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 Table of Contents    
RESEARCH ARTICLE
Year : 2021  |  Volume : 53  |  Issue : 6  |  Page : 471-479
 

In silico binding analysis of lutein and rosmarinic acid against envelope domain III protein of dengue virus


1 School of Science, Narsee Monjee Institute of Management Studies, Mumbai, India
2 MIT School of Bioengineering Science and Research, ADT University, Pune, India
3 Department of Virology, Haffkin Institute for Training, Research and Testing, Mumbai, India
4 Department of Microbiology, D. Y. Patil School of Medicine, Navi Mumbai, India

Date of Submission15-Oct-2019
Date of Decision29-Aug-2020
Date of Acceptance11-Nov-2021
Date of Web Publication30-Dec-2021

Correspondence Address:
Dr. Sandeepan Mukherjee
Department of Virology, Haffkin Institute for Training, Research and Testing
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijp.IJP_576_19

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 » Abstract 


OBJECTIVE: The study was performed to evaluate in silico binding ability of lutein and rosmarinic acid (RA) with the envelope domain III (EDIII) proteins of the four serotypes of dengue virus (DENV), enlightening potential antiviral activity of the two compounds.
MATERIALS AND METHODS: EDIII protein structures for the four DENV serotypes were retrieved from RCSB Protein data bank (PDB) and used as receptors. Four ligands of lutein and four of RA were selected from the ZINC database and used for computational molecular docking and ligand interaction analysis with the four receptors using bioinformatics tools like AutoDock Vina and Molecular Operating Environment (MOE) software.
RESULTS: The EDIII of the four serotypes demonstrated significant interaction with ligands of lutein and RA. RA ligand ZINC00899870, particularly presented best binding energy values of -6.4, -7.0, and -6.9 kcal/mol with EDIII of serotype DENV-1, DENV-2, and DENV-4 respectively. Whereas, lutein ligand, ZINC14879959 presented best binding energy value of -7.9 kcal/mol for EDIII of serotype DENV-3. From the results predicted by MOE, the hydroxyl (OH) of 3, 4-dihydroxyphenyl group of RA ligand ZINC00899870 is actively involved in interaction with all four serotypes.
CONCLUSION: RA is a competent candidate for further evaluation of potential in vitro antiviral activity that can be effective in conferring protection against the four serotypes of DENV.


Keywords: Antiviral, dengue virus, lutein, molecular docking, rosmarinic acid


How to cite this article:
Panchal R, Bapat S, Mukherjee S, Chowdhary A. In silico binding analysis of lutein and rosmarinic acid against envelope domain III protein of dengue virus. Indian J Pharmacol 2021;53:471-9

How to cite this URL:
Panchal R, Bapat S, Mukherjee S, Chowdhary A. In silico binding analysis of lutein and rosmarinic acid against envelope domain III protein of dengue virus. Indian J Pharmacol [serial online] 2021 [cited 2022 Jan 25];53:471-9. Available from: https://www.ijp-online.com/text.asp?2021/53/6/471/334357





 » Introduction Top


Dengue is one of the major emerging zoonotic viral infectious diseases prevalent in sub-tropical and tropical countries, characterized by high fever, rash, headache, joint pain among some of its symptoms.[1],[2] Dengue fever is caused by dengue virus (DENV) which has four serotypes DENV-1, DENV-2, DENV-3, and DENV-4 that produce similar clinical presentations being genetically distinct (the four serotypes share 67%–75% homology with each other).[3] The antibodies generated against one serotype will confer lifelong protection against that particular serotype, while may cross react with a different serotype in a subsequent secondary infection. The cross reactivity may result in a phenomenon known as antibody-dependent enhancement (ADE), leading to vigorous immune response which may predispose the individual into fatal manifestations of the disease, dengue hemorrhagic fever, or dengue shock syndrome.[4],[5]

This feature of dengue infection possesses a severe challenge in the development of a potent vaccine which could confer equal protection against all the four serotypes of DENV. We do not have any specific antiviral drug treatment and the vaccine candidates have failed to show respectable proficiency against all the four serotypes.[6] Probable alternative is to identify therapeutic agents, drug molecules which could impede or reduce the virus titer. Most of the antiviral drugs target the viral replication process or assembly or block the viral attachment with the host cells, ceasing its multiplication.[7],[8],[9]

