Large Scale Virtual Screening for Finding Inhibitor against the

RNA-dependent RNA Polymerase from Herbal Medicine for

SARS-Cov-2 Therapy

Xiaogang Liu

, Zirong Liang

, Shiye Wu

, Ying Wang

and Binquan Gou

School of Materials and Environment, Beijing Institute of Technology, Zhuhai, 519000, China

Keywords:

SARS-Cov-2, Rdrp, TCM Database, Molecular Docking, Molecular Dynamics Simulation.

Abstract:

The COVID-19 pandemic caused by SARS-CoV-2 has cause worldwide health concerns. The research on

the virus infection mechanism was carried out and has made some progress. For the SARS-CoV-2

replication, the RNA-dependent RNA polymerase (RdRp) plays an important role and has been proven to be

an effective target. Traditional medicinal plants are widely used in epidemic prevention in China and they

have attracted great attention of scientists. Therefore, we executed large scale virtual screening on the

Traditional Chinese medicinal (TCM) database and hoped to find a potential drug against the virus

polymerase. As a result, we obtained nine non-toxic available compounds derived from TCM database by

docking and ADMET computing. Then 100 ns molecular dynamic was employed to uncover the potential

mechanisms which is helpful for further drug optimazation.

1 INTRODUCTION

A novel coronavirus that caused fatal respiratory

disease was reported at the end of 2019 (Zhu, Zhang,

Wang, Li, Yang, Song, Zhao, Huang, Shi, Lu, 2020).

The main clinical features of this rare virus disease

in the early stages were broadly fever, cough,

headache, diarrhea and loss of taste. As the infection

continues, some patients developed severe

respiratory difficulties, hemoptysis, diarrhea,

multiple-organ failure and death (Achak M, Alaoui

Bakri S, Chhiti Y, M'Hamdi Alaoui FE, Barka N,

Boumya W, 2021). The WHO experts warned that

virus can be spread quickly through close contact by

droplets or aerosols of cough and sneeze (Shereen

MA, Khan S, Kazmi A, Bashir N, Siddique R, 2020)

from an infected individual and has subsequently

named this pathogen 2019-nCoV (Ji, Wang, Zhao,

Zai, Li, 2020). Although government officials and

health experts around the world has implemented

measures to control its spread, the disease remains

https://orcid.org/0000-0002-5853-2005

https://orcid.org/0000-0002-4419-0999

https://orcid.org/0000-0001-5587-5304

https://orcid.org/0000-0002-7780-9372

https://orcid.org/0000-0003-2428-387X

great endemic worldwide. The 2019-nCoV led to

nearly 83 million infections and more than 1.8

million deaths (https://coronavirus.jhu.edu/).

Compared to the 1918 Spanish pandemic,

2019-nCoV spread had a disastrous impact on

human society (Shi, Wang, Shao, Huang, Gan,

Huang, Bucci E, Piacentini M, Ippolito G, Melino G,

2020).

With the help of whole genome sequencing

technology, Scientists have learned much of the

2019-nCoV and identified 2019-nCoV as a new

β-coronavirus (Wu, Zhao, Yu, Chen, Wang, Song,

Hu, Tao, Tian, Pei, 2020). As respiratory infectious

diseases SARS and MERS, the virus cause

respiratory infections in humans and scientists are

referring to it as SARS-CoV-2. The origin of this

virus is uncertain, but there is a definite

understanding of the lifecycle of the virus. The

diameter of the SARS-CoV-2 is 65-125 nm and

coated with glycoprotein on the outside and contains

26 to 32kbs positive-sense RNA inside the virus.

The SARS-CoV-2 infects cells through five typical

stages (Fig.1A). The first stage of the lifecycle is

attachment. With the spike glycoprotein which

recognizes the angiotensin converting enzyme 2 of

human cell, the virus completes the attachment and

enters cells by endocytosis (Luan, Lu, Jin, Zhang,

932

Liu, X., Liang, Z., Wu, S., Wang, Y. and Gou, B.

