Activity Prediction of Bioactive Compounds Contained in Etlingera elatior Against the SARS-CoV-2 Main Protease: An In Silico Approach

Coronavirus disease 2019 (COVID-19) is a disease caused by infection with the SARS-CoV-2 virus, which in January 2020 began to spread from Wuhan around the world (Hui et al., 2020). Globally, on August 30th 2020, there have been 24,854,140 confirmed cases of COVID-19, including 838,924 deaths (World Health Organization, 2020). One of the targets that have become a focus of research in the world for COVID-19 therapy was SARSCoV-2 main protease (MPro) (Dai et al., 2020; Jin et al., 2020; Wu et al., 2020; Zhu et al., 2011). The main protease is a key enzyme in the viral replication cycle, which proteolytically cleaves overlapping polyproteins pp1a and pp1ab into functional proteins, an essential step during viral replication (Du et al., 2004). Inhibition of these target proteins can result in disruption of the SARS-CoV2 replication cycle (Mahmud et al., 2020; Pratama et al., 2020). The SARS-CoV-2 MPro in COVID-19 is not the same as the main protease in humans, so it becomes a promising therapeutic target (Ullrich & Nitsche, 2020). Many compounds derived from medicinal plants have not been discovered and have great potential as therapeutic candidates (Mushtaq et al., 2018; Pan et al., 2013). In the discovery of COVID-19 therapy candidates, many natural products were used; some of them examined compounds from herbs against the SARSCoV-2 using in silico method (Aanouz et al., 2020; Enmozhi et al., 2020; Joshi et al., 2020; Prasanth et al., 2020; Sukardiman et al., 2020). However, the discovery of Activity Prediction of Bioactive Compounds Contained in Etlingera elatior Against the SARS-CoV-2 Main Protease: An In Silico Approach


INTRODUCTION
Coronavirus disease 2019 (COVID-19) is a disease caused by infection with the SARS-CoV-2 virus, which in January 2020 began to spread from Wuhan around the world (Hui et al., 2020). Globally, on August 30 th 2020, there have been 24,854,140 confirmed cases of COVID-19, including 838,924 deaths (World Health Organization, 2020). One of the targets that have become a focus of research in the world for COVID-19 therapy was SARS-CoV-2 main protease (M Pro ) (Dai et al., 2020;Jin et al., 2020;Wu et al., 2020;Zhu et al., 2011). The main protease is a key enzyme in the viral replication cycle, which proteolytically cleaves overlapping polyproteins pp1a and pp1ab into functional proteins, an essential step during viral replication (Du et al., 2004). Inhibition of these target proteins can result in disruption of the SARS-CoV-2 replication cycle (Mahmud et al., 2020;Pratama et al., 2020). The SARS-CoV-2 M Pro in COVID-19 is not the same as the main protease in humans, so it becomes a promising therapeutic target (Ullrich & Nitsche, 2020).
Many compounds derived from medicinal plants have not been discovered and have great potential as therapeutic candidates (Mushtaq et al., 2018;Pan et al., 2013). In the discovery of COVID-19 therapy candidates, many natural products were used; some of them examined compounds from herbs against the SARS-CoV-2 using in silico method (Aanouz et al., 2020;Enmozhi et al., 2020;Joshi et al., 2020;Prasanth et al., 2020;Sukardiman et al., 2020). However, the discovery of compounds from medicinal plants with potential activity as SARS-CoV-2 M Pro inhibitors is still being carried out today.
Etlingera elatior (known as Wualae in Tolakinese) is a medicinal plant from Indonesia which are found mainly on the island of Sulawesi, particularly Southeast Sulawesi (Fristiohady et al., 2020;Fristiohady et al., 2019). Etlingera elatior contains various types of compounds, including flavonoids and steroids with various pharmacological activities, one of them as antimicrobial Wahyuni et al., 2018). However, there has been no specific development of its antiviral activity until now, especially to the SARS virus family. Flavonoid and steroid group compounds as found in E. elatior have been widely researched on their activity to the SARS-CoV-2 and have shown promising results as a drug candidate for COVID-19 Suwannarach et al., 2020).
Therefore, this study aims to identify compounds from the flavonoid and steroid group contained in E. elatior, which have potential as SARS-CoV-2 M Pro inhibitors.

