Flavonoids as Multi-target Inhibitors for Proteins Associated with Ebola Virus: In Silico Discovery Using Virtual Screening and Molecular Docking Studies

Original Research Article

DOI: 10.1007/s12539-015-0109-8

Cite this article as:
Raj, U. & Varadwaj, P.K. Interdiscip Sci Comput Life Sci (2016) 8: 132. doi:10.1007/s12539-015-0109-8

Abstract

Ebola virus is a single-stranded, negative-sense RNA virus that causes severe hemorrhagic fever in humans and non-human primates. This virus is unreceptive to a large portion of the known antiviral drugs, and there is no valid treatment as on date for disease created by this pathogen. Looking into its ability to create a pandemic scenario across globe, there is an utmost need for new drugs and therapy to combat this life-threatening infection. The current study deals with the evaluation of the inhibitory activity of flavonoids against the four selected Ebola virus receptor proteins, using in silico studies. The viral proteins VP40, VP35, VP30 and VP24 were docked with small molecules obtained from flavonoid class and its derivatives and evaluated on the basis of energetics, stereochemical considerations and pharmacokinetic properties to identify potential lead compounds. The results showed that both top-ranking screened flavonoids, i.e., Gossypetin and Taxifolin, showed better docking scores and binding energies in all the EBOV receptors when compared to those of the reported compound. All the screened flavonoids have known antiviral activity, acceptable pharmacokinetic properties and are being used on human and thus can be taken as anti-Ebola therapy without the time lag for clinical trial.

Keywords

Ebola virus Docking Virtual screening Flavonoids Pharmacokinetic Gossypetin Taxifolin 

1 Introduction

The Ebola outbreak in 2014 is one of the largest viral outbreaks in history and the first in West Africa. Although currently it is affecting four countries in West Africa, namely Guinea, Liberia, Nigeria and Sierra Leone, according to the recent reports of the Centre for Disease Prevention and Control (http://www.cdc.gov/vhf/ebola/), it is spreading across globe as a potential pandemic scenario. Ebola virus (EBOV) is a deadly pathogenic virus which is classified under filoviridea family. It was initially reported in Africa in 1976 in democratic republic of Congo [1, 2]. Severe and often fatal hemorrhagic fever is the significant symptom of Ebola infection which happens in two stages: incubation period and late stage. Incubation period shows indications like joint pain, fever, weakness, sickness which can keep going for one week, and late side effects incorporate sorrow, eye irritation and hemorrhagic rash over the whole body [3, 4].

EBOV has thread-like tubular filaments which are encapsulated with viral envelope [5, 6]. It has a negative-stranded genome which contains seven structural genes, of which four structural proteins and three membrane-associated proteins are encoded by EBOV genome [7, 8, 9] (Fig. 1).
Fig. 1

Ebola viral genome arrangement [10]

As such there is no drug or vaccine available as of now for the treatment of EBOV infection (http://www.physorg.com/news134840607.html). EBOV encodes seven polypeptides from its RNA genome of ca. 19.0 kb, including glycoprotein (GP), nucleoprotein (NP), RNA-dependent RNA polymerase (L), VP35, VP30, VP40 and VP24 [10, 11]. Out of these proteins, we have focussed on VP40, VP35, VP24 and VP30 proteins as the potential drug targets looking into the function of these proteins to cause protective immune responses to EBOV.

The most abundant protein located under the viral bilayer is VP40, and it is required to make the structural integrity of the viral particles. The assembly and budding process of the matrix protein VP40 occurs at the plasma membrane and requires lipid raft microdomains [12]. During its replication, it also plays an important role either in the RNA metabolism of viral or in the host cell [13]. The EBOV VP40 comprises of the N-terminal and C-terminal domains which are linked together by a flexible linker made up of residues ranging from 195 to 200. The N-terminal domain is folded into a \(\beta\)-sandwich comprising six antiparallel strands arranged in two \(\beta\)-sheets of three strands each. This along with the C-terminal domain forms the monomer of VP40 receptor. The C-terminal domain of VP40 acts as a potential drug target due to its role in membrane association [14], whereas the N-terminal domain is responsible for the oligomerization of the protein. The C-terminal domain comprises of a conserved proline-rich region in VP40 EBOV receptor ranging from amino acids 205–219 which is responsible for interaction with cellular Sec24C and also essential for plasma membrane targeting and viral particle release [15].