Large Scale Virtual Screening for Finding Inhibitor against the RNA-dependent RNA Polymerase from Herbal Medicine for SARS-Cov-2 Therapy.

DOI: 10.5220/0011313300003443

In Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics (ICBEB 2022), pages 932-943

ISBN: 978-989-758-595-1

2020). The second stage is membrane fusion. This

process is mediated by cathepsin-L in the endosome,

which promotes activation of spike protein and the

release of RNA. Alternatively, viruses fuse to cell

membranes by the membrane protein TMPRSS2 and

the genome enters the cell in a non-endocytic

pathway (Faheem, Kumar, Sekhar, Kunjiappan,

Jamalis, Balana-Fouce, Tekwani, Sankaranarayanan,

2020). Subsequently, the virus completes replication

and assembly in the host cell. The virus RNA

utilizes host cells ribosomes to synthesize two

polyproteins (pp1a and pp1ab) and four structural

proteins. The polyproteins are split into Nsp1-16

(non-structural proteins) by the papain-like domain

and the main protease contained in itself. Nsp3

contains a papain-like domain which slit

polyproteins at three different positions (Barretto,

Jukneliene, Ratia, Chen, Mesecar, Baker, 2005).

Meanwhile, Nsp5 is known as the main protease

which slit poly-proteins at eleven different positions

(Kumar, Bhardwaj, Kumar, Gehi, Kapuganti, Garg,

Nath, Giri, 2020). Nsp1 is associated with host

immune suppression (Kamitani, Huang, Narayanan,

Lokugamage, Makino, 2009) while the biological

function of the Nsp2 protein is unclear, and

scientists believe that the protein is associated with

the strong infectiousness of SARS (Angeletti,

Benvenuto, Bianchi, Giovanetti, Pascarella,

Ciccozzi, 2020). Nsp4, Nsp3 and Nsp6 are involved

in the formation of double-membrane vesicles

(Angelini, Akhlaghpour, Neuman, Buchmeier, 2013),

and Nsp7 and nsp8 act as co-factors to form

transcriptional complexes with the essential Nsp12,

which is directly involved in the replication of RNA

(Peng, Peng, Yuan, Zhao, Wang, Wang, Wang, Sun,

Fan, Qi, 2020). The Nsp11 is an intrinsically

disordered protein that may plays a critical role in

the interaction between virus and host cell

membrane (Gadhave, Kumar, Kumar, Bhardwaj,

Garg, Giri, 2021). The Nsp13 of the virus contains

three zinc ions and exhibits RNA helicase activity, it

plays a key role in the unwinding double- stranded

RNA when the virus replicate in host cells (Shu,

Huang, Wu, Ren, Zhang, Han, Mu, Wang, Qiu,

Zhang, 2020), which is similar to helicase

super-family-1.Nsp14 is a bifunctional enzyme

containing two structural domains, one for the

3’-5’exonuclease structural domain for RNA

proofreading and the other one is the transferase

active structural domain to produce cap structure of

7-methyl at the 5’-end of RNA guanine-N7 (Snijder,

Bredenbeek, Dobbe, Thiel, Ziebuhr, Poon, Guan,

Rozanov, Spaan, Gorbalenya, 2003). In contrast to

Nsp14, Nsp15 is a ribonucleic acid endonuclease.

Scientists believe that Nsp15 endonuclease activity

facilitates interference to the innate immune

response of the host (Kim, Jedrzejczak, Maltseva,

Wilamowski, Endres, Godzik, Michalska,

Joachimiak, 2020). Nsp16 plays an essential role in

immune evasion (Vithani, Ward, Zimmerman,

Novak, Borowsky, Singh, Bowman, 2020). With the

assistance of the non-structural proteins1-16, viral

replication and assembly are preforming in the

endoplasmic reticulum and Golgi apparatus of the

host cell. The last stage is exocytosis which Viral

particles are released outside the cell in a budding

(Mohanty, Sahoo, Padhy, 2021).

