Multi Epitopes Potential on Surface SARS-CoV-2 Protein as a Covid-19 Vaccine Candidate

 

Khoirul Anam1,2*, Bobi Prabowo3,4, Meike Tiya Kusuma3, Yuliati3, Sri Winarsih5,

Tri Yudani Mardining Raras6, Sumarno Reto Prawiro5

1Doctoral Program in Medical Science, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia.

2Study Program of Medical Laboratory Technology, Institute of Health and Science Technology,

Wiyata Husada Samarinda, Indonesia.

3Master Program in Biomedical Science, Faculty of Medicine, Universitas Brawijaya. Malang Indonesia.

4Department of Emergency Medicine, Dr. Iskak General Hospital, Tulungagung, Indonesia.

5Department of Clinical Microbiology, Faculty of Medicine, Universitas Brawijaya. Malang Indonesia

6Department of Biochemistry and Molecular Biology, Faculty of Medicine,

Universitas Brawijaya Malang. Indonesia.

*Corresponding Author E-mail: sanambwi@yahoo.co.id

 

ABSTRACT:

Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the etiology of an outbreak Covid-19. SARS-CoV-2 has a structural part consisting of spike glycoprotein, nucleoprotein N, membrane M and envelopes small membrane pentamer E. Immunoinformatic approach epitope analysis is developed to identify both weak and robust epitopes. Our study aims to identify several epitopes present in the spike glycoprotein, envelope, and membrane protein from the SARCoV-2 surface, with the help of insilico approach that highly potential as vaccine candidates. Analysis of antigeninicity was performed with the Kolaskar and Tongaonkar Antigenicity software. Epitope Mapping was analyzed using Linear Epitope Prediction Bepired. The structure of proteins with epitope regions was visualized by software Pyrex and PyMOL. Conserve analysis was performed using bio edit software. HLA mimicry was analyzed through HLAPred software. Molecular docking between the epitope with HLA I and HLA II was validated by Chimera and PyMOL software. The toxicity test for candidate vaccine peptides was carried out using ToxinPred software. Our study found seven potential epitope candidates as vaccine candidates. The seven epitopes were derived from spike proteins (5 epitopes), envelope proteins (1 epitope), and membrane proteins (1 epitope). All epitope codes are conserved and are not the same as HLA in Humans. The docking test results show a value with low affinity so that a strong bond can provide a high immune response. Toxicity tests show that all epitopes are non-toxic and safe to use as vaccine ingredients. Seven peptides from the spike, envelope, membrane protein that showed potential as vaccine candidates against Covid-19.

 

KEYWORDS: Immunoinformatic, Surface protein, Epitope, Covid-19, Vaccine candidate.

 

 


INTRODUCTION:

Covid-19 pandemic is outbreak diseases caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This virus is positive single-stranded RNA virus and enveloped.

 

Based on phylogenetic tree analysis, SARS-CoV and SARS-CoV-2 are a subgenus of Sarbecovirus within the genus of Betacoronavirus1,2. The SARS-CoV-2 has six genome encoding spike glycoprotein trimer S, nucleoprotein N, membrane protein M and envelopes small membrane protein pentamer E3,4.

 

The conserved region in designing vaccines is a viable strategy to develop vaccine efficacy against variable pathogens that affect adaptive immune responses. Multiple sequence alignment (MSA) was analyzed for recognition of conserved regions in viral structural proteins. All the sequences of SARS CoV-2 spike protein are highly conserved. Thus, a vaccine based on its sequence will be highly likely to have broad-spectrum immunological implications5,6.

 

Immunoinformatic epitope analysis approaches are developed to identify both weak and strong epitopes4. Modern technology can be used for the production of protein synthesis containing epitopes. The development of an epitope-based peptide vaccine candidate is a new step for an effective SarsCov 2 vaccine7,8. The immunoinformatic approach aims to predict antibody production and a long-lasting immunological response3.

 

Several proteins were analyzed to screen only useful epitopes based on criteria to find the most suitable and authentic epitopes, for further testing in a wet laboratory9,10. This study aims to identify several epitopes on the glycoprotein spike, envelope, and membrane proteins from the surface of SARCoV-2, which can be recommended as vaccine candidates.

 

MATERIAL AND METHODS:

The method used in this study is bioinformatic based using the approach of Antigenicity, Epitope Mapping, Multi Sequence Alignment, HLA-I and HLA-II Prediction, Toxicity Prediction, Tertiary Structure Prediction, and Molecular docking.

 

Analysis of the identified antigenic protein was carried out using the approach in silico bioinformatics with the Kolaskar and Tongaonkar Antigenicity software from the Epitope Immune Database and Analysis Resource (http://www.iedb.org) with values threshold (threshold value) 1.07. Epitope Mapping using Linear Epitope Prediction Bepired with a threshold value (entry) 0.35 of IEDB. The structure of proteins with epitope regions visualized by software Pyrex and PyMOL11,12.

 

Conservation analysis was carried out using bio edit software. Our protein sequences were obtained from NCBI or UniProt data. BioEdit was used to determine conserved sites via ClustalW13.

