The Profile of SARS-Cov-2 Genome from Indonesia and Its Impact

on Paxlovid

in Treating Covid-19

Hotma Martogi Lorensi Hutapea

1,2,* a

, Yustinus Maladan

, Tri Yunis Miko Wahyono

Arli Aditya Parikesit

and Mondastri Korib Sudaryo

Department of Epidemiology, Faculty of Public Health, Universitas Indonesia, Depok, Jawa Barat, Indonesia

National Research and Innovation Agency, Jl. M.H. Thamrin No. 8, Jakarta 10340, Indonesia

Department of Bioinformatics, School of Life Sciences, Indonesia International Institute for Life Sciences (i3L), Jakarta

13210, Indonesia

Keywords: 3CLPro, Molecular Docking, Nirmatrelvir, Paxlovid

, SARS-CoV-2 Genome.

Abstract: Since April 2023, Paxlovid

has been used to treat SARS-CoV-2 infection in Indonesia. This medication

contains 2 active compounds, ritonavir (RTV) and nirmatrelvir (NTV) that act as human CYP3A4 and viral

main proteinase or 3CL

Pro

respectively. NTV is novel drug to inhibit SARS-CoV-2 progressivity. Mutations

that decrease NTV effectiveness have been reported in several countries, however, the data from Indonesia is

still limited. We are using SARS-CoV-2 genomic data from GISAID which were collected from Sept 1, 2022

– Oct 31, 2023, from Indonesia. Any mutation in 3CL

Pro

was recorded and then proceeded to be analysed

further. NTV-3CL

Pro

complex was downloaded from the Protein data bank (7SI9), and separated in PDB

format. The 3CL

Pro

was mutated using FOLDX to generate the mutant variant. Docking simulation was

performed using Autodock Vina which is integrated into PyRx.0.9.7 software with SARS-CoV-2 Wuhan-Hu

isolate (NC_045512.2) as control. RMSD score was calculated using YASARA software and considered valid

if the redocking score is <2.0 Å. In total, 13,345 genomes from COVID-19 patients were submitted in GISAID,

and all of them were Omicron, with GRA clade and XBB subvariant being more predominant. We found out

that 3CL

Pro

encoding genes were relatively conserved with only P132H mutation motive (99.8%) identified.

Therefore, we performed the simulation on mutant P184L which was found in the Delta variant. Docking

simulation demonstrated that the binding affinity score between nirmatrelvir and control was -8.6 kcal/mol,

and -8.5 kcal/mol on 3CL

Pro

mutant. According to the visualization of NTV-3CL

Pro

interaction, the mutant

P132 and P184 showed no difference compared to the control. We found no mutation that potentially

decreased the effectiveness of Paxlovid

based on the activity of NTV in the SARS-CoV-2 genome collected

from patients in Indonesia. Therefore, SARS-CoV-2 in Indonesia might be susceptible to Paxlovid

1 INTRODUCTION

SARS-CoV-2 infection causes coronavirus disease

2019 (COVID-19), which has caused approximately

6.7 million cases and over 160 thousand fatalities in

Indonesia as of March 2023 (World Health

Organization, 2023b). It remains a major public

health threat globally and has been indicated that the

virus will most likely remain as an established

https://orcid.org/0000-0002-7099-3891

https://orcid.org/0000-0002-6685-7790

https://orcid.org/0000-0001-8716-3926

https://orcid.org/0000-0003-0896-1538

pathogen in humans and animals for a long time. On

April 2023, Ministry of Health of The Republic of

Indonesia has received a shipment of the oral antiviral

medicine nirmatrelvir (NTV)/ritonavir (RTV)

(PAXLOVID™) (World Health Organization,

2023a). It is drug cocktail that designed to stop

COVID-19 from worsening by inhibiting the

replication of SARS-CoV-2 in patients’ body (Lin et

al., 2023). It is suitable to treat early infection in order

to stop the diseases progression. NTV is shown to be

Hutapea, H. M. L., Maladan, Y., Wahyono, T. Y. M., Parikesit, A. A. and Sudaryo, M. K.

The Proﬁle of SARS-Cov-2 Genome from Indonesia and Its Impact on Paxlovid TM in Treating Covid-19.

DOI: 10.5220/0013217000003873

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Medical Science and Health (ICOMESH 2023), pages 32-37

ISBN: 978-989-758-740-5

suppressing SARS-CoV-2 by binding and

suppressing Main protease (Mpro) or known as

3CLpro as GC373 analog both in vitro and in vivo.

However, it is metabolized mainly by cytochrome

P450 3A4 (CYP3A4) which is responsible for the

primary metabolism of about 50% of drugs. RTV

boosts nirmatrelvir activity by inhibiting CYP3A

(Lam & Patel, 2023).

