INTRODUCTION:

Since the beginning of the 21st century, coronavirus have repeatedly caused pneumonia pandemic in humans. This condition was started in 2002-2003 by Severe acute respiratory syndrome coronavirus (SARS-CoV), then in 2012 by Middle-East respiratory syndrome coronavirus (MERS-CoV), and finally in 2019 to this date by Severe Acute Respiratory Syndrome Coronavirus 2 ( SARS-CoV-2). SARS-CoV-2 is the virus that causes the 2019 Coronavirus Disease (COVID-19), which has been declared a pandemic in several countries in the world, especially in Indonesia. This novel coronavirus has never been previously identified in humans^1,2.

The number of cases increased and spread to various countries in a short time. Thailand is the first country outside China to report a case of COVID-19. After Thailand, the next countries that reported the first cases of COVID-19 were Japan and South Korea, which later spread to other countries. As of June 30, 2020, WHO reported 10,185,374 confirmed cases with 503,862 deaths worldwide (Case Fatality Rate/CFR of 4.9%), while on July 9, 2020, WHO reported 11, 84, 226 confirmed cases with 545,481 deaths worldwide (CFR of 4.6%).

Indonesia reported its first case of COVID-19 on March 2, 2020. As of November 30, 2020, the Ministry of Health reported 538,883 confirmed cases of COVID-19 with 16,945 total deaths spread across all provinces. Most cases occurred in the age range of 45-54 years and the least occurred at the age of 0-5 years. The highest mortality rate was found in patients aged 55-64².

Up to this point, COVID-19 remains a very high risk at the global and national levels. While the vaccine is still under development, the world is required to prepare to coexist with COVID-19. The mortality rate of this disease is relatively high since it potentially causes various complications such as severe pneumonia, acute respiratory distress syndrome (ARDS), pulmonary edema, septic shock, and organ failure, thereby increasing the mortality rate of those infected².

An optimal immune system is required for self-protection against the eradication of COVID-19. However, the immune system of COVID-19 patients in some cases works inappropriately, and it actually worsens patient outcomes. COVID-19 patients usually experience an inflammatory process to activate and strengthen the immune system to fight the virus.

However, this activation process in certain cases becomes excessive and uncontrolled, causing a condition known as the cytokine storm. This condition results from excessive release of proinflammatory cytokines, especially interleukin 6 (IL-6), a 'vicious circle' experienced by COVID-19 patients.

The formation of IL-6 in cells occurs through the activation of NFB; a transcription factor activated when IL-6R binds to IL-6. Once activated, NFκB will trigger the formation of new IL-6 so that the number increases significantly, and this process repeats. Tumor Necrosis Factor α (TNFα) also plays a crucial role in this process by increasing the activation of NFκB. The process involving this pathway has been widely studied to prevent the occurrence of cytokine storm^3,4. Cytokine storm and ARDS are the main causes of death from this disease. To the point when this study was conducted, no evidence-based definitive therapy for COVID-191 had been found^,2,5.

Consumption of healthy food/drink is one of the means to boost the immune system and prevent COVID-19 infection. One of the plants that can be processed into healthy food/drink is Saussurea costus. This plant belongs to the Asteraceae family and grows in various parts of the world, especially in India, Pakistan and the Himalayas. This plant contains active ingredients that can serve as anti-inflammatory, antitumor, antibacterial, antiseptic, antifungal agents, etc. In a previous in vivo study, Saussurea costus combined with honey and Nigella sativa was shown to trigger an immune response with the difference in the number of Th2 and Th17 immune cells more than control immune cells⁶. Despite the numerous benefits this plant has to offer, studies on the role of the active ingredients as an anti-inflammatory agent to treat COVID-19, prevent cytokine storms, and improve COVID-19 patient outcomes are rarely found. Therefore, in this study, an in silico experiment was conducted on the effect of the active ingredients of Saussureacostus on the pathophysiological (hyperinflammatory) process of COVID-19 process as the main cause of this disease morbidity and mortality.On that ground, the potential of this plant to be utilized in COVID-19 therapy is expected to be identified.