The envelope (E) protein of flaviviruses is the one most widely studied owing to its critical role in recognition and attachment of cognate host cell receptor, penetration, hemagglutination, cell tropism, and virulence.[10] E protein is comprised of three domains that are folded to form a raft like structure in dimeric configuration. Domain 1 forms a central domain connecting domain II containing a fusion loop that mediates membrane fusion and domain III. The DENV envelope domain III (EDIII) protein is recognized to be involved in the host cell adhesion and hence plays a pivotal role in viral infection. EDIII of DENV has always been center of interest owing to the presence of critical epitopes recognized by neutralizing antibodies.[10],[11] The significant role of EDIII in host cell adhesion has also been suggested by antibody neutralization and peptide based studies.[12] Therefore, blocking EDIII could theoretically restrict the virus from receptor recognition and entering the host cell. The drug under consideration should have wide spectrum effect against maximum serotypes of the virus to be considered as a potent anti-Dengue viral drug.

Lutein is a naturally occurring carotenoid known for its immunomodulatory and antioxidant activities.[13],[14] Lutein has previously shown to inhibit the activity of the full-length promoter (Fp) of the hepatitis B virus (HBV). This research indicates that lutein possesses an anti-HBV activity through blocking of HBV transcription.[15] RA is a caffeic acid ester present in diverse plant species and known to exhibit antioxidant and other medicinal properties. RA has gained a lot of attention since it was identified as the primary molecule of lemon balm for its anti-herpes simplex virus (HSV) activity.[16],[17] Furthermore, significant decrease in viral loads and proinflammatory cytokine levels in Japanese encephalitis (JEV) infected murine model suggests its strong therapeutic effects against JEV, a flavivirus, closely related to DENV.[18]

Current study was conducted to assess the in silico binding ability of lutein and RA to the EDIII proteins of the four DENV serotypes, assessing the potential antiviral activity. Using computational molecular docking analysis and ligand interaction study with the four receptors, we determine the related binding energy of interaction between the compounds and the EDIII proteins to illuminate the potential antiviral activity of the two compounds.


 » Materials and Methods Top


Preparation of receptor

The structures for domain proteins of DENV with RCSB Protein Data Bank (PDB) ID: 3IRC, 2JSF, 3VTT and 2H0P corresponding to EDIII of DENV-1, DENV-2, DENV-3, and DENV-4, respectively, were selected based on the literature survey and its availability in the PDB database.[19],[20],[21],[22] The proteins though available in PDB were modelled using structure modelling software PHYRE2 (Protein Homology/analogY Recognition Engine V 2.0). Molecular graphics and analyses were performed using UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco. The structural anomalies were corrected in the side chain and folds and the structures were energy minimized. All further docking studies were performed using the modified structures so obtained, which were saved in .pdb format [Table 1].
Table 1: EDIII proteins of DENV with PDB ID: 3IRC, 2JSF, 3VTT and 2H0P corresponding to DENV-1, DENV-2, DENV-3 and DENV-4, respectively

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Preparation of ligands

The ZINC database by the Irwin and Shoichet Laboratories in the Department of Pharmaceutical Chemistry at the University of California, San Francisco (UCSF) was explored for ligands of lutein and RA, subsequently, four ligands of lutein ZINC40164432, ZINC14879961, ZINC14879959, ZINC08221225 and four ligands of RA ZINC05784598, ZINC13341234, ZINC00899870, and ZINC00901160 were retrieved based on availability in the database. Marvin Sketch software v. 5.10 (M/s. ChemAxon) was used to prepare the selected ligands. The “add hydrogen” and “clean hybridization” options were used for checking the addition of missing hydrogen atoms and fidelity of all bonds, respectively. OpenBabel GUI v 2.3.1, a chemical toolbox designed to convert between various chemical formats was used to interact and convert file formats between different software. Structural modeling was performed on the derived ligand molecules using UCSF chimera tools. The modified structures so obtained were saved in .pdb format and used for all further docking studies [Table 2].
Table 2: Ligands for lutein and RA retrieved from ZINC database

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Prediction of pharmacological property

Ligands were screened with Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) constraints according to Lipinski's rule of five and oral bioavailability to test the theoretical pharmacokinetics and predict the drug-likeness of the ligands.[23] Compounds abiding to 3 or more of the five parameters are considered to be effective drug-like molecules. Using online prediction platform Molsoft L.L.C. (Molecular properties and drug likeliness), molecular descriptors for Lipinski's rule were analyzed for lutein and RA. The software provides a score for each of the five criteria and also provides a drug-likeliness score (between − 1: +1).

