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Article

Diterpenes/Diterpenoids and Their Derivatives as Potential Bioactive Leads against Dengue Virus: A Computational and Network Pharmacology Study

by
Rasel Ahmed Khan
1,†,
Rajib Hossain
2,*,†,
Abolghasem Siyadatpanah
3,
Khattab Al-Khafaji
4,
Abul Bashar Ripon Khalipha
2,
Dipta Dey
5,
Umma Hafsa Asha
2,
Partha Biswas
6,
Abu Saim Mohammad Saikat
5,
Hadi Ahmadi Chenari
3,
Polrat Wilairatana
7,* and
Muhammad Torequl Islam
2,*
1
Pharmacy Discipline, Life Science School, Khulna University, Khulna 9280, Bangladesh
2
Department of Pharmacy, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Dhaka 8100, Bangladesh
3
Ferdows School of Paramedical and Health, Birjand University of Medical Sciences, Birjand 9717853577, Iran
4
Department of Medical Laboratory Technology, Al-Nisour University College, Baghdad 10001, Iraq
5
Department of Biochemistry and Molecular Biology, Life Science Faculty, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Dhaka 8100, Bangladesh
6
Department of Genetic Engineering and Biotechnology, Faculty of Biological Science and Technology, Jashore University of Science and Technology (JUST), Jashore 7408, Bangladesh
7
Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Molecules 2021, 26(22), 6821; https://doi.org/10.3390/molecules26226821
Submission received: 26 September 2021 / Revised: 6 November 2021 / Accepted: 8 November 2021 / Published: 11 November 2021
(This article belongs to the Special Issue Antiviral Agents for RNA-Virus Infection)
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Abstract

:
Dengue fever is a dangerous infectious endemic disease that affects over 100 nations worldwide, from Africa to the Western Pacific, and is caused by the dengue virus, which is transmitted to humans by an insect bite of Aedes aegypti. Millions of citizens have died as a result of dengue fever and dengue hemorrhagic fever across the globe. Envelope (E), serine protease (NS3), RNA-directed RNA polymerase (NS5), and non-structural protein 1 (NS1) are mostly required for cell proliferation and survival. Some of the diterpenoids and their derivatives produced by nature possess anti-dengue viral properties. The goal of the computational study was to scrutinize the effectiveness of diterpenoids and their derivatives against dengue viral proteins through in silico study. Methods: molecular docking was performed to analyze the binding affinity of compounds against four viral proteins: the envelope (E) protein, the NS1 protein, the NS3 protein, and the NS5 protein. Results: among the selected drug candidates, triptolide, stevioside, alepterolic acid, sphaeropsidin A, methyl dodovisate A, andrographolide, caesalacetal, and pyrimethamine have demonstrated moderate to good binding affinities (−8.0 to −9.4 kcal/mol) toward the selected proteins: E protein, NS3, NS5, and NS1 whereas pyrimethamine exerts −7.5, −6.3, −7.8, and −6.6 kcal/mol with viral proteins, respectively. Interestingly, the binding affinities of these lead compounds were better than those of an FDA-approved anti-viral medication (pyrimethamine), which is underused in dengue fever. Conclusion: we can conclude that diterpenoids can be considered as a possible anti-dengue medication option. However, in vivo investigation is recommended to back up the conclusions of this study.

1. Introduction

Dengue (pronounced Den’gee) is a viral disease caused by one of the dengue virus strains, namely DEN1, DEN2, DEN3, and DEN 4 [1,2]. Viral transmission to humans occurs by the infected mosquito bite of an Aedes aegypti type. Dengue virus (DENV) is an RNA virus, otherwise known as arboviruses, and belongs to the Flaviviridae family [3]. The DENV genome has 11,000 nucleotide bones. They have three different protein molecules, C, prM, and E, that form virus particle. They also contain seven other types of protein molecules (NSI, NS2a, NS2b, NS3, NS4a, NS4b, and NS5) found in infected host cells and are instrumental for viral replication [1].
DENV is an enveloped, single-stranded, positive-sense virus with a 10.7 kb RNA genome [4,5], which is translated as a single polyprotein and then cleaved into three structural proteins, e.g., capsid (C), remembrance/membrane (prM/M), and envelope (E) and seven non-structural (NS) proteins, by a virus- and host-encoded proteases. The three structural proteins are important for capsid formation (C) and assembly into viral particles (prM and E). The non-structural proteins contain a serine protease and ATP-dependent helicase (NS3), which is required for virus polyprotein processing, a methyltransferase, and RNA-dependent RNA polymerase (NS5), and a cofactor for the NS3 protease (NS2B). NS4B has been implicated in blocking the interferon (IFN) response. NS1, NS2A, and NS4A have unknown or incompletely understood functional activities of dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN) on dendritic cells [6], followed by viral uptake by receptor-mediated endocytosis. Endosomal acidification causes fusion of the viral and endosomal membranes and nucleocapsid. These NS proteins may be necessary for replication. In primary infection, the virus (DENV) enters target cells by the adherence of E protein to cell surface receptors, such as release into the cytoplasm [7,8]. Virus genome replication occurs in discrete domains within the endoplasmic reticulum (ER), assembly occurs in the ER, and virions come out via Golgi-derived secretory vesicles [9].
After being bitten by a mosquito of A. aegypti or A. albopictus type [10], DENV can cause a range of mild-to-severe illnesses. Each year it is believed to infect 50 to 100 million people worldwide (https://www.who.int/denguecontrol/epidemiology/en/, accessed on 20 June 2021), having a mortality rate of 1–5% without treatment and less than 1% with treatment. Severe illness (dengue hemorrhagic fever, D. S. S) has a mortality rate of 26%. The dengue rate has climbed to a 30-fold increase between 1960 and 2010. The reason is believed to be factors such as rapid urbanization, population growth, international travel from endemic areas, and global warming. The geographical area around the equator, mainly Asia and the Pacific, is mostly affected [1]. Initial global estimates of total dengue infections were based on an assumption of a constant annual infection rate among a crude approximation of the population at risk (10% of one billion [10] or 4% of two billion [11], resulting in several 80–100 million infections per year worldwide in 1988 [10,11]. Later, with more information regarding the ratio of dengue hemorrhagic fever to dengue fever cases, and the ratio of deaths to dengue hemorrhagic fever cases, the global infection was revised to 50–100 million infections per year [12,13,14,15].
In research by da Silva and his co-workers, it is indicated that labdane diterpenes isolated from the oil-resin fractions of Copaifera reticulata exhibit considerable larvicidal activity (median lethal concentration (LC50 = 0.8 ppm) towards the mosquito [16]. Labdane diterpenoid of the same species (C. reticulata) caused the death of A. aegypti larvae by cell destruction in the midgut [17]. The diterpene content of the essential oil of Lantana montevidensis also showed a larvicidal effect against A. aegypti [18]. Methyl dodovisate A and B, isolated from the aerial parts of Dodonaea viscose, is reported to exhibit a larvicidal effect (LC50 > 30 μg/mL) on A. albopictus larvae [19]. On the other hand, caesalacetal and caesaljapin isolated from Sulcobrachus sauteri also displayed anti-A. albopictus activity with LC50 values of 3 and 9 μg/mL, respectively [20]. The lipophilic nature of diterpenes and their derivatives enables them to cross the biological membranes which include the blood-brain barrier (BBB). Additionally, they can induce oxidative stress, increase levels of nitric oxide (NO) in the infected host, reduce the anti-viral resistance to reactive oxygen species (ROS), increase lipid peroxidation, and induce chronic inflammatory responses and cell membrane damage [21].
As a result, there are two major strategies for developing new DENV agents. To begin, the compound must (i) precisely inhibit the host behavior involved in viral replication while not affecting the cell’s normal function, and (ii) be able to adequately inhibit the host factor in vivo throughout physiological conditions [22]. Some of the natural diterpenes/diterpenoids and their derivatives were shown to exert a prominent effect on DENV vectors and exhibit cytotoxic effects on DENV as well. Moreover, these diterpenes/diterpenoids exert their anti-viral viral effects through different mechanisms of action, including the anti-DENV effect and larvicidal activity [23]. In this regard, this research aimed to look into the in silico ability of diterpenoids and their derivatives against the proteins that make up viral proteins.