The Ebola VP35 protein is a crucial protein which acts as component of the viral RNA polymerase complex, viral assembly factor. It hampers the host interferon (IFN) production, hence is vital for virulence of EBOV. Further, the mutation of selected residues within the C-terminal of VP35 impairs its dsRNA-binding activity. It has been reported that the dsRNA-binding cluster which is centered on Arg-312 is a highly conserved residue which is crucial for EBOV virulence [16]. Knockdown of VP35 leads to reduced viral amplification and reduced lethality in infected mice [17]. Therefore, VP35 is a crucial drug target due to its role in viral replication and pathogenesis.

Similarly, the structural protein VP24 of EBOV has proven to be antagonizing the host IFN function. It had also been established that in a mice model, this role could depend on the ability of VP24 to counter the IFN system [18]. There is likewise confirming that this protein can influence the transcription and replication of an EBOV minigenome [18, 19] and, when transitorily expressed together with NP and Vp35, is included in the framing of viral nucleocapsids [20, 21, 22].

VP30 is crucial for the formation of the viral mRNAs even though it has been reported that EBOV transcription could occur solely if the NP get changed, triggering the incorporation of the transcription initiation site [9, 23]. It has been hence conjectured that VP30 may help to beat this obstruction for transcriptional enactment and steady with its proposed part at an early phase of interpretation. VP30 due to its role in homo-oligomerization is considered as a potential target for antiviral treatment [5].

Structure-based drug designing approaches involves the 3D structure of protein on which docking studies of various individual small molecules have been carried in order to calculate their docking score and binding energy by utilizing a series of scoring functions. The virtual screening and molecular docking of the drug candidates on target protein could find out the best lead like compounds with further optimization of the compounds to finalize the lead [24].

According to latest reports, ZMapp, optimized combination of drug contains monoclonal antibodies made from a tobacco-plant strain can act as antiviral therapy against Ebola infection [25]. ZMapp is a cocktail combining the best components of two treatments, namely MB-003 (Mapp) and ZMAb (Defyrus/PHAC), and is produced in a laboratory by exposing mice to fragments of the virus. But it does not get the FDA approval yet. As of now, only two cases have been reported stating that ZMapp has been effective in treating Ebola, while studies have shown that only 43% of animals affected with the EBOV have been cured by ZMapp even though it is yet to be tested on human [25].

Also another drug BCX4430 (Developed by BioCryst), a new synthetic adenosine analog, inhibits infection of different filoviruses in human cells [26]. Biochemical, reporter-based and primer-extension assays indicate that BCX4430 inhibits viral RNA polymerase function, acting as a non-obligate RNA chain terminator. Post-exposure intramuscular administration of BCX4430 protects against EBOV and Marburg virus disease in rodent models, but it is not tested in humans yet.

It is a well-known fact that flavonoid groups of natural chemotypes act as a good example of “natural fit” holding leading performance in range of antiviral, antibacterial, anti-inflammatory, anticancer, antioxidant activities [27, 28, 29]. Flavonoids have low toxicity and are widely available in plants, including edible.

The stereochemistry of binding of the flavonoids on EBOV receptor has not yet been characterized. In this study, we selected flavonoids as inhibitors for VP40, VP35, VP24 and VP30 viral protein receptors along with the reported inhibitors. Further, we made a comparative analysis of the efficacy of these flavonoids versus all the reported drugs against these said above receptors and inferred that the screened flavonoids could act as better inhibitors than the existing reported drugs.

2 Materials and Methods

All computational analysis was carried out on a Red Hat 10.2 Linux platform running on a Dell PC with an Intel Core i7 processor and 12 GB of RAM.