METHOD:

Preparation of Samples

According to the literature research, Saussurea costus contains 75 chemical compounds acting as active ingredients. Five of these chemical compounds were selected to be utilized as ligands in this study, namely isoalantolactone (CID 73285), isozaluzanin c (CID 470970), arbusculin a (CID 160153), β-costic acid (CID 12304100), and picriside B (CID 21636024). The five compounds belong to the sesquiterpenes group⁶. The PubChem database (https://pubchem.ncbi.nlm.nih.gov/) was utilized in this study for the preparation of the ligand samples. The information obtained consisted of CID, molecular weight, molecular formula, smile canonical, and 3D structure of the ligand samples in structure data format (SDF). The target proteins utilized in this study were IL-6R (PDB code: 1N26), NFKB1 (PDB code: 2O61), and TNFR1 (PDB code: 1EXT). The 3D structures of the target proteins were obtained from the RCSB database (https://www.rcsb .org/) and downloaded in protein databank (GDP) format.

The ligand samples were minimized before undergoing the molecular docking simulation process to obtain a 3D structure in PDB format and increase the flexibility of the structure⁸. The minimization process of the ligands was performed through the OpenBabel plugin on PyRx 0.8. The target proteins from the native ligands and water molecules were then sterilized to increase the effectiveness of the binding energy formed on the molecular complex as a result of molecular docking simulation^9,10.

Prediction results of biological activities of Saussurea costus active ingredients

The biological activities of the drug candidate compounds as anti-inflammatory and immunosuppressant agents in this study were predicted through the PASSOnline database server (http://www.pharmaexpert.ru/passonline/)¹¹.http://www.pharmaexpert.ru/passonline/ This server served to identify a chemical compound through SMILE Canonical readings to obtain the predicted probability activation (Pa) and protease inhibitor (Pi) scores. This study applied the principle of medium confidence, namely Pa > 0.3, in which screening for the potential natural material according to the research objectives was only proven in silico^12,13.

Druglikeness Analysis:

This prediction aimed to determine whether a molecule could be categorized as a drug molecule or not by referring to certain rules^14,15. This study applied Lipinski's rule (http://www.scfbio-iitd.res.in/software/drugdesign/lipinski.jsp) to determine whether a molecule was a good drug candidate or not. The drug candidate compounds shall meet at least two of the five criteria in Lipinski's rule^16,17.

Molecular Docking:

The Molecular docking simulation aimed to interact molecules with one another to obtain a large binding energy formed¹⁸. The binding energy values depicted the influence level of the ligands on the target protein activities. In this study, the level of these values was utilized to determine the inhibitory nature of the ligands on the target proteins^19,20. This study applied blind docking to screen the potential compounds of the natural ingredients without using control and functional aspects of the proteins but referring to the most negative ligand binding^21,22. The open source PyRx 0.8 software (https://pyrx.sourceforge.io/) was utilized for the molecular docking simulation in this study.

Data Analysis:

LigPlot+ was utilized in this study (https://www.ebi.ac.uk/thornton-srv/software/LIGPLOT/) to identify the type of chemical interaction formed and the binding position of the ligands to the domain of the target proteins²³. The complex interaction of the ligand and the target protein molecules included weak bonds, namely hydrophobic, Van der Waals, electrostatic, hydrogen, and alkyl interactions^24,25. However, this software was able to identify only the type of hydrogen bonding and hydrophobic interactions²⁶.

The docked molecular complex was displayed in PyMol with 3D structures consisting of surfaces, cartoons, and sticks²⁷. Staining selection was also conducted in this study to obtain the representative appearance of and clarify the specific functional parts of the proteins and ligands^27,28.

DISCUSSION:

In COVID-19 patients, cytokine storm results from a significant increase in IL-6 and TNF levels, and this process is closely related to ARDS severity and patient outcomes. Therefore, IL-6 and TNF are potential targets for preventing cytokine storms in COVD-19 patients^29,30. One of the methods to inhibit IL-6 multiplication is the administration of tocilizumab, an anti-IL-6R monoclonal antibody. This way, it is expected that IL-6 signaling through the NFΚB pathway does not occur and thereby prevents cytokine storms. Interestingly, the administration of tocilizumab has been proven to reduce the need for mechanical ventilation, improve oxygenation, and prevent lung damage in severe COVID-19 patients^31,32. Besides, TNF is a pro-inflammatory cytokine, which is considered to also play a role in causing cytokine storms in COVID-19 patients. TNF plays a role in initiating inflammatory pathways, including the production of IL-6. In addition, increased TNF also plays a role in coagulation disorders, which are also the cause of thrombosis and ARDS^33,34. A previous study suggested that the administration of anti-TNF drugs was able to improve the outcome and survival of patients with confirmed COVID-19³⁵. On that ground, TNF-blockers are also suitable for use in treating COVID-19 patients. The inhibition of NFκB in COVID-19 patients has not been widely studied. However, an in vivo study revealed that the inhibition of NFκB in mice with confirmed SARS-CoV infection increased the survival rate. It also decreased the level of other proinflammatory cytokines, prevented hyperinflammatory conditions, and improved patient outcome^36,37.