2. Results and Discussion

2.1. Attribution of Proteins’ Active Sites and Validation

The binding sites of receptor proteins of dengue virus envelope (E) protein, NS3, NS5, and NS1 were predicted through the CASTp server using default parameters of the webserver [24]. In envelope (E) protein has 74 binding pockets that were characterized to attain residues probe radius 1.4 Å. Moreover, NS3, NS5, NS1. The amino acid residues involved in the conformation of binding pockets are depicted in Figure 1.

2.2. Computational Virtual Screening of Diterpenoids and Their Derivatives

ADMET Analysis

For the analysis and optimization of pharmacokinetic properties, the pkCSM and Swiss ADME approach confer a platform. The ADMET study of diterpenoids and their derivatives are shown in Table 1 and Figure 2.

2.3. Molecular Docking

2.3.1. Docking Approach of Natural Bioactive against DENV Receptor Proteins

Interaction with Viral Envelope (E) Protein

The best docking energy for the viral envelope (E) protein is the natural ligands triptolide, stevioside, alepterolic acid, and sphaeropsidin A with the binding energies of −8.1, −8.4, −8.3, and −8.7 kcal/mol, respectively. The binding mode study was carried out on the next four active compounds, and the results are shown in Table 2. Additionally, the existence of hydrogen bonds between the phytochemicals and the viral E protein stabilizes the ligand within its binding locations. The docking complexes were visually inspected in-depth for the interactions and binding mechanisms of each ligand with the functional residues of the DENV E protein (Figure 3).
Triptolide, a component of the medicinal plant Tripterygium wilfordii Hook, displays energy and is known to be useful against a variety of diseases, including lupus, cancer, rheumatoid arthritis, and nephrotic syndrome [25,26]. Triptolide has been demonstrated to suppress dengue reproduction [27], HIV1 replication [28], and herpes virus viral titer in recent research [29]. At 0.5–4 nM, it (triptolide) showed anti-DENV activity in a DENV model [27]. Whereas stevioside is a natural sweetener [30], Stevia rebaudiana displayed −9.3 kcal/mol against NS1 proteins and exhibited an anti-rota viral effect in combination with Sophora flavescens plant extract [31]. Along with the anti-viral effect of stevioside demonstrated anti-inflammatory effect [32], anti-hyperglycemic effect [33], and so on.
Furthermore, sphaeropsidin A, a fungal metabolite (phytotoxin), was found from Diplopia cupressi, which has a larvicidal effect (LD50: 36.8 ppm) on A. aegypti [34]. Moreover, sphaeropsidin A has the potential ability to include anti-biofilm activity, anti-microbial activity [35], and anti-cancer activity [36]. In our molecular docking study, sphaeropsidin A displayed good binding energy with DENV NS1 receptor protein through two hydrogen bonds and some other conventional hydrogen bonds, pi-pi, pi-alkyl bonds (Table 2).
Alepterolic acid is an ent-labdane diterpene found as a major metabolite from Aleuritopteris argentea (S. G. Gmél.) Fée is a medicinal fern. Alepterolic acid exhibited dengue larvicidal properties with an LC50 of 87.3 ppm. Additionally, it has shown potential selectivity towards Trypanosoma brucei with a median inhibitory concentration (IC50) of 3.42 μM [37]. Incorporation of the amino moiety into alepterolic acid can inhibit the proliferation of the cervical cancer cell line HeLa and induce apoptosis through the mitochondrial pathway [38].

Interaction with Viral NS3

Natural ligands stevioside, sphaeropsidin A, methyl dodovisate A, and caesalacetal showed the best binding energies for the viral NS3 protein with −8.0, −8.3, −9.2, and −8.0 kcal/mol, respectively. The binding mode study was carried out on the next four active compounds, and the results are shown in Table 3. The existence of hydrogen bonds between the phytochemical and the viral E protein additionally stabilizes the ligand within its binding locations. The docking complexes were visually inspected in-depth for the interactions and binding mechanisms of each ligand with the functional residues of the DENV E protein (Figure 4).
Stevioside is a natural sweetener [30]; Stevia rebaudiana, displayed −9.3 kcal/mol against NS1 proteins and showed inhibitory activity against NS2B-NS3pro of DENV4, with IC50 values of 14.1 ± 0.2, 24.0 ± 0.4, and 15.3 ± 0.4 µg/mL, respectively, where it is present in a mixture or similar compounds such as rebaudioside A (Reb-A), or steviol glycosides (SG), etc. [31,32]. It also has been associated with anti-hyperglycemic properties [33], and so on. Sphaeropsidin A was also found to have a larvicidal impact on Aedes aegypti (LD50: 36.8 ppm) [34]. Furthermore, anti-biofilm activity, antibacterial activity [35], and anti-cancer activity are all possible with sphaeropsidin A. [36]. Sphaeropsidin A showed good binding energy with dengue viral NS1 receptor protein in molecular docking research, thanks to two hydrogen bonds and additional traditional hydrogen bonds, pi–pi, and pi–alkyl bonds (Table 3).
On the other hand, methyl dodovisate A is isolated from the aerial parts of D. viscosa. It showed a larvicidal effect with an LC50 > 30 μg/mL on A. albopictus [38]. Furthermore, caesalacetal, isolated from S. sauteri also displayed anti-A. albopictus activity with LC50 values of 3 μg/mL [20].