It is obvious that RdRp plays a critical role in the

replication and assembly of the SARS-CoV-2 in the

life cycle. Although the mechanism of RdRp is

unclear, we reconstructed the possible replication

patterns among the Non-structural proteins. It will

have positive implications for antiviral drug

development. The virus replication complex is

composed of three proteins: Nsp7, Nsp8 and Nsp12,

and the primers required in the virus replication

process are provided by Nsp7 and Nsp8 (Romano,

Ruggiero, Squeglia, Maga, Berisio, 2020). Nsp12 is

the critical enzyme that synthesizes viral dsRNA.

The RdRp complex contains six typical domains.

The function of the fingers and thumb domains is to

bind to the template chain. The palm structural

domain cooperates with the finger structural domain

to stabilize the phosphate skeleton, and catalyzes the

synthesis of RNA chains base on the principle of

base pairing (McDonald, 2013). Similar to RNA

family polymerases, the SARS-CoV-2 contains

seven conserved motifs in the palm structural

domain. The catalytic residues which are also

conserved in most viral RdRp is located in the motif

C (Gao, Huang, 2020). NiRAN domains are in close

contact with palm by an interface domain. β-hairpin

and NiRAN domaintogether stabilize the

polymerase structure.

Large Scale Virtual Screening for Finding Inhibitor against the RNA-dependent RNA Polymerase from Herbal Medicine for SARS-Cov-2

Therapy

933

Figure1: A: The structure of SARS-CoV-2 RdRp. B: The life cycle of SARS-CoV-2.

At present, effective drugs for the treatment of

SARS-Cov2 have not been reported. Some scientists

have found that the anti-virus RdRp drugs approved

by FDA are somewhat effective against

SARS-Cov-2. Ribavirin, Remdesivir, Sofosbuvir

and Galli- decivir (Elfiky, 2020) that target RNA

polymerase to inhibit viral replication are some of

the few drugs. But more experimental data are still

needed to support this discovery.

TCM is popular in the Chinese cultural circle.

This medicine based on life experience has been

practiced in East Asia for 5,000 years (Leng, Gany,

2014). TCM contains 11146 kinds of medicinal

plants and is a very valuable resource bank. There

have been numerous successful examples of finding

drugs from TCM. Computational technologies have

also made advances that can support these very large

scale screenings (Perez-Regidor, Zarioh, Ortega,

Martin-Santamaria, 2016). In this study the

SARS-CoV-2 RdRp is used as the template to search

for lead compounds from the TCM database. In

sight of the long history of traditional Chinese

medicine, so the drug candidates are also used in

emergency health events.

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

934

2 METHODS

The calculation method of this study is illustrated in

Fig.2

2.1 Structural Analyses for the

SARS-Cov-2 RdRp

The crystal structure of SARS-CoV2 RdRp complex

(PDBID: 7AAP) was downloaded from the RCSB.

Protein primary structure and physicochemical

parameters of RdRp is performed using an online

server of ExPASy (Gasteiger, Gattiker, Hoogland,

Ivanyi, Appel, Bairoch, 2003)

MCPB. py can

perform parameterizations for both Zn

ions

coordination bond (Li, Merz, Jr, 2016). The crystal

of 7AAP contains a gap between Leu895 and

Asn911.we employed Rosetta3.10 to build the gap

(Leman, Weitzner, Lewis, Adolf-Bryfogle, Alam,

Alford, Aprahamian, Baker, Barlow, Barth, 2020).

2.2 Molecular Docking

Traditional Chinese Medicine database contains

11146 kinds of medicinal plants and 33765

molecules. Molecular docking was carried out to

study the binding affinity between all molecules and

target protein (7AAP) by AutoDockVina1.2 (Trott O,

Olson AJ, 2010). Grid box coordinate was set at (x,

y, z) = 98.555, 96.343, 104.405 and docking

computing parameter employs AutoDock Vina

default settings. Pharmacokinetics assessment and

analysis is performed using an online ADMETsar

server (Cheng, Li, Zhou, Shen, Wu, Liu, Lee, Tang,

2012).