Table 1 Prediction results of biological activities of Saussurea costus active ingredients on PASSOnline

Chemical Compounds	Antiinflammatory agent		Immunosuppressant agent
Chemical Compounds	Pa	Pi	Pa	Pi
Isoalantolactone	0.826	0.005	0.611	0.028
Isozaluzanin C	0.807	0.006	0.503	0.042
Arbusculin A	0.765	0.009	0.571	0.033
β-costic acid	0.725	0.013	0.717	0.015
Picriside B	0.769	0.009	0.710	0.015

Pa: Probabillity Activation; Pi: Probabillity Inhibition

In this in silico study, Saussurea costus compounds were analized and five of which showed the greatest potential as the drug candidates, namely isoalantolactone, isozaluzanin C, arbusculin a, β-costic acid, and picriside B. These five active compounds were selected after testing the biological activity prediction and Lipinski's prediction. In addition, the data availability and comprehensiveness of these five compounds in the database were also the determinants for selecting these compounds.

The analysis results signified that according to the predicted probability with medium confidence (Pa > 0.3), all of the drug candidate compounds of Saussurea costus in silico indicated biological activities as anti-inflammatory and immunosuppressant agents (Tabel 1). These five compounds were then utilized as ligands for the target proteins (IL-6R, NFKB1, and TNFR1), which are on the main axis of the cytokine storms in COVID-19 patients.

Table 2 Lipinski's prediction results

Chemical Compounds	MW	LogP	HBD	HBA	MR
Isoalantolactone	232.000	3.240	0	2	66.331
Isozaluzanin C	246.000	1.987	1	3	67.627
Arbusculin A	250.000	2.435	1	3	67.815
β-costic acid	312.000	-0.053	5	6	77.145
Picriside B	410.000	0.347	4	8	102537

MW: Molecular weight; LogP: High lipophilicity; HBD: Hydrogen bond donor; HBA: Hydrogen bond acceptors; MR: Molar refractivity

These drug candidate compounds shall meet at least two of the five criteria in Lipinski's rule, including: the molecular weight shall be lower than 500 Daltons; the lipophilicity (LogP) shall be lower than five; the donor hydrogen bonds shall be lower than five; the hydrogen bond of the acceptor shall be lower than ten; and the molar refractivity value shall range between 40 to 130^14,16. The analysis results of the drug candidate compounds of Saussurea costus indicated a positive prediction that all of these compounds could be categorized as drug-like molecules (Table 2).

Tabel 3 Molecular docking simulation scores

Chemical Compounds	Binding Affinity (kcal/mol)
Chemical Compounds	IL6R	NFKB1	TNFR1
Picriside B	-6.3	-6.5	-9.0
Arbusculin A	-6.0	-5.6	-7.1
Isozaluzanin C	-5.6	-5.7	-7.4
β-costic acid	-5.7	-5.3	-6.5
Isoalantolactone	-5.5	-5.6	-6.6

The results of the molecular docking analysis in this study indicated that the five selected active compounds in Saussurea costus in this study demonstrated their potential by showing their affinity for the aforementioned target proteins. Among the five active compounds, picriside B had the lowest binding affinity for IL-6R, NFKB1, and TNFR1, with total energies of -6.3 kcal/mol, -6.5 kcal/mol, and -9.0 kcal/mol, respectively (Table 3). In addition, picriside B also demonstrated the most interactions with all of the target proteins. This compound was able to form hydrophobic and hydrogen bonds with the three target proteins (Table 4). The greater the number of chemical bond interactions formed between the ligands and the target proteins, the higher the activity level they produce. Besides, the other four active compounds could be potentially utilized as adjuvant therapy for COVID-19 because these compounds had an affinity for and many chemical bond interactions with the three target proteins.

Figure 1: 3D structure visualization of pricriside B binding to the three target proteins in. The visualization was displayed in the structure of transparent surfaces, cartoons, and sticks.