Interaction with Viral NS5

With DENV protein NS5, phytochemicals, triptolide, stevioside, andrographolide, and caesalacetal demonstrated good to moderate binding energies of −8.8, −9.4, −8.4, and −8.4 kcal/mol, respectively (Table 4). The existence of hydrogen bonds between the phytochemical and the viral NS5 protein additionally stabilizes the ligand within its binding locations. The docking complexes were visually inspected in-depth for the interactions and binding mechanisms of each ligand with the functional residues of the DENV protein (Figure 5).
Andrographolide is a lactone diterpene, isolated from Andrographis paniculata, and possesses many biological effects, including antioxidant [39], anti-inflammatory [40], neuroprotective [41], hepatoprotective [42], anti-viral [43,44,45], anti-thrombotic [46], anticancer [47], and others. This diterpene lactone at 100 and 200 μM concentration showed an anti-DENV effect via GRP78 interaction pathway and at 5, 10, 15, and 25 ppm, a concentration larvicidal effect by inducing cytopathic effects in the midgut epithelium (LC50: 12 ppm) [23].

Interaction with Viral NS1

The natural ligands triptolide, stevioside, sphaeropsidin A, and caesalacetal have the best docking energy for the viral NS1 protein, with binding energies of −8.3, −9.3, −8.5, and −8.5 kcal/mol, respectively. The binding mode study was carried out on the next four active compounds, and the results are shown in Table 5. Furthermore, the existence of hydrogen bonds between the NS1 receptor protein and the phytochemical stabilizes the ligand in its binding locations. By visually inspecting the docking complexes, the interactions and binding mechanisms of each ligand with the functional residues of the DENV NS1 protein were investigated in-depth (Figure 6).
Triptolide, a component of the medicinal plant Tripterygium wilfordii Hook, displays energy and is known to be useful against a variety of diseases, including lupus, cancer, rheumatoid arthritis, and nephrotic syndrome [26,48]. Triptolide has been demonstrated to suppress DENV reproduction [27], HIV1 replication [28], and herpes virus viral titer in recent research (Long et al., 2016) [49]. At 0.5-4 nM, it showed anti-DENV activity in a DENV model [27]. On the other hand, stevioside displayed −9.3 kcal/mol against NS1 proteins and exhibits an anti-rota viral effect in combination with S. flavescens plant extract [31]. Along with its anti-viral effect, it also demonstrated an anti-inflammatory effect [32], anti-hyperglycemic effect [33], and so on.
Besides its larvicidal effect [34], sphaeropsidin A possess the potential ability to include anti-biofilm, anti-microbial [35], and anti-cancer activity [36]. In our molecular docking study, this gamma-lactone fungal metabolite displayed good binding energy with DENV NS1 receptor protein through two hydrogen bonds and some other conventional hydrogen bonds, pi-pi, pi-alkyl bonds (Table 6).
Caesalacetal, a cassane-type furanoditerpenoids, is mostly found in S. sauteri [20]. It is also isolated from the roots of C. decapetala var [50]. It exhibited larvicidal activities with an LC50: 3 μg/mL in the DENV vector [20]. It further demonstrated anti-viral activity against the protein NS1 (Table 5). The 2D and 3D structures of non-bond interactions of triptolide, stevioside, sphaeropsidin A, and caesalacetal with the target protein NS1 are shown in Figure 6.

2.3.2. Docking Approach of Chemical Analog (Pyrimethamine) against DENV Proteins

The chemical compound (pyrimethamine), a DENV NS2B/3 protease inhibitor that has been shown to impede DENV translation and polyprotein processing [51], specifically at one intramolecular cleavage site within NS3 [52]. In molecular docking study, pyrimethamine has demonstrated good binding energies with four DENV receptor proteins E protein, NS3, NS5, and NS1 (Table 6) to be −7.5, −6.3, −7.8, and −6.6 kcal/mol, respectively. In Figure 7, the docked postures are shown. The results showed that when each receptor was docked with certified natural ligands, it had superior docked scores and binding energies than when the outcome was anticipated using a chemical equivalent. Pyrimethamine [5-(4-chlorophenyl)-6-ethylpyrimidine-2,4-diamine Chloridine], an FDA-approved chemical molecule, is highly selective against the proteins that cause dengue fever. Its efficacy against DENV has been previously documented [53]. As a result, it has been recommended that various natural ligands be used to attack certain infectious and dangerous targets. Furthermore, using natural substances to treat a variety of recently emerging infections has become a popular method in medicinal chemistry since these molecules are unlikely to induce adverse effects that would otherwise be induced by pharmaceuticals [54]. Moreover, these bioactive natural ligands are major components of widely available plants with significant therapeutic potential, which are still utilized in traditional medicine to treat a variety of viral infections [55].

2.4. Molecular Dynamic Simulation Analysis

The binding of a compound to the binding site of a protein can lead to observable conformational changes in the dynamics of the targeted protein. Root mean square deviation (RMSD) is one of the most important fundamental properties for establishing whether the protein is stable and close to the experimental structure [56] According to the RMSD plot, native, alepterolic acid, sphaeropsidin A, and stevioside binding kept the dynamics of targeted proteins at less than 0.3 nm, whereas triptolide binding resulted in more structural deviations from its native conformation (Figure 8A). In the case of the native-bound 1OKE and alepterolic acid, sphaeropsidin A, and stevioside-bound 1OKE complexes, the nature of their dynamics was the same during 100 ns of MD simulation.
In another case, the dynamics of caesalacetal, methyl dodovisate A, and stevioside-bound 2VBC were less than native-bound 2VBC, while the dynamics of sphaeropsidin A-bound 2VBC increased dramatically after 60 ns (Figure 8). For 4O6B, all of the selected compounds had a good dynamical effect on 4O6B, where all RMSD values of selected compound-bound 4O6B fluctuated less than 0.3 nm during the 100 nm. It can also be observed that caesalacetal and triptolide diminished the degree of fluctuation less than the native-bound 4O6B (Figure 8C).
For another targeted protein (4V0Q), the average value for the RMSD of native-bound 4V0Q was ≈ 0.287 as shown in Figure 8D. Further, we can observe that caesalacetal and stevioside reduced the dynamics of 4V0Q when they bound to it. Triptolide, on the other hand, increased the overall RMSD fluctuation by 100 ns more than the native ligand (Figure 8D). Moreover, the dynamics of understudied drugs inside the active site were compared and presented in Figure 8B. It can be observed that all of these ligands have nearly the same nature of movements inside the active site.
To investigate the dynamics of the protein’s backbone residues in the protein-ligand complexes compared to the Native-bound protein, the root means square fluctuations (RMSF) of the backbone atoms of the protein were depicted in Figure 9. Figure 9A reveals that the alepterolic acid, sphaeropsidin A, stevioside, and triptolide reduced the RMSF values of 1OKE when compared with native-bound protein. For the second target (2VBC) methyl dodovisate A and stevioside had a significant impact on increasing the fashion of fluctuation of RMSF of 2VBC when compared with native (Figure 9B). Whilst the third target (4O6B), the overall average RMSF value for native-bound 4O6B (Figure 9C), is higher than the caesalacetal, sphaeropsidin A, stevioside, and triptolide-bound 4O6B, and for the fourth target (4V0Q), as shown in Figure 9D, stevioside nearly fluctuated higher than the dynamics of native-bound 4V0Qand rest compound-bound 4V0Q complexes.