Prediction of toxicity

Toxicity predictions were accomplished using the Lazy structure activity relationships (LAZAR) software package (in silico toxicology GMBH). The software detects mutagenic and/or carcinogenic properties of the query molecule on the basis on the similarities in functional groups with mutagenic and/or carcinogenic compounds present in the LAZAR database.[24]

Sequence analysis and structural comparison between envelope domain III of four dengue virus serotypes

Comparative analysis was carried out to ensure the identity and variability between EDIII structures. Sequence comparison was performed using CLUSTALW by European Bioinformatics Institute (EMBL-EBI), which carries out multiple sequence alignment.[25] The conserved regions can be found between sequences using CLUSTALW. Structural comparison was accomplished using PyMOL software by Schrödinger. By using a scheme similar to Dayhoff's amino acid replacement score PyMOL defines the structural resemblance score as log-odds of two probabilities.[26],[27] In the program, structures were crystallized by inputting the PDB code and loading PDB format files on the user's computer. Validated 3D models of domain structures were super imposed with each other. Structural difference is indicated by RMSD (root mean square deviation) value.

Molecular docking

Molecular docking techniques are used to dock ligands into the protein-binding sites.[28],[29] In order to understand how these ligands bind to the receptors, docking studies were performed on EDIII of the four DENV serotypes and eight compounds of lutein and RA (4 for lutein and 4 for RA) by using AutoDock Vina by The Scripps Research Institute and ligand interaction study using Molecular Operating Environment (MOE) software by Chemical Computing Group. The receptor grid was cantered based on active site of protein, using the receptor grid generation tool. Ligands were prepared using AutoDock. The docking method was employed using Monte Carlo based algorithm. These ligands were docked into the active sites of the proteins to predict binding poses for ligands. Default docking parameters were used. Docking algorithm was able to generate numerous possible structures. Conformational expansion of the ligand was systemically done to initiate the docking process. This was then placed in the receptor site. Force-field refinement or energy minimizations of ligands in the field of receptor were carried out using conventional molecular mechanics setup where final energy was calculated. The best conformation for given ligand was established based on the final score.


 » Results Top


Prediction of pharmacological property

From the results obtained from Molsoft L.L.C. software analysis of the ligands [Table 3], it can be predicted that lutein did not follow three parameters of Lipinski's rules, which were, that the molecular weight must be <500 Da, the Log P must be <5 and the refractivity molar range must be between 40 and 130 cm3. Furthermore, the predicted drug likeliness model score was calculated to be -0.33 which is on the lower end of drug-likeliness scale for a compound [Figure 1]. However, RA successfully cleared the Lipinski's rules with a predicted drug-likeliness model score of 0.37 which is at the positive end of drug-likeliness scale for a compound [Figure 2]. Thus, it can be concluded that RA ligands showed higher probability of success for drug-likeness of the two compounds.
Table 3: Pharmacological properties for lutein and RA predicted by Lipinski's rule of five for oral bio-availability using Molsoft L.L.C. software

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Figure 1: Drug-likeliness model score for lutein was predicted using Molsoft L.L.C. software to be −0.33, indicating that lutein may not be a suitable candidate for oral formulation based on bioavailability

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Figure 2: Drug-likeliness model score for RA was predicted using Molsoft L.L.C. software to be 0.37, indicating that RA possesses drug-like properties for oral formulation based on bioavailability. RA=Rosmarinic acid

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Prediction of toxicity

The LAZAR software predicted that all the ligands of lutein and RA are noncarcinogenic and nonmutagenic. Probability of this prediction was >0.025, suggesting that the predictions are reliable [Table 4].
Table 4: Toxicity predictions by lazy structure activity relationships (LAZAR) software for ligands of lutein and RA to detect mutagenic and/or carcinogenic properties based on the similarities in functional group with mutagenic and/or carcinogenic compounds present in the LAZAR database

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Sequence analysis and structural comparison between envelope domain III of four dengue virus serotypes