2.3 Molecular Dynamics Simulation

MD simulation computing was performed in explicit

solvent system. AMBER18 program was employed

to run 100ns for collecting data (Song, Lee, Zhu,

York, Merz, Jr, 2019). Force field of small

molecules, water and protein are generated

separately using antechamber, TIPT3P and ff14SB

of AMBER module (Maier, Martinez, Kasavajhala,

Wickstrom, Hauser, Simmerling, 2015; Steinberg,

Russo, Frey, 2019). The production simulation was

run 100 ns for three times.

2.4 RMSD and RMSF Calculation

Root mean squared deviation (RMSD) is used to

analyze the stability of complexes. When N means

the number of atoms, mi means the mass of atomi,

Xi means the coordinate vector for targetatom i, Yj

means the coor dinate vector for reference atom and

M means the total mass (Meli, Biggin, 2020; Khan,

Umbreen, Hameed, Fatima, Zahoor, Babar, Waseem,

Hussain, Rizwan, Zaman, 2021).

RMSD=



∑

m

∗X

−Y





i0

Root means square fluctuation (RMSF) analysis

was used to estimate the fluctuations of each amino

acid residue over the simulation time. When T is the

whole simulation time, tis the mass of atom i, ⎯ Xi is

the average coordinate for target residue i, x(t) is the

coordinate of residue i in time t.

𝑅𝑀𝑆𝐹=



𝑇

(𝑥

(

𝑡

)



−



𝑋



)







2.5 Binding Free Energy Calculation

The free energy of RdRp binding to small molecules

was calculated by the molecular mechanics energies

combined with the generalized born and surface area

continuum salvation (MM/PBSA) method (Jessica,

Swanson, Andrew McCammon, 2004). In order to

identify the most crucial residues of RdRp for the

binding of the natural small molecules, the total

binding free energy was decomposed into

contributions from individual residues (i = 1, 2, …,

932):

∆𝐺



=∆𝐺









=∆𝐺



,









∆G

bind

is the per-residue contributions, and

∆G

bind

i,j

isthe residue-pairwise interaction

contributions. The calculations were rendered by the

MMPBSA.py.MPI module of AMBER (Miller,

McGee, Jr., Swails, Homeyer, Gohlke, Roitberg,

2012).

Large Scale Virtual Screening for Finding Inhibitor against the RNA-dependent RNA Polymerase from Herbal Medicine for SARS-Cov-2

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935

Figure 2: Process of virtual screening.

Table1: Summary of top ranked Phytochemical screened against RdRp receptor docking score and binding free energy.

Phytochemical name

Plant source

Phytochemical

structure

Docking

Score

(kcal/mol)

Binding

free

Energy

(kcal/mol)

Residues interacting

with phytochemical*

7',8'-Dihydroxuxuarine Aα[39]

Maytenus chuchuhuasca

-12

-39.5029

±4.1410

Ala685, Ala688, Ile589,

Met601, Trp598, Ser592

Thr591, Gln815, Val588,

Lys593, Leu758, Cys813

Ala580, Lys577, Ile494,

Gln573, Arg569, Leu576

Gly 590

7,8-Dihydroisoxuxuarine Gα[39]

Maytenus chuchuhuasca

-11.8

-34.5054

±2.5765

Lys551, Ser549, Ala550,

Ile548, Hie439, Arg836

Cys813, Trp598, Lys593

Met601, Thr591, Ser759

Leu758, Ala547, Lys621

Asp618, Tyr619, Lys798

Pro620, Arg553

7,8-Dihydroisoxuxuarine Fα[39]