2.5. MM-PBSA Analysis

Hydrogen bond number and distribution in the selected targets with the selected compounds were studied to determine the stability of the protein-drug interactions inside the binding site during the 100 ns simulation period (Table 7). The hydrogen bond number results showed that stevioside had the highest number of hydrogen bonds (2.116988301) with 1OKE when compared with native, alepterolic acid, sphaeropsidin A, and triptolide Figure 10. Again, stevioside exhibited the highest average number of hydrogen bonds (3.206679332) compared to native, caesalacetal, methyl dodovisate A, and sphaeropsidin compounds as presented in Figure 10B. Further, stevioside, showed very strong interaction (average number of hydrogen bonds is 4.02439756) with 4OBE (Figure 10C). Most interestingly, the behavior in which stevioside again established the highest number of hydrogen bonds with 4V0Q (average is 2.765623438) is illustrated in Figure 10D. The hydrogen bond results help in understanding the functionality and ability of stevioside to work as a multi-target binder.

2.6. Network Pharmacology of Diterpenoids

2.6.1. Gene Set Enrichment Analysis

Enrichment analysis is a versatile method to gain insight into the pathways whose activity is influenced by a particular gene group. As seen in Figure 11A, our biological process enrichment analysis indicated that the list of genes targeted by our medicinal plant compounds was most significantly associated with DNA metabolic process, DNA repair, and replication, cellular response to DNA damage stimulus, nucleocytoplasmic transport, regulation of translational initiation, protein localization to nuclear envelope, regulation of translation, and spliceosomal snRNP assembly regulation of cell cycle G2/M phase transition pathways. The top 10 molecular function enrichments are mismatched DNA binding, damaged DNA binding, ribosomal small subunit binding, nucleoside diphosphate kinase activity, phosphatidylinositol phospholipase C activity, phospholipase C activity, nucleobase-containing compound kinase activity, phosphoric diester hydrolase activity, double-stranded DNA binding, and snRNA binding, as shown in Figure 11B. Figure 11C illustrates the cellular components that include the spindle pole centrosome, methylosome, centrosome, small nuclear ribonucleoprotein complex, microtubule organizing center, U4/U6 x U5 tri-snRNP complex, replication fork, spliceosomal tri-snRNP complex, centriole, and nuclear body. The KEGG pathway annotation showed that pathways in cytosolic DNA-sensing pathway, longevity regulating pathway, prion diseases, epithelial cell signaling in Helicobacter pylori infection, tumor necrosis factor (TNF) signaling pathway, RNA transport, vasopressin-regulated water reabsorption, ErbB signaling pathway, spliceosome and cysteine, and methionine metabolism were at the top of the list, as shown in Figure 11D.

2.6.2. Construction of “Drug-Target-Pathway” Network

The seven drug candidates, 313 gene targets, and the top 10 pathways were imported into Cytoscape (V.3.8.2) software, and the “Drug-Target-Pathway” network was obtained as shown in Figure 12. Light green hexagonal symbols represent the chosen drugs, the blue circle represents potential targets, and the red triangle represents pathways. Through the software, the node is visualized by degree value, and the node size is proportional to degree value. According to the requirements of topological parameters, the key nodes were determined by degree values greater than twice the median to obtain potential active components for later molecular docking tests.

3. Materials and Methods

3.1. Protein/Macromolecule Structure Preparation

The crystal structural protein of DENV envelope (E) protein (PDB ID: 1OKE, resolution: 2.40 Å) [57], a serine protease, and ATP-dependent helicase (NS3) (PDB ID: 2VBC. resolution: 3.15Å) [58], RNA-dependent RNA polymerase (NS5) (PDB ID: 4V0Q, resolution: 2.3 Å) [59], NS1 (PDB ID: 4O6B, resolution: 3 Å) [60] (Figure 1). Three-dimensional crystal enzyme structures in PDB format for Structural Bioinformatics were downloaded from the Protein Data Bank (PDB) (https://www.rcsb.org/, accessed on 1 June 2021) and for energy minimization in the crystal structure, we utilized the Swiss-PDB Viewer software package (version 4.1.0), and then all the heteroatoms and water molecules of proteins were removed by usingPyMOl (V.2.4.) before docking [61]. These structures were examined critically using Ramachandran Plot by ProCheck [62] to inspect the superior quality of the target protein structures selected for docking studies. All the crystallographic water molecules and associated heteroatoms were eliminated from the original crystal structures, and polar hydrogen atoms were added along with the Kollman charges. The geometry of the original moiety was rectified and visualized by PyMol (V.2.4) [63].

3.2. Active Site Prediction

For efficient docking, CASTp [24] has been used to approximate viral receptor active sites, and PyMol (V.2.4) was used to describe the Cartesian coordinates x, y, and z (active sites). Auto Dock Vina also used these regions to create grid boxes for molecular docking [64]. The active sites with the highest scores were characterized as a required precursor for the production of a grid in identified viral and vector receptors. CASTp was used to characterize and measure the active sites, binding sites, internal inaccessible cavities, surface accessible structural pockets and structure, and protein cavities [65].

3.3. Selection and Preparation of Ligands

There are 160 diterpenes/diterpenoids that were collected and selected from natural resources and mentioned by the literature-screening procedure [66,67,68]. From them, nearly 20 diterpenoids are available and showed anti-DENV activity in several in vivo experimental systems (Table 8) [23] as well as the FDA-approved drug, pyrimethamine, were obtained from the PubChem repository sample in the “sdf” file format. Pyrimethamine (Pubchem ID: 4993), a DENV NS2B/3 protease inhibitor, could block the translation and polyprotein processing in DENV [51], particularly at one intramolecular cleavage site within NS3 [52]. All internal energies of the ligands were optimized by using Chem3D Pro12.0 program packages [69]. The chemical structures were drawn using Chemsketch [70]. The final optimized and prepared ligands were used for molecular docking (Table 8).