2.1 Protein Structure

The X-ray crystal structure of the matrix protein VP40 at 1.60 Å resolution (PDB ID: 1H2C), VP35 at 1.40 Å resolution (PDB ID: 3FKE), VP30 at 2.00 Å resolution (PDB ID: 2I8B) and VP24 at 1.92 Å resolution (PDB ID: 4M0Q) was retrieved from Protein Data Bank [30]. Processing of protein structures was carried out by “Protein preparation wizard” of Maestro, version 9.7, Schrödinger, LLC, New York, NY, 2014 [31]. Before protein preparation process, all the water molecules and heteromolecule attached with the structures, i.e., RNA ,were removed from the original crystal structure of VP40. Hydrogen atoms were added, and the geometry of all the heterogroups was corrected. For optimizing the network of H-bonds, hydrogen bond assignment tool was implemented. The minimization of energy was carried out by utilizing in-built constraint of RMSD: 0.3 Å and force field: optimized potentials for liquid simulations-2005 (OPLS_2005).

2.2 Active Site Prediction

The active sites of all the four Ebola viral receptors were identified using SiteMap, version 3.0, Schrödinger, LLC, New York, NY, 2014 [32]. The most essential property produced by Sitemap is an overall Sitescore, which has demonstrated to be successful at distinguishing known binding sites in co-crystallized complexes. Active sites with best site scores were taken as a prerequisite for receptor grid generation in all the Ebola viral receptors. The active sites identified by this program have been in accordance with the literature available for the VP40, VP35, VP24 and VP30 Ebola viral receptors.

2.3 Grid Preparation of Viral Receptors

Receptor Grid Generation Panel of Glide module of version 6.2, Schrödinger, LLC, New York, NY, 2014, used to generate grid which defines receptor structure by excluding any other co-crystallized ligand that may be present, settle on the position and size of the active site [33]. Grid point’s level for xyz axis (3.68, 19.15, 25.87) for 1H2C, (10.92, 24.85, 8.94) for 3FKE, (2.00, 30.00, 5.00) for 2I8B and (\(-10\), \(-15\), \(-20\)) for 4M0Q, respectively, within the grid parameters and grid generation was performed using OPLS_2005 (Fig. 2).
Fig. 2

Outline of virtual screening on multiple targets of EBOV

2.4 Compound Library Selection and Preparation

Flavonoid library and extended flavonoid library of 500 and 4000 compounds, respectively (http://www.timtec.net/), were downloaded. All the ligand structures in the libraries were in 2D SDF format which were first converted to 3D for docking. Geometry minimizations were performed on all the ligands using the OPLS 2005 force fields and truncated Newton conjugate gradient (TNCG). QikProp, v3.9, Schrödinger, LLC, New York, NY, 2014, was used for the screening of the ligands during their preparation and further to calculate the absorption, distribution, metabolism and excretion (ADME) properties [34]. Both physicochemically significant descriptors and pharmacokinetically relevant properties were predicted for all the ligands from the compound libraries. Lipinski’s rule of five was one of the factors used to assure the drug-like (oral) pharmacokinetic profile of the ligands.

2.5 Three-Tiered Virtual Screening

Virtual screening is the easiest method to recognize and rank potential leads from a database of various compounds against one or more targets. Considering the active sites of VP40, VP35 and VP24, three-tiered virtual screening was performed utilizing the flavonoids and extended flavonoid compound database. The compounds were subjected to Glide-based docking strategy in which all the compounds were docked by three phases of the docking convention: high-throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). However, the same scoring function has been implemented in HTVS (first phase) and SP (second phase), but HTVS reduces the number of intermediate conformations all through the docking funnel. All the screened compounds from HTVS are passed on to the second stage of SP docking. The SP resultant compounds were then docked using more accurate and computationally intensive mode in the final step of screening named XP. Taking into account the Glide (docking) score and Glide energy, the procedure gives the leads in XP descriptor. Glide module of the XP visualizer assesses the specific interactions such as ligand–protein interaction energies, H-bonds, hydrophobic interactions, internal energy, \(\pi {-}\pi\) stacking interactions, root mean square deviation (RMSD) and desolvation.