Multiple sequence alignment using CLUSTALW software revealed conserved regions between EDIII proteins of the four DENV serotypes [Figure 3]. The alignment indicated 75% region of the entire sequence to be highly similar, indicating the active sites of the EDIII proteins to be conserved. The dissimilar regions were toward the terminal ends of the proteins indicating no effect toward the function of the protein. Structural comparison was accomplished using PyMOL software. The superimposed 3D structures of the four DENV EDIII proteins presented overlapping between the beta sheets [Figure 4]. Low RMSD values suggest little deviation between the EDIII of four DENV serotypes [Table 5], indicating highly conserved regions between them. Hence, it can be predicted that the EDIII of the four serotypes share highly conserved regions among them.
Figure 3: Multiple sequence alignment of EDIII proteins of DENV-1, DENV-2, DENV-3 and DENV-4 serotypes using CLUSTALW. The alignment indicates 75% region of the sequence to be highly similar, stipulating the active sites of the four EDIII proteins to be conserved. DENV: Dengue virus, EDIII=Envelope Domain III

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Figure 4: Superimposed 3D structures of EDIII protein of four DENV serotypes (DENV-1, DENV-2, DENV-3 and DENV-4) using PyMOL software. The superimposition demonstrates overlapping between the beta sheets. Also, the low RMSD values calculated by the algorithm suggests very little deviation between the EDIII of four DENV serotypes, indicating highly conserved regions between them. DENV: Dengue virus, EDIII=Envelope Domain III, RMSD=Root Mean Square Deviation

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Table 5: RMSD values calculated for structural superimposition of secondary structures of envelope EDIII proteins of four DENV serotypes predicted by PyMOL software

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Docking analysis

The docking result of EDIII receptors (3IRC, 2JSF, 3VTT, and 2H0P) and 8 ligands of lutein and RA (4 for lutein and 4 for RA) using AutoDock Vina arranged ligands based on energy in increasing order. The analyzed results suggest that EDIII of all four serotypes showed significant interaction with ligands of lutein and RA. RA ligand ZINC00899870 demonstrated best-binding energy values with DENV-1, DENV-2, and DENV-4 receptors. The docking scores for DENV-1, DENV-2, and DENV-4 were -6.4, -7.0, and -6.9 kcal/mol, respectively [Table 6]. Whereas, lutein ligand ZINC14879959 showed best binding energy value of -7.9 kcal/mol for EDIII of serotype DENV-3 [Table 7]. Even though the overall docking score was good for lutein ligands, the top 3 docking scores were observed for RA ligand, suggesting RA has better conformation to bind to all four DENV-EDIII proteins. MOE predicted the RA ligands interaction sites for the proteins. The hydroxyl group of RA ligand ZINC00899870 is predicted to forms a hydrogen bond with Glut16 of receptor 3IRC (DENV-1). Also, a π-π interaction is observed with Lys15 residue of receptor and the ligand [Figure 5]a and [Figure 5]b. Residues of receptor 2JSF (DENV-2) Phe49, Glu50, and Asn67 form a hydrogen bond with the hydroxyl group of the RA ligand ZINC00899870 [Figure 6]a and [Figure 6]b. The hydroxyl group of lutein ZINC14879959 ligand interacts with hydrogen of Gly153 of receptor 3VTT (DENV-3) [Figure 7]a and [Figure 7]b with a bond distance of 1.62 Å, indicating strong bonding. For receptor 2H0P (DENV-4) protein, the oxygen of RA ligand ZINC00899870 interacted with Met13 residue of receptor and the hydrogen group of ligand interacts with Ile49 residue of receptor at bond distance of 1.58 Å [Figure 8]a and [Figure 8]b. The above results suggest that hydroxyl group of the ligands plays an important role in their interaction to the proteins. The docking regions being conserved as was observed in the multiple sequence alignment, stipulates the low difference in the docking scores. These results suggest that the above compounds bind and interact within the domains of the active site of the receptor.
Table 6: Binding energy fitness score for docking interactions of lutein ligands with EDIII receptors of four DENV serotypes predicted by AutoDock Vina molecular docking software

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Table 7: Binding energy fitness score for docking interactions of RA ligands with EDIII receptors of four DENV serotypes predicted by AutoDock Vina molecular docking software