Ligand preparation
The ligands used in this study were compounds contained in E. elatior. A total of seven compounds contained in E. elatior were selected in this study based on the KNApSAcK database (http://www.knapsackfamily.com/KNApSAcK/) (Afendi et al., 2012). The compound identity, as well as their two-dimensional structure, can be seen in Table I.

Receptor preparation
The three-dimensional structure of the SARS-CoV-2 M Pro was obtained from the Protein Data Bank (PDB) website http://www.rcsb.org/pdb/. The receptor with the PDB ID 6LU7 and resolution 2.16 Å was chosen. Furthermore, the unique ligands and water molecules were removed from the receptor. Then, the receptor was added with polar hydrogen and given a charge (Kollman charge). All preparation procedures were performed using AutoDock 4 software (Morris et al., 2009).

Validation method
The native ligand from the 6LU7 receptor (N-[(5- yl]methyl}but-2-enyl)-l-leucinamide; an inhibitor N3)  was separated from the protein, then redocked using AutoDock 4 software into the previous active site. The native ligand conformation from the docking procedure was taken and overlayed with the native ligand conformation before docking.
Furthermore, validation is done by looking at root-meansquare deviation (RMSD) parameters, calculated using PyMOL software. An RMSD value of fewer than 2.0 Å indicates that the method is valid and can be used for the docking process (Bell & Zhang, 2019).

Molecular docking simulation
The simulation was carried out using previously valid

Prediction of Activity Spectra for Substances
The in silico Prediction of Activity Spectra for Substances (PASS) were carried out to get biological activity spectra of compounds accessed through PASS web server (http://www.way2drug.com/PASSOnline/predict.ph p) (Marwaha et al., 2007). This server estimates the predicted activity spectrum of a compound as probable activity (Pa) and probable inactivity (Pi). Prediction of this spectrum by PASS is based on structure-activity relationship analysis of the training set containing more than 205,000 compounds exhibiting more than 3,750 kinds of biological activities. For probabilities range, the Pa and Pi values vary from 0.000 to 1.000. The PASS prediction results were interpreted and used flexibly: 1. Only activities with Pa > Pi are considered as possible for a particular compound.
2. If Pa >0.7, the chance to find activity is experimentally high.
3. If Pa is >0.5 but less than <0.7, the chance to find activity is experimentally low, but the compound is probably different from known pharmaceutical agents.
4. If Pa <0.5, the chance to find activity is experimentally is low, but the chance to find structurally NCE's is high.

Validation method
Validation was carried out to see the strength of affinity prediction through re-docking the native ligand into its binding site. The validation results can be seen in Figure   1. It showed that the RMSD value of the native ligand was 1.3 Å, with the binding energy obtained was -7.30 kcal/mol. This shows that the molecular docking method used is valid because of the RMSD value below 2.0 Å.

Molecular docking simulation
The bioactive compounds in E. elatior after docked showed varied binding energies as shown in Table II Meanwhile, the type of steroid has been previously studied by Ghosh et al. (2020). As shown by the docking results in Table II, the steroid group showed better inhibitory activity than the flavonoid groups to SARS-CoV-2 M Pro receptor. The docking results show that the steroids' binding energy, namely ergosterol peroxide and sitostenone, was -10.4 and -9.17 kcal/mol, respectively.
Compared to the flavonoid group, the lowest binding energy was shown by catechins (-8.64 kcal/mol), while the binding energy of the other compounds was in the range of -6.53 to -7.9 kcal/mol.

Molecular interactions
The top two compounds that ranked by their binding energy, ergosterol peroxide and sitostenone, were analyzed for their amino acid interactions with the SARS-CoV-2 M Pro receptor and compared with the interactions of the native co-crystal ligand (N3 inhibitor). The interactions' tabulation data can be seen in Table III, while the two-dimensional interaction can be seen in  Gln-189  Gln

Prediction of Activity Spectra for Substances
The PASS prediction was carried out on native ligand, ergosterol peroxide, and sitostenone compounds to see and compare their probability level as COVID-19 therapy (  Moreover, from the molecular docking simulation, ergosterol peroxide and sitostenone showed better affinity against SARS-CoV-2 M Pro compared to flavonoid groups and the native ligand.