3.4. In Silico Pharmacokinetic Study

For identification of drug likeliness of diterpene ligands, a study has been utilized similar to the way that Lipinski’s rule of five [71], Ghose filters [72], CMC 50 like rule [73], Veber filter [74], MDDR like rule [75], BBB likeness (Clark, 2003) [76], and QED [77] were used to gauge the compounds. Lipinski’s filter was used to measure hydrophobicity. Many of the ligands in the active compounds had their pharmacokinetic profile and physicochemical descriptors expected. In drug development, these guidelines have been used to preselect bioactive molecules [78].
ADME (Adsorption, Distribution, Metabolism, and Excretion) is important to analyze the pharmacodynamics of the proposed molecule that could be used as a drug. SWISS-ADME tool [79] is a website (https://www.swissadme.ch, accessed on 5 June 2021) which allows the user to draw their respective ligand or drug molecule or include SMILES data from PubChem and provides the parameters, such as lipophilicity (iLOGP, XLOGP3, WLOGP, MLOGP, SILICOS-IT, Log P0/w), water solubility-Log S (ESOL, Ali, SILICOS-IT), drug-likeness rules (Lipinski, Ghose, Veber, Egan, and Muegge) and Medicinal Chemistry (PAINS, Brenk, Leadlikeness, Synthetic accessibility) methods [79]. Data from PubChem, which consists of SMILES of diterpene ligands (https://pubchem.ncbi.nlm.nih.gov/compound, accessed on 5 June 2021) was entered into the search bar and was analyzed.
Toxicology prediction of small molecules is important to predict the tolerability of the small molecules before being ingested by human and animal models. pkCSM is an online database in which the small molecule can be drawn virtually or can be analyzed by submitting the SMILES of the same. The website can provide details of toxicology effects in the fields of human maximum tolerated dose, LD50, hepatotoxicity, and Minnow toxicity. The website was logged on and SMILES of the diterpene ligands data from PubChem was searched and submitted into the website, and toxicity mode was selected [80].

3.5. Molecular Docking Protocol

In medicinal chemistry, molecular docking is a numerical tool for drug design. The Auto Dock Vina tool uses this approach to predict the pharmacodynamic profile of drug candidates by ranking and orienting them to receptor binding sites [81]. The docking outcome specifies the degree of ligand interaction with the desired protein’s active site. The active binding sites of the target protein are the locations of the ligand in the initial target protein grids (40 × 40 × 40) [82], with PyMol, Auto dock Vina, and Drug Discovery Studio (v.20.1.0.19295) being used to examine them [83].

3.6. Molecular Dynamics (MD) Simulation Study

MD modeling is now considered a decisive step in computer-aided research for drug discovery at the atomic level. By studying the internal movement of proteins, many mysterious biological functions of proteins and their deep dynamic mechanisms can be revealed [56]. Regarding the dynamically changing time scale, we can use this time scale to judge whether the protein-ligand complex is stable [84]. In this study, we performed MD simulations on the four proteins with docked ligands in addition to cocrystal ligands, produced by molecular binding on a time scale of 100 ns. We used the GROMACS 2018.1 package [85] to run the MD simulation. The CHARMM 27 force field [86] was used to parameterize the ligand-protein complex of all atoms. The intermolecular three-point transfer potential (TIP3P) was chosen as the solvent [87], adding Na + or Cl-ions to adjust the charge to simulate the physiological environment. Then we used the steepest descent algorithm [56] with an allowable value of 1000 kJ/mol·nm to minimize the energy of these systems. In the next step, the NVT and NPT pools canceled out the positionally restricted complexes on the protein molecule within 0.1 ns. Then, MD simulations with no restrictions on protein molecules or ligands were performed to determine the stability within 100 ns. Finally, some Gromacs modules were used to analyze MD trajectories, such as gmx rms, gmxrmsf, and gmxhbond.

3.7. Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA) Analysis

We utilized the g_mmpbsa tool to estimate the binding free energies of the protein-ligand systems [88]. One of the popular methods to estimate the interaction energies are Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA) analysis. This method uses molecular dynamics simulation trajectories to predict binding free energies (ΔEMMPBSA) of protein-protein, protein-ligand, or protein–DNA systems. We performed the MMPBSA analysis on the last 20 ns of the MD trajectory of each protein-ligand system at an interval of 50 ps. Total binding energies of the protein-ligand complexes are presented in Table 1. It can be observed that binding free energies of the chosen compounds with selected targeted proteins alter between different values, owing to differences in the mode of binding. However, the most promising results which can be obtained from this table are those related to binding affinities of stevioside with viral envelope (E) protein (PDB ID: 1OKE), serine protease (NS3) protein (PDB ID: 2VBC), RNA-directed RNA polymerase (NS5) (PDB ID: 4V0Q), and non-structural protein 1 (NS1) (PDB ID: 4O6B).

3.8. Network Pharmacology of Diterpenoid

Three main stages are included in network pharmacology assessment: (a) target estimation for selected bioactive ligands; (b) amplification study for predicted targets, and (c) network construction and analysis for selected ligands, targets, and pathways. Briefly, targets of chosen drugs were predicted using DIGEP-Pred [89] at the pharmacological activity (Pa) of 0.5. Next, the predicted proteins of chosen drugs were enriched using STRING (V.11.0) [90] to generate the protein-protein interaction. All proteins which are obtained from the STRING database were submitted to the Enricher database (https://maayanlab.cloud/Enrichr/, accessed on 9 July 2021) to enrich their biological processes, molecular function cellular components, and KEGG pathways. Finally, the network between chosen drugs, their targets, and pathways was constructed using Cytoscape(V.3.8.2.) [91].

4. Conclusions and Final Considerations

Dengue fever is a severe infectious endemic illness that affects over 100 countries across the globe, from Africa to the Western Pacific. It is caused by DENV, which is transmitted to people by an A. aegypti mosquito bite. Dengue fever and dengue hemorrhagic fever have killed millions of people across the world. Natural phytocompounds have a potential anti-viral effect. Among them, diterpenes/diterpenoids are the most prominent bioactive lead compounds. In this study, among the selected drug candidates, triptolide, stevioside, alepterolic acid, sphaeropsidin, methyl dodovisate, andrographolide, caesalacetal, and pyrimethamine have good to moderate binding affinities compared with the FDA-approved anti-viral medication (pyrimethamine). Our findings will benefit future nonclinical, preclinical, and clinical investigations using these compounds, as well as encourage medicinal chemistry specialists to perform relevant studies on these potential natural lead compounds and their derivatives.

Author Contributions

Conceptualization, R.A.K., R.H., P.B., P.W. and M.T.I.; methodology, R.H., K.A.-K., D.D., A.S.M.S.; software, R.H., K.A.-K., D.D., A.S.M.S.; validation, A.S., A.B.R.K., U.H.A., H.A.C., and M.T.I.; formal analysis, R.H., R.A.K., P.B., A.S.M.S., P.W.; investigation, R.H., K.A.-K., D.D., and A.S.; resources, A.S.M.S., H.A.C., P.W., M.T.I.; data curation, R.H., A.B.R.K., U.H.A., M.T.I.; writing—original draft preparation, R.H., K.A.-K., R.A.K.; writing—review and editing, R.H., A.B.R.K., U.H.A., P.W., M.T.I.; visualization, D.D., R.A.K., P.B.; supervision, P.W., M.T.I.; project administration, H.A.C., P.W.; funding acquisition, A.S., H.A.C., P.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Mahidol University, Bangkok 10400, Thailand (grant number: MU/2001/2021 and MU/20011/2021).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors are very thankful to the International Centre for Empirical Research and Development (ICERD), Bangladesh for mathematical and instrumental support.