2.6 ADME Screening

The ADME properties (i.e., absorption, distribution, metabolism and excretion) of obtained screened flavonoids were predicted by using QikProp program. It also predicts both physical descriptors and pharmaceutical properties. All compounds should be neutralized before using QikProp because QikProp is unable to calculate descriptors in the rational mode. The program predicted approximately more than 40 properties for the molecules, existing principal descriptors and physiochemical properties, along with a detailed analysis of log P (octanol/water), QP % and % oral human absorption. On the basis of Lipinski’s rule of five [34], it evaluates the compound which is mandatory for rational drug design.

3 Results and Discussion

3.1 In Silico Screening of Compounds Against Ebola Viral Receptors

A total of 4500 compounds were screened with stepwise filtering strategy; initially, the compounds with high molecular weight (\(\mathrm{MW}>500\)) and with reactive functional groups were filtered out. The final compounds were then docked into the active site of VP40, VP35, VP 24 and VP30 proteins, using above-mentioned three stages of docking. The details of screened compounds at the final level of virtual screening have been summarized in Table 1, and their 2D structures are shown in Fig. 3. The Glide score was selected as the scoring function, and the e-model (Kcal/mol) was used to rank the poses of the ligands as the e-model combines the Glide score, non-bonded interaction energy and excess internal energy of generated ligand conformation for flexible docking. Similar docking parameters for BCX4430 are also reported in Table 1 for the comparative purpose.
Table 1

Comparison of binding efficacy on the basis of docking score, Glide g-score and binding energy of the screened flavonoids against all four Ebola viral receptors

Compounds

VP40 (1H2C)

VP35 (3FKE)

VP24 (4M0Q)

VP30 (2I8B)

Docking score

Glide g-score

Glide e-model

Docking score

Glide g-score

Glide e-model

Docking score

Glide g-score

Glide e-model

Docking score

Glide g-score

Glide e-model

ST059622

\(-6.049\)

\(-6.049\)

\(-37.486\)

\(-5.395\)

\(-5.395\)

\(-31.628\)

\(-8.252\)

\(-8.252\)

\(-34.633\)

\(-6.225\)

\(-6.225\)

\(-35.075\)

ST060285

\(-6.465\)

\(-6.485\)

\(-31.117\)

\(-5.433\)

\(-5.453\)

\(-37.229\)

\(-7.328\)

\(-7.328\)

\(-47.572\)

\(-7.320\)

\(-7.321\)

\(-45.869\)

ST50903219

\(-6.396\)

\(-6.397\)

\(-41.736\)

ST50940361

\(-5.490\)

\(-5.503\)

\(-37.576\)

ST101866

\(-7.810\)

\(-7.830\)

\(-47.195\)

ST078351

\(-7.775\)

\(-7.781\)

\(-40.775\)

BCX4430

\(-4.810\)

\(-4.871\)

\(-30.844\)

\(-4.393\)

\(-4.455\)

\(-33.444\)

\(-6.179\)

\(-6.241\)

\(-35.241\)

\(-5.586\)

\(-5.586\)

\(-40.140\)

‘–’ Symbol represents that the corresponding lead is not a top-ranked screened candidate for the respective receptor

Fig. 3

16 Structures of all the potential screened flavonoids; 7 structure of reported compound, i.e., BCX4430

The docking studies indicated that the top-ranked compounds showed strong hydrogen bonding interactions with the receptor. On the basis of docking score, Glide g-score and Glide e-model value, compound id’s named ST059622 and ST060285, are more effective against all the four Ebola viral protein receptors as compared to the reported drug BCX4430 which is in testing phase. These two compounds occupy the better binding efficiencies in all the Ebola viral receptors with comparatively higher docking scores and strong interactions as compared to the reported lead as shown in Table 1. On the other hand, compounds ST50903219, ST50940361, ST101866 and ST078351 are only specific antagonist to VP40, VP35, VP24 and VP30 of Ebola virus, respectively.