Maytenus chuchuhuasca

-11.7

-43.5704

±0.7284

Val560, Ala558, Lys500

Gly559, Thr565, Gly683,

Asn568, Ala685, Asp684,

Arg569, Gln573, Leu576,

Lys577, Ala580, Gly590,

Tyr689, Thr687, Ser682,

Leu544, Lys545, Gln408,

Asn543, Val557, Ser501,

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

936

7',8'-Dihydroxuxuarine Dβ[39]

Maytenus chuchuhuasca

-11.6

-34.4187

±1.1823

Gly590, Arg553, Lys545,

Ala547, Tyr546, Trp598

Asp865, Leu758, Cys813

Ser592, Lys593, Ile864

Phe594, Ser861, Thr591,

Ile589

Scabrans G5

[40]

Gentiana scabra

-11.6

-24.4734

±4.2354

Cys813, Ser759, Asp760,

Asp761, Ala547, Arg836,

His439, Lys551, Ser549,

Gln815, Ala550, Lys798,

Asp618, Glu811, Lys621,

Ile548, Asp623, Ser814,

Asp865, Leu862, Ile837,

Ala840, Pro832, Arg555

6",8'-Bisdiosquinone

[41]

Diospyros mafiensis

-11.3

-30.9596

±3.7960

Ala688, Leu576, Ala580,

Tyr689, Lys577, Val588

Gly590, Gln573, Ile589

Arg569, Asn496, Asn497,

Lys500, Cys813, Leu758,

Gln815, Lys593, Trp598,

Met601, Ser592, Phe812,

Thr591

Scabrans G4

[40]

Gentiana scabra Bunge

-11.3

-17.1623±2

.8491

Asp623, Arg624, Arg553,

Asp452, Ala554, Val557

Thr556, Asn691, Thr687,

Ser759, Lys545, Ile548

Ala547, Ser549, Ser814

Asp761, Asp618, Lys798

Pro620, Lys621, Tyr619

Cys622, Arg555, Asp760

Pusilatin C

[42]

Blasiaceae

-11.2

-20.7154

±2.2755

Arg566, Thr562, Lys497

Asp 681, Ala685, Gly680

Val554, Lys542, Ser811

Cys810, Asp758, Leu755

Asp 757, Ser756, Asn688

Ser679, Thr684, Tyr686

Leu573, Lys574, Gln570

Ile491, Val490, Val492,

Ala682

Isoxuxuarine Gβ

[39]

Maytenus chuchuhuasca

-11.0

-38.1405

±3.4054

Ala685, Asn496, Ala688,

Ile589, Ser759, Leu758

Ser814, Ile837, Arg836

Asp833, Asp865, Pro832

Gln815, Lys593, Cys813

Thr591, Gly590, Ala580

Tyr689, Lys577, Leu576

Gln573, Ile494, Arg569,

Val493, Val495, Val588

Galidesivir

[24]

Drugs used as control

-6.4

-25.8283

±1.7663

Ala685, Val560, Thr565,

Lys500, Ile562, Ser501,

Ala502, Ala512, Leu498

Tyr516, Asn497, Val495

Arg596, Gln573, Asn496

Large Scale Virtual Screening for Finding Inhibitor against the RNA-dependent RNA Polymerase from Herbal Medicine for SARS-Cov-2

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937

Table 2: Residues contributing large amount of negative (<-1.0KJ/mol)) energies towards RdRp.

ligand Residues

7',8'-Dihydroxuxuarine Aα

Ile589 Ala685 Ile494 Lys577 Gln573 Leu758

-1.9956 -1.9249 -1.3253 -1.2867 -1.2833 -1.2817

7,8-Dihydroisoxuxuarine

Fα

Leu576 Ala685 Arg569 Gly559 Lys577 Val560

-1.4921 -1.4501 -1.3727 -1.1525 -1.1460 -1.0501

Isoxuxuarine Gβ

Ser592 Thr591 Ile589 Ile494 Lys593 Cys813

-2.8722 -2.1811 -1.9397 -1.3814 -1.3792 -1.3575

Table 3: Hydrogen bond lifetime(H-bond) during the 100 ns MD simulation.