Conflicts of Interest

The authors declare no conflict of interest.

Sample Availability

Not applicable.

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Molecules 26 06821 g001 550
Figure 1. The estimated active sites, which make up the amino acids, are shown in the active site identification (red pocket) findings from the CASTp network and structure validation (by Procheck). (A) Viral envelope (E) protein (PDB ID: 1OKE); (B) serine protease (NS3) protein (PDB ID: 2VBC); (C) RNA-directed RNA polymerase (NS5) (PDB ID: 4V0Q); (D) non-structural protein 1(NS1) (PDB ID: 4O6B). [Some errors (letters in Ramachandran plot) are generated by automated software which can’t be changed maually].
Figure 1. The estimated active sites, which make up the amino acids, are shown in the active site identification (red pocket) findings from the CASTp network and structure validation (by Procheck). (A) Viral envelope (E) protein (PDB ID: 1OKE); (B) serine protease (NS3) protein (PDB ID: 2VBC); (C) RNA-directed RNA polymerase (NS5) (PDB ID: 4V0Q); (D) non-structural protein 1(NS1) (PDB ID: 4O6B). [Some errors (letters in Ramachandran plot) are generated by automated software which can’t be changed maually].
Molecules 26 06821 g001
Molecules 26 06821 g002a 550Molecules 26 06821 g002b 550
Figure 2. Summary of physiochemical, pharmacokinetics, and toxicological properties of selected ligand candidates (the color space is a suitable physiochemical space for oral bioavailability; LIPO (Lipophility): –0.7 < XLOGP3 < 5.0; SIZE: 150 g/mol < MW < 500 g/mol; POLAR (Polarity): 20 Å2 < TPSA < 130 Å2; INSOLU (insolubility): 0 < LogS(ESOL) < 6; INSATU (in saturation): 0.25 < FractionCsp3 < 1; FLEX (Flexibity): 0 < Num. rotatable bonds < 9).
Figure 2. Summary of physiochemical, pharmacokinetics, and toxicological properties of selected ligand candidates (the color space is a suitable physiochemical space for oral bioavailability; LIPO (Lipophility): –0.7 < XLOGP3 < 5.0; SIZE: 150 g/mol < MW < 500 g/mol; POLAR (Polarity): 20 Å2 < TPSA < 130 Å2; INSOLU (insolubility): 0 < LogS(ESOL) < 6; INSATU (in saturation): 0.25 < FractionCsp3 < 1; FLEX (Flexibity): 0 < Num. rotatable bonds < 9).
Molecules 26 06821 g002aMolecules 26 06821 g002b
Molecules 26 06821 g003a 550Molecules 26 06821 g003b 550
Figure 3. Binding poses of four top-ranked compounds at the binding site of the dengue virus envelope (E) protein (PDB ID: 1OKE) and 2D and 3D interaction diagrams. (A) triptolide-E protein; (B) stevioside-E protein; (C) alepterolic acid-E protein, and (D) sphaeropsidin A-E protein.
Figure 3. Binding poses of four top-ranked compounds at the binding site of the dengue virus envelope (E) protein (PDB ID: 1OKE) and 2D and 3D interaction diagrams. (A) triptolide-E protein; (B) stevioside-E protein; (C) alepterolic acid-E protein, and (D) sphaeropsidin A-E protein.
Molecules 26 06821 g003aMolecules 26 06821 g003b
Molecules 26 06821 g004a 550Molecules 26 06821 g004b 550
Figure 4. Binding poses of four top-ranked compounds at the binding site of dengue viral NS3 (PDB ID: 2VBC) and 2D and 3D interaction diagrams. (A) Stevioside-NS3; (B)sphaeropsidin A-NS3; (C) methyl dodovisate A-NS3, and (D) caesalacetal-NS3.
Figure 4. Binding poses of four top-ranked compounds at the binding site of dengue viral NS3 (PDB ID: 2VBC) and 2D and 3D interaction diagrams. (A) Stevioside-NS3; (B)sphaeropsidin A-NS3; (C) methyl dodovisate A-NS3, and (D) caesalacetal-NS3.
Molecules 26 06821 g004aMolecules 26 06821 g004b
Molecules 26 06821 g005a 550Molecules 26 06821 g005b 550
Figure 5. Binding poses of four top-ranked compounds at the binding site of dengue virus NS5 (PDB ID: 4V0Q) and 2D and 3D interaction diagrams. (A) Triptolide-NS5; (B) stevioside-NS5; (C) caesalacetal-NS5; (D) andrographolide-NS5.
Figure 5. Binding poses of four top-ranked compounds at the binding site of dengue virus NS5 (PDB ID: 4V0Q) and 2D and 3D interaction diagrams. (A) Triptolide-NS5; (B) stevioside-NS5; (C) caesalacetal-NS5; (D) andrographolide-NS5.
Molecules 26 06821 g005aMolecules 26 06821 g005b
Molecules 26 06821 g006a 550Molecules 26 06821 g006b 550
Figure 6. Binding poses of four top-ranked compounds at the binding site of dengue virus NS1 (PDB ID: 4O6B) and 2D and 3D interaction diagrams. (A) Triptolide-NS1; (B) stevioside-NS1; (C)sphaeropsidin A-NS1; (D) caesalacetal-NS1.
Figure 6. Binding poses of four top-ranked compounds at the binding site of dengue virus NS1 (PDB ID: 4O6B) and 2D and 3D interaction diagrams. (A) Triptolide-NS1; (B) stevioside-NS1; (C)sphaeropsidin A-NS1; (D) caesalacetal-NS1.
Molecules 26 06821 g006aMolecules 26 06821 g006b
Molecules 26 06821 g007a 550Molecules 26 06821 g007b 550
Figure 7. Interaction of reference drugs (pyrimethamine; IUPAC name: 5-(4-chlorophenyl)-6-ethylpyrimidine-2,4-diamine-chloridine) with dengue virus protein. (A) Envelope (E) protein (PDB ID: 1OKE); (B) NS3 (PDB ID: 2VBC); (C) NS5 (PDB ID: 4V0Q); (D) NS1 (PDB ID: 4O6B).
Figure 7. Interaction of reference drugs (pyrimethamine; IUPAC name: 5-(4-chlorophenyl)-6-ethylpyrimidine-2,4-diamine-chloridine) with dengue virus protein. (A) Envelope (E) protein (PDB ID: 1OKE); (B) NS3 (PDB ID: 2VBC); (C) NS5 (PDB ID: 4V0Q); (D) NS1 (PDB ID: 4O6B).
Molecules 26 06821 g007aMolecules 26 06821 g007b
Molecules 26 06821 g008a 550Molecules 26 06821 g008b 550
Figure 8. The RMSD plot for the backbone atoms for (A) 1OKE; (B) 2VBC; (C) 4O6B, and (D) 4V0Q.
Figure 8. The RMSD plot for the backbone atoms for (A) 1OKE; (B) 2VBC; (C) 4O6B, and (D) 4V0Q.
Molecules 26 06821 g008aMolecules 26 06821 g008b
Molecules 26 06821 g009a 550Molecules 26 06821 g009b 550
Figure 9. The RMSF plot for the backbone atoms for (A) 1OKE, (B) 2VBC, (C) 4O6 Band (D) 4V0Q.
Figure 9. The RMSF plot for the backbone atoms for (A) 1OKE, (B) 2VBC, (C) 4O6 Band (D) 4V0Q.
Molecules 26 06821 g009aMolecules 26 06821 g009b
Molecules 26 06821 g010 550
Figure 10. The hydrogen bonds plot between selected compounds with (A) 1OKE; (B) 2VBC; (C) 4O6B, and (D) 4V0Q.
Figure 10. The hydrogen bonds plot between selected compounds with (A) 1OKE; (B) 2VBC; (C) 4O6B, and (D) 4V0Q.
Molecules 26 06821 g010
Molecules 26 06821 g011 550
Figure 11. Gene ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the selected genes (performed via enricher) (A) GO Biological Process 2018; (B) GO Molecular Function 2018; (C) GO Cellular Component 2018; (D) KEGG 2019.
Figure 11. Gene ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the selected genes (performed via enricher) (A) GO Biological Process 2018; (B) GO Molecular Function 2018; (C) GO Cellular Component 2018; (D) KEGG 2019.
Molecules 26 06821 g011
Molecules 26 06821 g012 550
Figure 12. Drug-targets-pathway networks.
Figure 12. Drug-targets-pathway networks.
Molecules 26 06821 g012
Table
Table 1. ADMET and drug likeliness properties for molecules.
Table 1. ADMET and drug likeliness properties for molecules.
PropertiesTriptolideSteviosideAlepterolicAcidSphaeropsidin AMethyl DodovisateAAndrographolideCaesalacetalPyrimethamine
FormulaC20H24O6C38H60O18C20H32O3C20H26O5C22H28O2C20H30O5C21H28O5C12H13ClN4
Molecular weight (g/mol)360.40804.87320.47346.42324.46350.45360.44248.71g/mol
H-Bond Acceptors618352552
H-Bond Donors111220312
Num. Rotatable Bonds110415322
TPSA (Å2)84.12294.9857.5383.8326.3086.9968.9077.82
Fraction Csp30.850.920.750.700.500.750.760.17