In Coronaviridae genus, 3CLpro promotes the

replication by cleaving polyprotein when the viral

RNA enters the host cells. This protein exhibits >96%

sequence identity with SARS-CoV, and the residues

of its binding pocket are highly conserved. A study

conducted in Canada using samples collected from 1

January 2020 – 12 January 2023 shows a very low-

frequency (0.16 – 0,58%) variants at position linked

to Paxlovid

resistance genes (nsp5). Even though

SARS-CoV-2 exhibit slower mutation rate (2.9×10

mutations/nt/cycle - 3.7×10

-6

mutations/nt/cycle)

(Gudiño León. et al., 2021), and 3CLpro binding

pocket residues are highly conserved, the potential of

drug resistant-associated mutation should not be

neglected.

A study was conducted to identify mutation that

naturally existed in the virus, and 100 mutations were

found in 3CLpro encoding gene. These mutations

located in NTV binding site and showed comparable

enzymatic activity to the wild-type (kcat/Km <10-

fold change) and resistance to NTV (Ki >10-fold

increase). Another spot in SARS-CoV-2 genome for

drug resistant is S144, M165, E166, H172, and Q192

which exhibit resistance 1.8 to 534.0-fold depending

on the location of the mutation (Lee et al., 2022).

Based on those data, it is important to identify the

presence of NTV resistance-related mutation to

understand the potential of drug-resistance. In this

study we aim to identify the mutation associated with

Paxlovid

resistance, specifically NTV, and to

analyse the interaction between NTV with 3CLpro

mutant.

2 METHODS

2.1 Analysis of SARS-CoV-2 Genome

Profile

This was a case series study, with population was

COVID-19 patients who were eligible for SARS-

CoV-2 genome isolation according to Ministry of

Health genomic surveillance policy. We downloaded

full genome sequences submitted between Sept 1,

2022 – Oct 31, 2023 from the GISAID EpiCoV

database (https://www.gisaid.org/). We excluded the

genome if it was incomplete, and contains >5%

unidentified nucleotide. We extracted nsp5 genes

from the genomes and aligned the sequences using

MEGA X software and used SARS-CoV-2 Wuhan-

Hu isolate (NC_045512.2) as control. The data such

as patients’ gender and age, and virus’ data such as

clade lineage, and mutations were recorded from

meta data of the genome.

2.2 Molecular Docking of NTV-3CLpro

PyRx 0.9.7 integrated Autodock Vina was utilized to

perform molecular docking between NTV and

3CLPro. We were using a computer with the

following configuration ASUS ROG GL553 VE,

8GB RAM. NTV-3CLPro complex was obtained

from PDB (PDB:7SI9) and separated using saved in

PDB format. The mutant form of 3CLPro was

generated using FOLDX. Docking validation was

performed by redocking NTV to 3CLPro, and the

docking procedure was considered as valid if RMSD

value was < 2.0 Å.

3 RESULTS AND DISCUSSION

3.1 Results

3.1.1 Molecular Epidemiology of

SARS-CoV-2

There were 15,753 genomes submitted between

September 1, 2022 – October 31, 2023 and all of them

were identified as Omicron variant of SARS-CoV-2.

Among them, 14,835 genomes were having complete

genes composition, and 13,345 genomes were having

<5% of unidentified nucleotides. These genomes

were extracted from nasopharynx swab of patients

who were receiving treatment in hospital and from

genomic surveillance majority in Java Island.

Majority of them were female with age 19-45 years

old (median of age was 39 years old) (Table 1).

Table 1: Demographic and SARS-CoV-2 characteristics,

and samples distribution

Characteristics Frequency

(n=13,345)

e, Median

(

median, SD

)

39±21

rou

, n

(

)

0-18 1,553

(

11.6

)

19-45 5,631 (42.2)

46-65 3,127 (23.4)

>65 1,799 (13,5)

Missin

1,255

(

9.3

)

The Proﬁle of SARS-Cov-2 Genome from Indonesia and Its Impact on Paxlovid TM in Treating Covid-19

Gender, n

(

)

Female 6,494 (48.7)

Male 5,654 (42.4)

Missin

1,197

(

8.9

)

Clade, n

(

)

GH 1

(

0.0

)

2 (0,0)

GR 7 (0,1)

GRA 13,334 (99.9)

O 1

(

0,0

)

inea

es, n

(

)

B.1 1,760

(

13.2

)

BA.1 651 (4.9)

BA.5 4,075 (30.5)

EG 1,117

(

8.4

)

FL 787

(

5,9

)

XBB 4,159

(

31.2

)

Others 796 (6.0)

Patients’ status, n (%)

Survive 2,717 (20.4)

Decease

(

0,5

)

Unknown 10,555

(

79.1

)

Sam

les’ distribution, n

(

)

Sumatera 1,861 (13.9)

Java 9,908 (74.3)

Bali 624

(

4.7

)

Kalimantan 604

(

4.5

)

Sulawesi 207

(

1.6

)

Nusa Tenggara 67 (0.5)

Maluku 27 (0.2)

Papua 47 (0.3)

Clade GRA was predominating which caused almost

100% the infection. In overall, subvariant XBB was

prevalent in Java, Bali, Nusa Tenggara, and Papua

while Sumatera, Kalimantan, Sulawesi, and Maluku

were dominated by BA.5 (table 2), however the

fluctuation was observed across subvariants (figure 1).