ST059622 is a flavonol compound named Gossypetin. It has been isolated from the flowers and the calyx of Hibiscus sabdariffa (roselle) and possesses natural antiviral activity. It was also found that the extract from Alchemilla mollis affected influenza virus particles directly and inhibited their infectivity [35, 36].

The other flavonoid ST060285 is commonly named Taxifolin, which may be present in China: Taxus chinensis, in Siberia: conifers like Larix sibirica, in Russia: Pinus roxburghii and Cedrus deodara [37]. It is also found in the silymarin extract from the milk thistle seeds, in the açaí palm and in small quantities in red onion [38]. The role of Taxifolin in decreasing the content of low-density lipoproteins in blood plasma and liver and showing antiviral properties have also been well established [39].
Table 2

Comparison of interactions of the Gossypetin (ST059622) and Taxifolin (ST060285) with the active site residues of all four Ebola viral receptors

Receptors

No. of H-bonds

H-bond interacting residues

Other non-bonded interactions

Using flavonoid ST059622 as inhibitor

 VP40

3

His 124, Gly 126, Gln 170

\(\pi\)\(\pi\) stacking [Tyr 171(2)]; hydrophobic (Phe 125, Ala 128, Pro 131, Tyr 171, Phe 172); polar (Thr 123); charged +ve (Lys 127)

 VP35

2

Gln 241(2)

Hydrophobic (Ile 295, Ile 297, Ile 303, Pro 304, Phe 328); polar (Gln 244, His 296); Charged +ve (Arg 298); charged –ve (Asp 302)

 VP24

4

Gln 103, Ser 123, Asp 124, Asn 185

Hydrophobic (Ala 99, Ile 107, Ala 116, Leu 127); polar (Thr 128, Thr 183, Gln 184, His 186)

 VP30

5

Asp 158(2), Arg 196, Gln 233(2)

Hydrophobic (Ile 159, Leu 199, Ile 236, Phe 238, Ala 241); polar (His 193, Ser 234, Thr 240); charged +ve (Arg 160)

Using flavonoid ST060285 as inhibitor

 VP40

3

His 124, Gly 126, Gln 170

Hydrophobic (Phe 125, Ala 128, Tyr 171); polar (Thr 123); charged +ve (Lys 127)

 VP35

3

Gln 244(2), Asp 302

Hydrophobic (Val 245, Cys 247, Ile 295, Ile 297, Ile 303, Pro 304, Phe 328); polar (Gln 241); charged +ve (Arg 225, Lys 248)

 VP24

5

Gln 103(2), Ser 123, Asp 124, Gln 184

Hydrophobic (Ala 99, Ile 107, Ala 116, Leu 127); polar (Thr 128, Thr 183, Asn 185, His 186)

 VP30

7

Arg 196, Gly 200(3), Gln 233, Ser 234, Phe 238

Hydrophobic (Leu 199, Val 207, Trp 230, Ile 236, Ile 239, Ala 241); polar (Gln 203, Thr 240)

Table 3

ADMET properties of the best two screened flavonoid inhibitors

Compounds

MW\(^\mathrm{a}\)

HBA\(^\mathrm{b}\)

HBD\(^\mathrm{c}\)

Mol log P\(^\mathrm{d}\)

Mol log S\(^\mathrm{e}\)

% Human oral absorption\(^\mathrm{f}\)

Gossypetin

318.239

6.000

5.000

−0.221

−2.521

29.705

Taxifolin

304.256

6.450

4.000

0.123

−2.720

52.057

\(^\mathrm{a}\) Molecular weight of the molecule should be in range between 160 and 500

\(^\mathrm{b}\) Estimated number of H-bond acceptors should not be more than 10

\(^\mathrm{c}\) Estimated number of H-bonds donors should not be more than 5

\(^\mathrm{d}\) Mol Log P for octanol/water (\(-2.0\) to 6.5)

\(^\mathrm{e}\) Calculated aqueous solubility, log S, should be in the range from \(-6.5\) to 0.5

\(^\mathrm{f}\) % Human oral absorption in GI (\(\pm\)20 %) should not be \({<}\)25 %