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Figure 5: (a) Ball and stick illustration for molecular interaction of receptor 3IRC (EDIII DENV-1) with RA ligand ZINC00899870, as predicted by MOE software. (b) 2D illustration for molecular interaction of receptor 3IRC (EDIII DENV-1) with RA ligand ZINC00899870, as predicted by MOE software. The hydroxyl group of ligand and Glut16 of receptor form a hydrogen bond, also, a pi-pi interaction is observed between the ligand and Lys15 residue of receptor. DENV: Dengue virus, EDIII=Envelope Domain III, RA=Rosmarinic acid, MOE=Molecular Operating Environment

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Figure 6: (a) Ball and stick illustration for molecular interaction of receptor 2JSF (EDIII DENV-2) with RA ligand, ZINC00899870 as predicted by MOE software. (b) 2D illustration for molecular interaction of receptor 2JSF (EDIII DENV-2) with RA ligand ZINC00899870, as predicted by MOE software. Residues Phe49, Glu50, and Asn67 of receptor form a hydrogen bond with the hydroxyl group of the RA ligand. DENV: Dengue virus, EDIII=Envelope Domain III, RA=Rosmarinic acid, MOE=Molecular Operating Environment

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Figure 7: (a) Ball and stick illustration for molecular interaction of receptor 3VTT (EDIII DENV-3) with lutein ligand, ZINC14879959 as predicted by MOE software. (b) 2D illustration for molecular interaction of receptor 3VTT (EDIII DENV-3) with lutein ligand ZINC14879959 as predicted by MOE software. The hydroxyl group of ligand is predicted to interact with the hydrogen of Gly153 of receptor. DENV: Dengue virus, EDIII=Envelope Domain III, MOE=Molecular Operating Environment

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Figure 8: (a) Ball and stick illustration for molecular interaction of receptor 2H0P (EDIII DENV-4) with RA ligand ZINC00899870 as predicted by MOE software. (b) 2D illustration for molecular interaction of receptor 2H0P (EDIII DENV-4) with RA ligand ZINC00899870 as predicted by MOE software. The oxygen of ligand interacted with Met13 residue of the receptor and the hydrogen group of ligand interacts with Ile49 residue of receptor at a bond distance of 1.58 Å. DENV: Dengue virus, EDIII=Envelope Domain III, RA=Rosmarinic acid, MOE=Molecular Operating Environment

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 » Discussion Top


Over the years, dengue has remained as one of the most cumbersome diseases having four serotypes which are genetically and antigenically distant.[11] Furthermore, a secondary infection with another serotype may generate cross-reactive antibodies leading to a phenomenon known as ADE, further enhancing the severity of the infection.[4],[5] These features possess inimitable challenges for the development of vaccine and therapeutic drug molecules, as the candidate must confer protection against all the four serotypes of the virus equally, failing to do so may lead to further complications.[6] Developing a chemotherapeutic agent that can act against all the serotypes is therefore imperative. EDIII of DENV and other flaviviruses are known to be involved in the receptor recognition and entry into the target host cell.[10] Therefore, blocking EDIII could theoretically restrict the virus from receptor recognition, thereby limiting viral propagation. With the advent of technology and development of enhanced bioinformatics tools, it has become feasible to screen the large number of potential compounds against a particular protein target by docking the active site of the target protein in less time.[28],[29] In this study, we have evaluated two phytochemical compounds, lutein and RA for potential inhibitory activity by virtue of being able to prevent the EDIII protein interaction with cognate host cell receptor by binding to and physically blocking the active site of EDIII of four DENV serotypes. Lutein and RA both are well known and established for their immunomodulatory and antioxidant properties. They have also demonstrated antiviral activities in the past. Lutein has previously shown to inhibit the activity of HBV, whereas, RA has been identified to possess antiviral activity against HSV, enterovirus A71 and JEV which is closely related to DENV.