Molar Refractivity88.54188.2695.4991.95100.1895.2195.3071.06
LogPo/w (XLOGP3)0.22−1.204.742.645.312.163.082.69
LogS (ESOL)−2.15−3.41−4.55−3.58−4.87−3.18−4.03−3.47
Max. tolerated dose (human) (logmg/kg/day)−0.321−1.524−0.297−0.074−0.1590.128−0.140.113
Oral Rat Acute Toxicity (LD50; mol/kg)3.1072.5972.281.921.7792.1622.5812.912
HepatotoxicityNoNoNoNoNoNoYesNo
Minnow toxicity (logmM)1.9839.2020.4591.606−0.5251.370.4180.919
Blood brain barrier (logBB)−0.362−2.029−0.0180.0160.629−0.598−0.1630.278
HIA (%)83.195094.67295.75397.80895.35797.56492.738
CaCo2 Permeability0.401−1.0871.4321.1351.641.071.1450.927
Total Clearance
(logml/min/kg)		0.4840.6911.1220.5411.3811.1830.538−0.033
Table
Table 2. The four best results for the docking of natural bioactive ligands with viral envelope (E) protein (PDB ID: 1OKE) proteins target.
Table 2. The four best results for the docking of natural bioactive ligands with viral envelope (E) protein (PDB ID: 1OKE) proteins target.
CompoundsTargetInteract ResiduesNo. of H-BondH-Bond ResiduesH-Bond LengthBinding Energy (kcal/mol)
Triptolide1OKELeu253
Thr236
Thr262		1Thr2651.76−8.1
SteviosideAla259
Ala263
Trp212		2Gln256
Hios209		2.09
2.16		−8.4
Alepterolic acidLeu253
Pro217		2Gln256
Thr265		2.31
1.87		−8.3
Sphaeropsidin
A		His261
Thr265
Trp206		0--−8.7
Table
Table 3. The four best results for the docking of natural bioactive ligands with viral proteins target.
Table 3. The four best results for the docking of natural bioactive ligands with viral proteins target.
CompoundsTargetInteract ResiduesNo. of H-BondH-Bond ResidueH-Bond LengthBinding Energy (kcal/mol)
Stevioside Asp192
Ile203
Met191
His194		7Arg202
Asn175
Glu173
Glu177
Gly198
His194
Pro174		2.33
2.29
1.96
2.59
2.17
2.39
2.60		−8.0
Sphaeropsidin A2VBCAla197
Ile203
Leu193		1Asp1752.57−8.3
Methyldodovisate A Asp258
Arg215
Arg217
His251
Ile256		3Arg254
Gly253
Thr252		2.17
2.17
2.94		−9.2
Caesalacetal Ala197
His194
Leu193		1Asp1752.59−8.0
Table
Table 4. The four best results for the docking of natural bioactive ligands with viral NS5 proteins target.
Table 4. The four best results for the docking of natural bioactive ligands with viral NS5 proteins target.
CompoundsTargetInteract ResiduesNo. of H-BondH-Bond ResiduesH-Bond LengthBinding Energy (kcal/mol)
Triptolide Glu356
Gly258
His52
Tyr119
Val687		2Ala259
Arg540		2.28
3.10		−8.8
Stevioside4V0QAsp663
Ile797		3Lys401
Ser661
Ser710		2.23
2.83
2.53		−9.4
Andrographolide Ile797
Val603		4Asp663
Gly604
Thr605
Tyr606		2.25
2.39
2.56
1.82		−8.4
Caesalacetal Cys82
Gly148
Ile147
Trp87		4Arg84
Asp146
Gly85
Gly86		2.63
2.36
2.29
2.25		−8.4
Table
Table 5. The four best results for the docking of natural bioactive ligands with viral proteins target (NS1).
Table 5. The four best results for the docking of natural bioactive ligands with viral proteins target (NS1).
CompoundsTargetInteracting ResiduesNo. of
H-Bond		H-Bond ResidueBond Length
(A)		Binding Energy (Kcal/mol)
Triptolide Lys174
Phe178
Pro226		3Lys227
Ser181
Ser227
2.28
2.52
2.69		−8.3
Stevioside Lys174
Lys227
Phe178
Pro226		5Asn234
Asp176
Glu154
Ser181
Trp232		2.72
2.41
1.99
2.14
2.06		−9.3
Sphaeropsidin A4O6BLys172
Lys227
Phe178
Pro226
Trp232		2Asp176
Ser181		2.21
2.16		−8.5
Caesalacetal Glu173
Lys227
Phe178
Ser181
Trp232		2Ser228
Trp210		2.33
2.39		−8.5
Table
Table 6. Results for the docking of pyrimethamine with all four dengue viral protein target proteins.
Table 6. Results for the docking of pyrimethamine with all four dengue viral protein target proteins.
CompoundsTargetInteracting ResiduesNo. of H-BondH-Bond ResidueBond Length (Å)Binding Energy
(kcal/mol)
PyrimethamineE protein
(1OKE)		Asp203
Lys202
Lys204
Val252		5Glu257
His261
Met201		2.55
2.60
2.44		−7.5
NS3(2VBC)Tyr3546Asp469
Asp470
Gln471
Glu468		2.15
2.83
2.56
2.63		−6.3
NS5(4V0Q)Arg352, Arg581,
Asn297, Lys355, Pro298,
Val66		3Glu296
Asn69
Glu351		2.04
2.60
2.55		−7.8
NS1(4O6B)Phe178
Ser181		3Asp176
Asp180
Cys179		2.32
2.42
2.43		−6.6
Table
Table 7. Calculation of MMPBSA energy (ΔEMMPBSA) of the selected proteins and the nominated ligands.
Table 7. Calculation of MMPBSA energy (ΔEMMPBSA) of the selected proteins and the nominated ligands.
Target NameCompound NameVander Waals Energy (kJ/mol)Electrostatic Energy
(kJ/mol)		Polar Solvation Energy (kJ/mol)SASA Energy (kJ/mol)Binding Energy
(kJ/mol)
1OKENative−96.764314.382−253.72332.344−3.761
Alepterolicacid−88.371−14.15968.7155−12.475−46.2895
SphaeropsidinA−122.068−5.75671.871−14.922−70.875
Stevioside−83.430−12.41073.405−11.170−33.605
Triptolide−130.551−13.74266.847−13.472−90.918
2VBCNative−149.888−15.82187.180−16.847−94.556
Caesalacetal−148.616−24.435104.966−16.718−84.309
MethyldodovisateA−138.175−14.924118.165−14.918−49.852
SphaeropsidinA−115.1833.98243.248−13.188−81.141
Stevioside−195.236−22.923144.028−22.388−96.519
4O6BNative−60.911−32.86989.094−9.556−14.602
Caesalacetal−139.283−33.11781.796−13.614−104.281
SphaeropsidinA−90.141−8.12543.680−9.868−64.454
Stevioside−162.844−110.614151.263−22.976−145.171
Triptolide−116.724−75.279100.616−13.566−104.953
4V0QNative−135.681−41.363131.823−14.601−59.822
Andrographolide−0.0364.88158.619−2.89360.571
Caesalacetal−108.4933.61035.992−12.449−81.34
Stevioside−270.746−68.928236.892−28.205−130.987
Triptolide−178.301−24.621210.824−19.300−11.398
Table
Table 8. Diterpenes/diterpenoids and their derivatives with bioactivity against DENV and DENV-infected experimental animals or cell lines.
Table 8. Diterpenes/diterpenoids and their derivatives with bioactivity against DENV and DENV-infected experimental animals or cell lines.
CompoundsSourcePubChem IDChemical Structure
Phorbol esterJatropha curcas22833501 Molecules 26 06821 i001
TriptolideTripterygium wilfordii107985 Molecules 26 06821 i002
SteviolStevia rebaudiana452967 Molecules 26 06821 i003
FerruginolPrumnopitys andina442027 Molecules 26 06821 i004
18-oxoferruginolTorreya nucifera52946772 Molecules 26 06821 i005
AndrographolideAndrographis paniculata5318517 Molecules 26 06821 i006
SteviosideStevia rebaudiana442089 Molecules 26 06821 i007
Rebaudioside AStevia rebaudiana Bertoni6918840 Molecules 26 06821 i008
ForskolinColeus forskohli47936 Molecules 26 06821 i009
Ent-kaur-16-en-19-oic acidElaeoselinum foetidum73062 Molecules 26 06821 i010
9(11),16-kauradien-19-oic acidMelantheria albinervia14635430 Molecules 26 06821 i011
Alepterolic acidCopaifera reticulata13858188 Molecules 26 06821 i012
Zanzibaric acidHymenaea courbaril101289556 Molecules 26 06821 i013
Isoozic acidHymenaea courbaril100983062 Molecules 26 06821 i014
Sphaeropsidin ADiplodia cupressi51361447 Molecules 26 06821 i015
PhytolHierochloëo dorata5280435 Molecules 26 06821 i016
7-oxo-8,11,13-cleistanthatrien-3-olV. gigantea132609177 Molecules 26 06821 i017
Methyl dodovisate AHierochlo ëodorata146156767 Molecules 26 06821 i018
CaesalacetalCaesalpinia decapetala var.132918611 Molecules 26 06821 i019
CaesaljapinCaesalpinia decapetala var.6712179 Molecules 26 06821 i020
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Khan, R.A.; Hossain, R.; Siyadatpanah, A.; Al-Khafaji, K.; Khalipha, A.B.R.; Dey, D.; Asha, U.H.; Biswas, P.; Saikat, A.S.M.; Chenari, H.A.; et al. Diterpenes/Diterpenoids and Their Derivatives as Potential Bioactive Leads against Dengue Virus: A Computational and Network Pharmacology Study. Molecules 2021, 26, 6821. https://doi.org/10.3390/molecules26226821