Fig. 4

ad Ligand interaction diagram of ST059622 (Gossypetin) with the VP40, VP35, VP24 and VP30 receptor, respectively

3.2 Binding Mode Analysis of Gossypetin in All the Ebola Viral Receptors

Gossypetin occupied the region of VP40 where RNA binds with a promising docking score of \(-6.465\) and the Glide (binding) energy of \(-31.117\) Kcal/mol as mentioned in Table 2. Hydrogen bond interactions were identified with the backbone amino acid residues His 124, Gly 126 and Gln 170. Five hydrophobic interactions with the amino acid residues Phe 125, Ala 128, Pro 131, Tyr 171, Phe 172 and one positive charge interactions with Lys 127 residue were observed (Fig. 4a). It also forms two \(\pi {-}\pi\) stacking with Tyr 171 residue and a single interaction with polar residue Thr 123.

It binds to interferon inhibitory domain (IID) region of VP35 which is substantial for the formation of replication complex by interacting with the viral NP. The docking score and Glide energy for this complex is found out to be \(-5.395\) and \(-31.628\) Kcal/mol, respectively (Table 2). Two hydrogen bond interactions were identified with the side chain of amino acid residue Gln 241 (Fig. 4b). It forms hydrophobic interactions with Ile 295, Ile 297, Ile 303, Pro 304 and Phe 328 amino acid residues. Polar interactions with amino acid residues Gln 244 and His 296 were observed. A charged positive residue Arg 298 and a charged negative residue Asp 302 are also involved in interaction with the ligand.

The highest docking score of \(-8.252\) and Glide energy of \(-34.633\) Kcal/mol is identified in the strong interaction of VP24 with Gossypetin (Table 2). With the Ebola viral receptor VP24, Gossypetin forms four H-bonds with the side chain of Gln 103, Ser 123, Asp 124 and Asn 185 amino acid residues. Four hydrophobic interactions with amino acid residues Ala 99, Ile 107, Ala 116 and Leu 127 were also identified. It also forms polar interactions with Thr 128, Thr 183, Gln 184 and His 186 amino acid residues (Fig. 4c).

Examination of the Ebola viral receptor VP30 sequence using hydrophobic cluster analysis revealed the presence of two structured domains from amino acid residue 45–119 and from amino acid residue 141–267, respectively. The docking score and Glide energy for this complex are found out to be \(-6.225\) and \(-35.075\) Kcal/mol, respectively (Table 2). Gossypetin forms two hydrogen bond interactions with the backbone amino acid residue Gln 233, two H-bonds with side chain amino acid residues Asp 158 and single H-bond interaction with amino acid residue Arg 196. It forms five hydrophobic interactions with Ile 159, Leu 199, Ile 236, Phe 238 and Ala 241 amino acid residues (Fig. 4d). Three polar interactions of Gossypetin with amino acid residues His 193, Ser 234, Thr 240 and single interaction with charged positive residue Arg 160 were also observed.
Fig. 5

ad Ligand interaction diagram of ST060285 (Taxifolin) with the VP40, VP35, VP24 and VP30 receptor, respectively

3.3 Binding Mode Analysis of Taxifolin in All the Ebola Viral Receptors

In resemblance to Gossypetin, Taxifolin possessed the same RNA binding region of VP40 with a good docking score of \(-6.049\) and the Glide (binding) energy of \(-37.486\) Kcal/mol (Table 2). Hydrogen bond interactions were identified with the backbone amino acid residues His 124, Gly 126, Gln 170. Three hydrophobic interactions with the amino acid residues Phe 125, Ala 128 and Tyr 171 (Fig. 5a) were identified. There is also one positive charge interaction with Lys 127 residue, and a single interaction with polar residue Thr 123 was observed.