Table 2: Samples’ distribution by lineage dominance

Characteristics Frequency

(

n=13,345

)

Dominant

linea

e (%)

Samples’

distribution, n(%)

Sumatera 1,861

(

13.9

)

BA.5

(

47.0

)

Java 9,908

(

74.3

)

XBB

(

33.2

)

Bali 624 (4.7) XBB (39.7)

Kalimantan 604 (4.5) BA.5 (31.0)

Sulawesi 207 (1.6) BA.5 (57.0)

Nusa Ten

ara 67

(

0.5

)

XBB

(

27.0

)

Maluku 27

(

0.2

)

BA.5

(

81.4

)

ua 47

(

0.3

)

XBB

(

42.6

)

On September 2022, the BA.5 subvariant was

predominant and causing 90.4% of the SARS-CoV-2

infection.

Figure 1: The trend of Omicron lineages in Indonesia

during the study. BA.5 lineage was dominating the

infection in the beginning of the observation, and then

replaced by EG lineage in the end of the observation.

The BA.5 infection was decreased constantly until

undetectable on January 2023. While BA.5 infection

was decreasing, XBB subvariant was increasing and

became dominant and reach its peak on December

2022. The XBB infection remained dominant for at

least a month and slowly decreased while EG

subvariant was increasing. On April 2023, the

proportion of XBB and EG subvariant was the same.

The XBB was undetected since July 2023, however

subvariant EG was taking over the infection until

October 2023.

3.1.2 Mutation Identification and Molecular

Docking

We found that 3CLpro encoding genes (nsp5) were

relatively conserved with only P132H mutation

motive (99.8%) identified. We performed molecular

docking on 3CLpro mutant P132H to NTV. In order

to obtain better understanding on the potential of

mutation to NTV susceptibility, we used 3CLpro

mutant P184H which was common in Delta variant of

SARS-CoV-2. The binding affinity of NTV-3CLpro

wild type was -8.6 kcal/mol, and the mutant P132H

and P184L were slightly weaker compared to wild

type (-8.5 kcal/mol) (Table 3).

Table 3: Docking result on NTV-3CLpro wild type and

mutants

Reseptor

Binding Affinity

(kcal/mol)

Protein stability

(kcal/mol)

Wild type -8.6 59.16

P132H -8.5 59.9

P184L -8.5 60.19

ICOMESH 2023 - INTERNATIONAL CONFERENCE ON MEDICAL SCIENCE AND HEALTH

The binding affinity between 3 models was

insignificantly different, and this result was supported

by the visualization of the interaction. The hydrogen

bond was formed in the same position, which was in

amino acid LEU141, GLY143, SER144, CYS145,

GLU166, GLN192.

Figure 3: Comparison of hydrogen bond position in 3CLPro

wild type and mutant P132H in Omicron and P184L in

Delta.

3.2 Discussion

This study depicted the profile of SARS-CoV-2 and

COVID-19 patients based on metadata obtained from

GIS database. In this study, majority of the patients

(74.3%) was from Java Island, the centre of Indonesia

with highest population density (Dsikowitzky et al.,

2018). All of the patients were infected with Omicron

variants of SARS-CoV-2, majority with XBB. Study

showed that proportion of asymptomatic and mild

patients was higher in Omicron group than Delta and

Beta groups, however those with Omicron had more

throat soreness and less headache (Yang et al., 2022).

Majority of the patients was between 19-49 years old,

this was consistent with previous studies which

showed that greater proportion of Omicron infection

was found in younger age group, while Delta was

found in older age group of patients (Miao et al.,

2023; Yang et al., 2022).

COVID-19 medication was mostly involving

immunological intervention by using antibody such

as tocilizumab and other anti-SARS-CoV-2

monoclonal antibody products, however, high

variation in spike of the virus is major obstacle to

keep the medication works as the way it is (Treatment

Guidelines Panel, 2023). The discovery of 3CLpro

inhibitors represents a major breakthrough in

COVID-19 treatment (Zhu et al., 2020). In this study,

all the samples collected were identified as Omicron

variant of SARS-CoV-2, with 353 sub-lineages, and

35% of them were XBB, and followed by BA.5

(34%). Omicron variant is more transmissible and can

evade immune system better compared to previous

variants of SARS-CoV-2 (Veltri et al., 2023). The

Omicron variant have dominated epidemiologic

landscape of SARS-CoV-2 infection globally. It also

had evolved remarkably in diversity by forming over

1,000 sub-lineages with the standards lineages are

BA.1, BA.2, BA.3, BA.4, and BA.5, which share

many mutations, but also significantly different

(Velavan et al., 2023; Veltri et al., 2023).

