

0.62 0.79 0.65 12.37 7.51 0.43

16.

AIH14848

303102

5564

689.20

-188.51

2.96 -0.71 -0.79 8.17 9.54 43.99

17.

AIH14849

303106

5624

746.40

-243.42

1.41 0.80 -1.23 5.66 11.82 34.67

18.

AIH14850

303107

5210

670.80

-180.86

0.65 0.59 -0.64 -6.50 21.27 -0.89

19.

AIH14851

303108

4958

652.90

-51.76

0.35 0.62 -1.71 6.08 -15.28 -0.49

20.

AIH14852

303110

5544

654.50

-121.53

2.24 1.25 -0.14 -10.61 21.53 23.16

21.

AIH14853

303153

5598

639.00

-158.99

-1.88 1.27 -0.07 -6.88 -21.86 9.13

22.

AIH14854

303157

6196

800.20

-229.59

-1.45 1.25 2.91 -0.43 7.45 27.75

23.

AIH14855

303160

4726

546.40

-202.31

2.90 -0.40 2.00 0.73 -3.79 38.21

24.

AIH14856

303163

5602

738.10

-229.32

0.21 -1.30 -0.64 -11.11 16.05 8.81

25.

AIH14857

303166

5090

653.10

-202.47

-2.31 0.06 2.94 22.03 5.18 20.97

26.

AIH14858

303167

6626

846.50

-233.11

-1.88 -0.85 -1.38 -5.79 14.16 20.40

27.

AIH14859

303168

5636

741.80

-176.59

-0.76 -0.35 1.99 30.32 -6.17 23.72

28.

AIH14860

303169

5314

701.60

-2.43

-1.09 0.23 0.84 9.69 -16.01 16.19

29.

AIH14861

303170

5504

683.00

-186.13

2.75 -0.78 0.97 3.92 7.25 10.50

30.

AIH14862

303172

4748

560.90

-44.75

-0.41 0.16 -1.06 -6.56 13.97 3.68

31.

AIH14863

303173

6240

755.00

-232.47

0.03 0.04 -1.59 8.30 9.47 6.44

32.

AIH14864

303174

5028

656.70

14.03

1.55 1.18 -0.09 0.77 12.54 10.46

 

Without close homolog’s in the Protein Data Bank (PDB), raptorx is a protein structure prediction server developed by the Xu group, which excels at predicting 3D structures for protein sequences[4]. Raptorx helps in the structural prediction of the protein sequences which is been retrieved from Gene Bank under accession number KJ879461-92. There are 32 sequences present and a single representative structure has been represented in Figure 1.

 

Figure 1. A representative protein structure found by RaptorX (AIH14833)

 

The Ramachandran plotswere constructed for each protein sequence. For a clear view, one of the Ramachandran plots has been displayed in Figure 2.

 

 

 

Figure 2. Ramachandran Plot for a given protein sequence(AIH14838)

 

 

The figure shows that the red regions correspond with conformations. These are the allowed regions, where there are no steric clashes like the alpha-helical and beta-sheet conformations. The yellow areas show the allowed regions if slightly shorter Van der Waals radii are used in the calculation, i.e. the atoms are allowed to come a little closer together. This brings out an additional region that corresponds to the left-handed alpha-helix[5].

RasMol is a computer program written for molecular graphics visualization. It is mainly used to explore  and depict biological macromolecule structures, such as those found in the Protein Data Bank[6]. RASMOL was used to visualize all the results as well as all the structure of all the protein sequences.

Table 4. Result of Lipinski Rule for All the Active Compounds

Compound

Mass

HBD

HBA

cLOGP

Molar Refractivity

Glycyrrhizin

912.000000

0

0

0.000000

0.000000

Lignans

912.000000

0

0

0.000000

0.000000

Piperine

342.000000

0

3

9.319986

139.000488

Galactomannan

576.000000

0

0

0.000000

0.000000

Wedelolactone

364.000000

10

7

6.725702

116.919746

Cajanin

364.000000

7

6

8.785706

135.272186

Catechin

342.000000

5

6

6.780993

123.389862

Gallic acid

202.000000

4

5

3.909029

68.664085

Vasicinone

242.000000

9

2

3.086290

82.836876

Zingerone

230.000000

4

3

5.821792

93.607079

Drug-like and non-drug like molecules can be differentiated by Lipinski Rule of 5. It predicts a high probability of success or failure due to drug-likeness for molecules[7]. Lipinski Rule was carried out for all the active compounds. The results are given in Table 4.

Prot Param is a tool that computes the various chemical and physical parameters for a given protein sequence which is given by the user. The parameters which are computed include the extinction coefficient, atomic composition, theoretical PI, molecular weight, amino acid composition, have estimated half-life, instability index, aliphatic index, and grand average of hydropathicity (Table 5)[8].