The structures of EDIII proteins of DENV retrieved from PDB with PDB ID: 3IRC, 2JSF, 3VTT and 2H0P corresponding to EDIII of DENV-1, DENV-2, DENV-3, and DENV-4, respectively, were selected based on the literature survey and its availability in the database. Yeturu and Rao used the PDB ID 3IRC for DENV-1 to demonstrate the possible antiviral activity of Neem on DENV. Similarly, the PDB ID 2JSF for EDIII DENV-2 was explored by Isa DM, Chin et al. to study binding interactions of two synthetic antiviral peptides (DET2 and DET4). Possible molecular mechanisms for recognition of serospecific antibodies are suggested by the high-resolution crystal structure PDB ID 3VTT of EDIII DENV-3 derived by Montasir Elahi, Monirul M. Islam et al. Stereochemical features of the EDIII of DENV-4 were studied for putative antigenic site on PDB ID 2H0P by Soares RO, Caliri A.

The 3D structures of the proteins though available in PDB were modelled by PHYRE2, a protein visualization tool. The structure was energy minimized using the UCSF Chimera tool after structural inconsistencies in the side chain and folds were corrected. It is well established by several studies that the four serotypes of dengue share about 65%–70% nucleotide sequence homology with first reports by Rico-Hesse dating back in 1990 (Rico-Hesse 1990). However, we were unable to encounter any study that compared the sequence and structural homology between the EDIII proteins of the four serotypes. This is especially important to identify the conserved regions between the four EDIII proteins and identify the active site pockets for the development of therapeutic agents that can target all the four EDIII proteins. Sequence analysis and structural comparison between EDIII of four serotypes using CLUSTALW software and PyMOL software, respectively, demonstrated that the four serotypes possess considerable similarity between them, indicating around 75% of conserved regions. The dissimilar regions were observed toward the terminal regions of the proteins indicating no effect toward the function of the protein. Furthermore, very little deviation was observed between the 3D structures of EDIII of four serotypes, especially between the rigid beta sheets which overlapped with each other indicating high similarity between them.

Four ligands for RA and four for lutein were obtained from ZINC database based on the availability in database. Prediction of the pharmacological properties of the compound under consideration is necessary to consider them as oral drugs. Although both lutein and RA are traditionally used as supplements, immune modulators, antioxidants, and also as therapeutics, it was necessary to evaluate their ADMET properties to be employed as an oral formulation. The ligands were screened for pharmacological properties using Lipinski's rule of five and oral bioavailability, using a software package Molsoft L.L.C. It was predicted that lutein ligands did not clear few parameters of the Lipinski's filter, whereas, RA ligands cleared the filter test successfully. Hence, it can be concluded that RA is a suitable therapeutic candidate. A major prerequisite for an antiviral drug candidate is the safety evaluation. Hence, both the ligands were tested for mutagenic and/or noncarcinogenic properties using LAZAR database and established to be noncarcinogenic.

Using computational molecular docking analysis and ligand interaction study with the four receptors, we determined the related binding energy of interaction between the EDIII of the four DENV serotypes and eight compounds of lutein and RA (4 for lutein and 4 for RA) by AutoDock Vina and ligand interaction study using MOE software.

RA ligand ZINC00899870 established wide spectrum effect demonstrating significant binding ability with a low-binding energy against all serotypes of DENV, being most effective against DENV-1, DENV-2, and DENV-4 in the increasing order of magnitude. On the other hand, lutein was most effective in binding ability having very low binding energy with DENV-3. RA established superior binding dynamics against all four serotypes. From the results predicted by MOE, hydroxyl group of the ligands plays an important role in the interaction of the ligands to the proteins. The docking regions being conserved as was observed in the multiple sequence alignment indicate the low difference in the docking scores. With the evidence of the findings, hydroxyl (OH) of 3, 4-dihydroxyphenyl group of RA ligand ZINC00899870 is actively involved in the binding with all the four DENV serotypes. Therefore, 3, 4-dihydroxyphenyl can be further investigated as a potential pharmacophore in the discovery of antiviral chemotherapeutic agents against DENV across all the four serotypes. These results point at a possibility that RA may have an important role in attaching within the active site of the EDIII receptors which share a common active binding site.

RA, which has also exhibited antioxidant properties and reported antiviral effect, can be investigated as a potential wide spectrum antiviral agent against dengue infection. The findings pave way for the design of novel antiviral compounds in future.

Further in vitro and in vivo studies with antiviral effect of the two compounds separately and in combination are required to support the in silico findings. However, the present work is an initial but important step toward understanding the potential mechanisms of ligands for EDIII of DENV serotypes. Further cell-free and cell-based in vitro and animal studies (in vivo) are needed to validate these results.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 4]



 

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