ligand Acceptor DonorH Donor Frac

7',8'-Dihydroxuxuarine Aα

ligand@O3 Gln_573@HE21 Gln_573@NE2 0.2240

ligand@O3 Gln_573@HE22 Gln_573@NE2 0.2205

7,8-Dihydroisoxuxuarine

Fα

ligand@O1 Tyr_689@HH Tyr_689@OH 0.3265

ligand@O2 Val_560@H Val_560@N 0.1920

Isoxuxuarine Gβ

Thr_591@O ligand@H1 ligand@O6 0.1930

ligand@O5 Gln_573@HE21 Gln_573@NE2 0.2775

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

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Figure 3: A: RMSD B: RMSF C: RoG D: H- bond interactions for three complexes in the 100ns simulation.

Figure 4: 3D structure for ligand-the SARS-CoV-2 RdRp.

Large Scale Virtual Screening for Finding Inhibitor against the RNA-dependent RNA Polymerase from Herbal Medicine for SARS-Cov-2

Therapy

939

3 RESULT

3.1 Structural of the SARS-CoV2

RdRp

TheSARS-CoV-2 RdRp contains 932 amino acids

and two zinc ion. One is bound to His295, Cys301,

Cys306 and Cys310 through four coordination

bonds. The other zinc ion is bound to His642,

Cys487, Cys645 and Cys646 through the four

coordination bonds. The molecular weight of the

SARS-CoV-2 RdRp is 106660.24 and the GRAVY

score is -0.224. Similar to RNA polymerase family,

the palm domain contains conversed motifs A-G.

The catalytic residue Asp760 of the SARS-CoV-2

RdRp is located in the motif C.

3.2 Molecular Docking

We docked Galidesivir, a potential inhibitor used as

control, with the binding groups and catalytic groups

of the SARS-CoV-2 Crystal RdRp Structure model

(PDBID: 7AAP). Traditional Chinese Medicine

databases which contain 33765 molecules were used

as the virtual screening protocol. Herein, we

identified small molecules that its docking scores is

higher than 11.0 kcal/mol by molecular docking

calculations. Then we screened 9 novel non-toxic

molecules thought the ADMETsar server (TableS1).

7',8'-Dihydroxuxuarine Aα was isolated from

Maytenus chuchuhuasca and exhibited the highest

docking score (-12kcal/mol). Isoxuxuarine Gβ was

also isolated from Maytenus chuchuhuasca and

exhibited the lowest docking score (-11.0kcal/mol).

Scabrans G5 was also isolated from Gentiana

scabra and forms hydrogen bonds with catalytic

residue Asp760 (Table 1; Fig S1), and exhibited the

middle docking score (-11.6kcal/mol).

3.3 RMSD and Free Energy

Decomposing

Amber18 was used to carry out 100ns MD

simulation for free energy calculation which result is

more accurate than that of docking (Table1 Binding

free energy). The production of MD simulation was

run for three times (Fig S2). This method can help

us understand what residues play important roles in

the complexes. From visualization of protein-ligand

system, and there are nine molecules locate at the

similar central cavity of the SARS-CoV-2 RdRp.

The three top of binding free energy is Isoxuxuarine

Gβ 7', 8'-Dihydroxuxuarine Aα, and 7,

8-Dihydroisoxuxuarine Fα. To do further

researching, we investigated the compactness,

stability and folding of protein through the Radius of

gyration calculation and fluctuations through

internal hydrogen bonds, two result indicates normal

behavior for three complexes (Figure3). Then we

also investigated the variation and stability of the

complexes through the RMSD calculation. As the

Figure3 shows, a similar trend of conformation

changes with RMSD over 932 C-alpha atoms for the

three systems during the whole simulation. It can be

found that the initial unsteady state lasted about

20ns before the atoms stably oscillated around their

new positions (0.3nm). Totally, a moderate

conformation change can be witnessed for the three

systems when compared them with their initial

structure.