 

Table 5. Shows composition of different elements in the studied sequence (physical and chemical parameters for a given protein sequences)

Results of ADMET OF LIGNANS (Phyllanthus niruri)

ID

Value

BBB

0.0100522

Buffer_solubility_mg_L

18.8721

Caco2

26.8396

CYP_2C19_inhibition

Inhibitor

CYP_2C9_inhibition

Inhibitor

CYP_2D6_inhibition

Non

CYP_2D6_substrate

Non

CYP_3A4_inhibition

Inhibitor

CYP_3A4_substrate

Substrate

HIA

97.099394

MDCK

14.3364

Pgp_inhibition

Inhibitor

Plasma_Protein_Binding

76.666659

Pure_water_solubility_mg_L

9.94881

Skin_Permeability

-4.24331

SKlogD_value

1.740200

SKlogP_value

1.740200

SKlogS_buffer

-4.341610

SKlogS_pure

-4.619660

ADME was carried out for each active compound to check their skin permeability, buffer solubility, plasma protein binding, and pure water solubility, etc [9].

Rasmol  is a computer program for molecular graphics visualization. It is mainly used to explore and depict biological macromolecule structures, such as those found in the Protein Data Bank[10]. RASMOL was used to visualize all the results as well as all the structures of all the active compounds and protein sequences.

This method which has been adopted in the current study has been tried and tested for identifying active compounds for the treatment of jaundice. A study has got similarity with a study carried out by Xia et al., 2011 where that target protein was HEV ORF2 protein. The procedure in their study mainly focuses on homology modeling and molecular docking. Also, the calculation of the binding domain and details of energy involved along with the configuration of hydrogen bonds are similar to our study (Xing et al., 2011).

In a study, carried out by You et al., 2014 that they predicted the epitope of 8H3 on E2S by epitope prediction software based on the combined approaches of ZDOCK. The study was to check a specific epitope of HEV E2S (You et al., 2014).

In a study carried out by Xing et al., 2011, where molecular docking of the HEV VLP crystal structure have shown that fab 224 covered three surface loops of the recombinant second open reading frame protein. Also determined the structure of a chimeric HEV VLP (Xing et al., 2011).

In a study, carried out by Quintero-Gil C et al., 2017 that they derived six antiviral peptides from the sequences of porcine Beta-Defensin-2 and bacteriocins Nisin and also generated Subtilosin by using in silico tools to propose new antiviral agents. And also, interactions between the HEV capsid protein and the six new antiviral peptide candidates were evaluated by molecular docking. (Quintero-Gil et al., 2017)

Conclusion

The selected active compounds have hepatoprotective activities of traditional medicinal plants of North-East India for treating jaundice. The present study shows that the docking score and energy associated shows the efficient activity of the studied compounds against HEV protein. Selected proteins were having 108: 171: 35: 36: 1 as the ratio for C, H, N, O, and S. All the selected proteins were rich in Leu (L), Arg (R), Ser(S), Pro (P), Glu (E). Ramachandran Plot refers to the β-sheet of the selected HEV protein. ADME results showed favorable results for the selected active compounds. Toxicity prediction of the selected active compounds was showing antitoxic and hepatoprotective properties. Therefore, in this study, we mainly tried to focus on the traditional herbs present in NE, India. The purpose of the study is to figure out the medicinal properties of the natural products present in the environment. The in silico analysis of these traditional herbs can be also useful. However, the current study finding needs to be validated by AUTODOCK results for carrying out animal model studies and human clinical trials.

Acknowledgments: The authors acknowledge the infrastructure support received from Assam down town University.

Conflict of interest: None

Financial support: None

Ethics statement: None

 

[1] http://www.scfbio-iitd.res.in/software/drugdesign/lipinski.jsp.

[4] www.bioinfo3d.cs.tau.ac.il

[6] www.mordred.bioc.cam.ac.uk

[7] https://sourceforge.net/projects/openrasmol/

[8] http://www.scfbio-iitd.res.in/software/drugdesign/lipinski.jsp

[9] www.web.expasy.org

[10] www.mordred.bioc.cam.ac.uk

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JOURNAL OF BIOCHEMICAL TECHNOLOGY
JOURNAL OF BIOCHEMICAL TECHNOLOGY
Journal of Biochemical Technology is a peer reviewed International Journal published by the Sevas Publishing on behalf of the Biochemical Technology Society, a Registered Charity Organization from India

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AREA OF INTEREST
Areas of high interest, cover new advances in enzymatic and protein mechanims; applied molecular genetics and biotechnology; genomics and proteomics; metabolic; medical, environmental, food and agro biotechnology.

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FOCUS AND SCOPE
Journal Of Biochemical Technology” Provides A Medium For The Rapid Publication Of Full-Length Articles, Mini-Reviews Of New And Emerging Products And Short Communications On All Aspects Of ...

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This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Keywords include, Biochemical Research: Endo/exocytosis, Trafficking, Membrane Biology, Cell Migration, Cell-Matrix Organelle Biogenesis, Cytoskeleton Proteolysis, Cell Death, Cell Cycle, Cancer, Cell Growth/Death, Differentiation, Drug Targets, Gene Therapy, Models of Disease, Proteomics, Stem Cells, Bioenergetics, Mitochondria, Free Radicals, Redox Signaling, Ion Transport/Channels, Oxidative