AMA Style

Khan RA, Hossain R, Siyadatpanah A, Al-Khafaji K, Khalipha ABR, Dey D, Asha UH, Biswas P, Saikat ASM, Chenari HA, et al. Diterpenes/Diterpenoids and Their Derivatives as Potential Bioactive Leads against Dengue Virus: A Computational and Network Pharmacology Study. Molecules. 2021; 26(22):6821. https://doi.org/10.3390/molecules26226821

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Khan, Rasel Ahmed, Rajib Hossain, Abolghasem Siyadatpanah, Khattab Al-Khafaji, Abul Bashar Ripon Khalipha, Dipta Dey, Umma Hafsa Asha, Partha Biswas, Abu Saim Mohammad Saikat, Hadi Ahmadi Chenari, and et al. 2021. "Diterpenes/Diterpenoids and Their Derivatives as Potential Bioactive Leads against Dengue Virus: A Computational and Network Pharmacology Study" Molecules 26, no. 22: 6821. https://doi.org/10.3390/molecules26226821

APA Style

Khan, R. A., Hossain, R., Siyadatpanah, A., Al-Khafaji, K., Khalipha, A. B. R., Dey, D., Asha, U. H., Biswas, P., Saikat, A. S. M., Chenari, H. A., Wilairatana, P., & Islam, M. T. (2021). Diterpenes/Diterpenoids and Their Derivatives as Potential Bioactive Leads against Dengue Virus: A Computational and Network Pharmacology Study. Molecules, 26(22), 6821. https://doi.org/10.3390/molecules26226821

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