In this study, on September 2022 we observed that

BA.5 was identified in majority of the samples. BA.5

was first detected in South Africa, and then in

Belgium, France, China, Botswana, Portugal,

Germany and Australia. The most recent ancestor of

BA.5 is estimated most closely related to BA.2. There

has been reported that BA.2 and BA.5 are more

transmissible and resistant to immunity generated by

previous variants and most monoclonal antibodies.

BA.5 dominance was dropping on October 2022 and

replaced by XBB variant. XBB was likely originated

via BA.2 descendant recombination. It was first

detected in India on October 2022 and immediately

became predominant globally. WHO declared that

XBB as Omicron subvariant under monitoring on

October 28, 2022 (Lee et al., 2022).

EG started to replace XBB since April 2023 until

October 2023. Limited information about EG.2 is

available; it is one of many subvariants that has

F456L in spike which makes it harder for many

existing antibodies to recognize the viral particles. If

Wild type

3CL-Pro

mutant P132H

3CL-Pro

mutant P184L

The Proﬁle of SARS-Cov-2 Genome from Indonesia and Its Impact on Paxlovid TM in Treating Covid-19

this virus also has L455F, it might have the ability of

immune-evading and tighter binding to the ACE2

protein, which is likely to enhance cell entry. The

EG.2 variant is radically different from the others,

and Q52H and F456L mutations make this variant

more similar to the original Omicron which has

greater binding affinity compare to the other XBB

descendants (Veltri et al., 2023)

Our study showed that mutation that has potential

in developing drug resistance remains rare, however

P132H was identified in almost all samples (99.8%).

This result is in line with current global situation

where this mutation is the most prevalent globally.

P132H mutation is exclusively associated with

Omicron because this mutation was identified in

>98% of Omicron (Sacco et al., 2022). On 2022,

P132H was most prevalent in UK (44%), and it was

found in 98% of Omicron subvariant. P132H

mutation is localized at about -22 Å away from the

catalytic site and not in direct contact with any of the

residues of allosteric pocket. Study showed that

P132H got 3CLpro thermal stability compromised

(Lee et al., 2022). A study demonstrated that P132H

mutation alone related to a decreased stability of the

enzyme in vitro. Another study also revealed the

crystal structures shows that the mutations does not

give rise any significant changes of the protein around

the binding pocket or the site of the mutation

(Greasley et al., 2022).

The effect of the P132H mutation on Omicron

3CLpro remains unclear. We found that the binding

affinity of P132H mutant was not significantly

different compared to the wild type. This result was

supported by visualization of hydrogen bond

position, we observed the same position of hydrogen

bond across the mutations. Our result is consistent

with previous study which showed that P132H might

not reduce enzymatic activity and inhibitor binding.

Study showed that P132H decrease thermal stability

of 3CLpro and may cause the increasing protein

flexibility which might broaden substrate profile

substrate profile or to alter ligand binding (Sacco et

al., 2022).

Another study showed that P132H will give effect

to thermal stability only if the proline at position 108

3CLpro is also replaced by other amino acid. Another

impact of P132H was observed by Chen et al.,

Omicron with P132H mutation permitted charged L-

Lys and the enzyme activity is increased toward L-

Trp and L-Tyr compared to the wild type. Catalytic

efficiency was observed on the double mutant K90

and P132H.(Chen et al., 2023) In this study we

observed that P132H alone without other mutation

along with it, therefore P132H alone is considered to

be non-major changes related to the chemical

characteristic of 3CLpro because this mutation does

not play role whether in the active site or the allosteric

binding site of the protein (Ullrich et al., 2022).

4 CONCLUSIONS

NTV is still potent to be used as oral antiviral to treat

COVID-19 in Indonesia, however routine genomic

surveillance is necessary to anticipate the appearance

of mutations that have been proven to be associated

with NTV resistances.

ACKNOWLEDGEMENTS

We gratefully acknowledge all SARS-CoV-2

sequence data contributors in Indonesia, i.e., the

authors and their originating laboratories responsible

for obtaining the specimens, and their submitting

laboratories for generating the genetic sequence and

metadata and sharing via GISAID, on which parts of

this research is based.

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The Proﬁle of SARS-Cov-2 Genome from Indonesia and Its Impact on Paxlovid TM in Treating Covid-19