Furthermore, the molecular docking results in the form of 3D structures were displayed through PyMol with staining and structural selection²⁷. The pricriside B binding to the three displayed proteins according to the docking simulation results was displayed in the structure of transparent surfaces, cartoons, and sticks (Figure 1).

Table 4 Molecular interaction analysis results

Molecular Complex	Position of Interaction and Types of Chemical Bonds
Saussurea costus compounds + IL6R	Picriside B: Hydrophobic (Lys154, Trp115, Lys185, Leu100, Gln187) & Hydrogen (Glu114, 2(Gln99), Gly116, Ser101) Arbusculin A: Hydrophobic (Ser122, Leu123, Tyr148, Phe155, Lys126) & Hydrogen (Thr125) Isozaluzanin C: Hydrophobic (Lys126, Phe155, Thr125, Leu123, Gln150, Tyr148, Gln147) β-costic acid: Hydrophobic (Pro121, Leu123, Tyr148, Gln150, Lys126) & Hydrogen (Ser122, 2(Thr125)) Isoalantolactone: Hydrophobic (Ser156, Phe103, Lys105, Ser224, Ser109, Val112, Glu114)
Saussurea costus compounds + NFKB1	Picriside B: Hydrophobic (Arg54, Gly52, Phe53, His64), Hydrogen (2(Ser240), 2(Lys241), Ser246, 2(Asn247), Lys249) Isozaluzanin C: Hydrophobic (Leu207, Asp206, Asn244, Ser208), Hydrogen (Tyr57, His141) Isoalantolactone: Hydrophobic (Leu207, Lys144, Lys241), Hydrogen (His141) Arbusculin A: Hydrophobic (Glu341, Lys49, Gln50, Arg51), Hydrogen (Thr339, Asn247, Glu338) β-costic acid: Hydrophobic (Tyr57, Ala242, Asp239, Ley207, Ser208, His141, Lys144, Thr143) Hydrogen (Val142)
Saussurea costus compounds + TNFR1	Picriside B: Hydrophobic (Phe112, Asn110, Cys96, Gln82, Lys75, Arg77, Leu111), Hydrogen (2(Asn110), Ser74, 2(Arg77), Gln82) Isozaluzanin C: Hydrophobic (Gln82, Asn110, Cys96, Glu109, Phe112, Thr94, Asp93, Ser74, Asn110) Hydrogen (Ser108, Lys75) Arbusculin A: Hydrophobic (Arg77, Lys75, Gln82, Cys96, Ser74, Lys75) Hydrogen (2(Asn110), 2(Arg77)) Isoalantolactone: Hydrophobic (Ser74, Arg77, Lys75, Cys96, Asn110, Phe112, Gln82, Asn110) β-costic acid: Hydrophobic (Lys75, Phe112, Asn110, Arg77, Ser74, Gln82, Asn110, Ser74, Val95) Hydrogen (Cys96, Thr94)

This results indicated that all of the ligands were able to form hydrophobic and hydrogen bond interactions, with the highest number of interactions generated by pricriside B (Table 4). The pricriside B protein-ligand complex with all of the proteins in this study was displayed using PyMol and LigPlot (Figure 2). The number of chemical bond interactions produced by the ligands when they bind to the domain of the target proteins can affect the level of activity they produces²⁸. Therefore, it is believed that based on the molecular interaction analysis, pricriside B is a good drug candidate because it has more molecular interactions than other compounds.

Figure 2: pricriside B protein-ligand complex with TNFR, NFKB1, and IL6R displayed using PyMol and LigPlot.

CONCLUSION:

Saussurea costus contains 5 active ingredients that potentially become and act as anti-inflammatory agents in silico, namely picriside B, isoalantolactone, isozaluzanin C, arbusculin A, and β-costic acid. This active ingredient has an affinity for IL-6R, TNFR1, and NFκB. This suggests that Saussurea costus has the potential to be utilized in oral anti-inflammatory therapy in treating COVID-19 patients.

ACKNOWLEDGEMENT:

We offer our greatest gratitude to the Division of Molecular Biology and Genetics and the Indonesian Generation Biology Foundation for editing this manuscript.

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Received on 08.06.2022 Modified on 22.07.2022

Research J. Pharm. and Tech 2023; 16(6):2649-2654.

DOI: 10.52711/0974-360X.2023.00435