Taxifolin also binds to IID region of VP35 which is important for the formation of replication complex by interacting with the viral NP. The docking score and Glide energy for this complex are found out to be \(-5.433\) and \(-37.229\) Kcal/mol, respectively (Table 2). Two stable H-bond interactions were detected with the backbone of amino acid residue Gln 244. Amino acid residue Asp 302 also forms single backbone H-bond interaction with the ligand (Fig. 5b). It forms hydrophobic interactions with Val 245, Cys 247, Ile 295, Ile 297, Ile 303, Pro 304 and Phe 328 amino acid residues. Polar interactions with amino acid residues Gln 241 was observed. The charged positive residues Arg 225 and Lys 248 are also involved in interaction with the ligand.

The highest docking score of \(-7.328\) and Glide energy of \(-47.572\) Kcal/mol is identified in the strong interaction of VP24 with Taxifolin (Table 2). With the Ebola viral receptor VP24, Taxifolin forms five hydrogen bonding interactions with the backbone of Gln 184 and the side chain of Gln 103(2), Ser 123, Asp 124 amino acid residues. Four hydrophobic interactions with amino acid residues Ala 99, Ile 107, Ala 116 and Leu 127 were also identified. It also forms polar interactions with Thr 128, Thr 183, Asn 185 and His 186 amino acid residues (Fig. 5c).

The docking score and Glide energy for the complex of VP30 with Taxifolin is found out to be \(-7.320\) and \(-45.572\) Kcal/mol, respectively (Table 2). Taxifolin forms seven H-bonds (backbone) with the amino acid residue Gly 200(3), Ser 234, Phe 238 and two H-bonds with side chain amino acid residues Arg 196 and Gln 233 (Fig. 5d). It forms six hydrophobic interactions with Arg 196, Gly 200(3), Gln 233, Ser 234 and Phe 238 amino acid residues. Two polar interactions of Taxifolin with amino acid residues Gln 203 and Thr 240 were also observed.

3.4 ADME Properties Prediction

Physically critical descriptors and pharmaceutically significant properties of the two lead compounds were investigated utilizing Qikprop program as depicted in Table 3. Molecular weight, H-bond acceptors, H-bond donors, log P octanol/water partition coefficient, Mol Log S and their percentage of human oral absorption were included as significant descriptors. The screened two lead compounds, i.e., Gossypetin and Taxifolin, were in the permissive range of Lipinski’s rule of five, demonstrating their potential for utilization as medication like drugs.

4 Conclusions

In conclusion, the results of the current study clearly demonstrated that screened flavonoids, i.e., Gossypetin and Taxifolin, are better inhibitors in comparison with reported lead BCX4430 for viral protein targets. Also the screened inhibitors are effective against multiple targets of Ebola therapy, hence helpful in blocking several signaling pathways simultaneously.

It is reported that the octameric VP40 target protein binds to RNA tribonucleotide at the inner pore surface of each antiparallel homodimer to form the viral matrix; hence, blocking the active site through screened flavonoids may restrict this pathway of virus membrane formation. Similarly, VP35 protein inhibits post-IFN induction by association with TBK1–IKBKE–DDX3 complex; hence, obstructing the active site of this protein by the screened flavonoids may hamper the replication and virulence factor of the EBOV. Further, the said screened flavonoids may inhibit the ability of VP24 protein to disrupt IFN signaling through prevention of STAT1 signaling pathway. It may be further inferred that the RNA binding ability of VP30 protein which is required for viral replication can also be successfully inhibited by the screened flavonoids. Considering the multi-target binding affinity of proposed ligands, these may be concluded as effective inhibitors for EBOV. The screened flavonoids have known antiviral activity and acceptable pharmacokinetic properties as reported and thus can be safely used as therapeutic regime for Ebola infection.

The findings of this study are paramount as there is requirement for new medication to restrain Ebola infection. The leads figured out could potentially restrain the disease. Notwithstanding, these leads ought to experience different preclinical analysis and optimization before going into clinical trials. Therefore, these new molecular entities were suggested as possible versatile inhibitors for these proteins.

Compliance with Ethical Standards

Conflict of interest

We declare that we have no conflict of interest.

Copyright information

© International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Bioinformatics DivisionIndian Institute of Information TechnologyAllahabadIndia

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