Then we used RMSF to estimate the fluctuations

of each amino acid residue over the simulation time

(Figure 3). It is clear that different Phytochemical

cause fluctuation of different residues. For the

7',8'-Dihydroxuxuarine Aα-RdRP system, amino

acids fluctuate considerably around 16, 26, 61, 227,

263, 425, 595. However, the dramatic fluctuation

can be found around amino acids residues 62, 199,

227, 425, 853, 886 and 917 in the

7,8-Dihydroisoxuxuarine Fα-RdRp. Also, the

Isoxuxuarine Gβ mainly effects around residues

338,432, 644 and 824.

Based on the accurate binding free

energy(table2), In the 7',8'-Dihydroxuxuarine Aα

and Isoxuxuarine Gβ-RdRP, Ile589 and Ile494

contribute more to the free energy. On the contrary,

Ala685 and Lys577 contribute more to the binding

free energy in the 7',8'-Dihydroxuxuarine Aα and

7,8-Dihydroisoxuxuarine Fα

3.4 Hydrogen Bond Life Time Analysis

In this part, we focus on exploring the ligand and

protein interaction in details, which is helpful for

drug design and optimization in the future. H-Bond

plays an important role in structure-based drug

design. In general, the compounds will display great

activity if they interact with the key residues in the

protein. As the table 3 shows, the H atoms (HE21)

of Gln573 in the RdRp mainly interact O3 atom of

the 7', 8'-Dihydroxuxuarine Aα, accounting for 22%

in 100ns simulation. The H atoms (HH) of the

Tyr689 interact with O1 of the 7,

8-Dihydroisoxuxuarine Fα, accounting for 32%

within in 100 ns simulation. H atoms (HE21) of the

Gln573 interact with O5 Isoxuxuarine Gβ,

accounting for 27% within in 100 ns simulation.

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

940

4 CONCLUSIONS

The growing SARS-CoV-2 cases urge the

development of specific drug and new therapeutics.

We investigated the life cycle of SARS-CoV-2 and

uncovered the mechanism of transmission. We

discovered that the SARS-CoV-2 RdRp plays a

unique role in viral replication and analyzed the

structure of the RdRp. It is obvious that the RdRp is

an ideal drug target. Considering the unique

contribution to epidemic prevention in the history,

traditional Chinese medicine database was screened.

Then we identified nine non-toxic compounds

though ADMET analysis. Finally, some detail

analysis was executed through the MD simulation,

such as the RMSD, RMSF, hydrogen bond lifetime,

free energy decomposing. The information may

contribute to the further drug design and

optimization. It is surprising that the top three

compounds come from Maytenus chuchuhuasca and

the plants are widely used in folk medicine in South

America (Osamu SHIROTA, 2004; Kikuchi,

Kakuda, Kikuchi, Yaoita, 2005; Ra®ullah M. Khana,

1999; Tatsuhiko Yoshida, Shigeru Takaoka, 1996;

Haydee ChaÂ vez aGR, 2000). We anticipate that

the compounds screened from medical plants will be

used in the antiviral experiments and served as a

novel anti- SARS-CoV-2 drug.

FUNDING

This work was funded by Beijing Institute of

Technology, Zhuhai (Nos. XK-2019-03;

Nos.2020001TSZY)

CODE AVAILABLE

UCSD receipt # 2020-19-167

ACKNOWLEDGEMENTS

We thank National Supercomputing Center in

Shenzhen for providing the computational resources

and Gaussian09 software.

We also thank Beijing Computational Science

Research Center for providing Traditional Chinese

Medicine database

AUTHORS’ CONTRIBUTION

L.X and G.B performed the data processing; L.Z

advised on the implementation of image

decomposition and calculation of Euclidean

distances; all authors contributed to the final

manuscript

COMPETING INTERESTS

The authors have no competing interests.

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