 

HLA mimicry was analyzed through HLAPred software (http://crdd.osdd.net/raghava/hlapred/). Human HLA mimicry analysis to see the similarities between epitope and peptide sequences in humans. This method identifies and predicts the HLA binding region of the antigen sequence for the prediction of HLA binding based on the HLA classification performed on Indonesian HLA14.

 

Antigen visualization was visualized using Molecular Evolutionary Genetics Analysis (MEGA), followed with models the 3D structure using SWISS-MODEL (https://swissmodel.expasy.org). The results of 3D models were displayed in the PyMol and Modloop software.

 

Molecular docking was performed between the epitope with HLA-I and HLA-II. Chimera, PyMOL, Plus PLIP software were used to visualize the interaction between candidate epitope wih HLA-I (B*44:03) dan HLA-II (DRB-1*07:01). Binding affinity values were scored by Autodock Vina15.

 

The toxicity test for vaccine candidate peptides was carried out using ToxinPred software (http://crdd.osdd.net/raghava/toxinpred/). The ToxinPred web server is utilized for determining the toxicity scoring of epitopes6.

 

RESULT AND DISCUSSION:

The complete amino acid sequences of spike, envelop and membrane protein of SARS-CoV-2 were downloaded in FASTA format from National Centre for Biotechnological Information (NCBI) database. The potential epitopes were predicted by performin, as shown in Fig 1 and Table 1.

 

Fig 1. The results of antigenicity analysis and epitope mapping using Kolaskar & Tongaonkar Antigenicity and Bepipred Linear Epitope Prediction software to obtain potential epitopes. A) analysis of the antigenicity and epitope mapping of the Sars-Cov2 spike glycoprotein; B) antigenicity analysis and epitope mapping of the envelope Sars-Cov2; C) analysis of the antigenicity and epitope mapping of the Sars-Cov2 membrane.

 


Table 1. Candidate Epitope for multiepitope Covid-19 vaccine design results from antigenicity analysis and epitope mapping.

S. No

Sequences Peptide (Epitope)

Location

Length

Description

1

FLVLLPLVSSQCVNL

4-18

15

Spike glycoprotein

2

ILPDPSKPSKRS

805-816

12

3

YQPYRVVVLSFELLHAPATVCGP

505-527

23

4

YGFQPTNGVGYQ

495-506

12

5

YFPLQSYGF

489-497

9

6

VNSVLLFLAFVVFLLVTLASS

14-32

21

Envelope protein

7

LYIIKLIFLWLLWPVTLACFVLAAVY

47-71

26

Membrane protein

 

 

Fig 2. Multi Sequence Alignment (MSA) epitope 1-7 using Bioedit software. A) analysis of conserve epitope 1; B) analysis of conserve epitope 2; C) analysis of conserve epitope 3-5; D) analysis of conserve epitope 6; E) analysis of conserve epitope 7.

 


The epitope candidate from the surface SARS-CoV-2 protein was subjected to conserve analysis using the bioedit software to identify whether the amino acid sequence that was the epitope's target was an area that underwent mutation (Fig 2).

 

The results from antigenicity analysis and epitope mapping were analyzed using human HLA mimicry analysis to reveal the similarity between peptide sequences and peptides in humans (Table 2).

 

Table 2 Analysis of Mimicry HLA was analyzed by web server.

Epitope

Sequence

Hits Against Genome

Comments

1

FLVLLPLVS

No Identical Sequence Found

The predicted binder can be recommended as a potential vaccine candidate because it has nothing in common with humans (eukaryotic organisms)

2

ILPDPSKPS

No Identical Sequence Found

3

YQPYRVVVL

No Identical Sequence Found

4

YGFQPTNGV

No Identical Sequence Found

5

YFPLQSYGF

No Identical Sequence Found

6

FLAFVVFLL FVVFLLVTL LFLAFVVFL LLFLAFVVF

No Identical Sequence Found

7

FLWLLWPVT

No Identical Sequence Found

 

 

The protein structures with epitope regions were visualized using the ModLoop design on the SARSCoV-2 protein surface (Fig 3).

 

Fig 3. Visualization of the multiepitope on the protein of SARSCoV-2 (ModLoop designed missing residue). A) Visualization of Epitope 1(red color) by 6ZGI; B) Visualization of Epitope 2 (yellow color) by PDB 6ZGI; C) Visualization of Epitope 3 (blue color) by PDB 6ZGI; D) Visualization of Epitope 4 (cyan color) by PDB 6ZGI; E) Visualization of Epitope 5 (orange color) by PDB 6ZGI; F) Visualization of Epitope 6 by PDB 2MM4 (magenta color). Visualization of epitope 7, like the visualized structure of Mycobacterium tuberculosis 13, has a similarity value of 42,3% of membrane glycoprotein SARSCoV-2.

 

Molecular docking of epitope with HLA-I (HLA-B*44:03: PDB 3KPN). Binding affinity values were scored by Autodock Vina 12. Visualization HLA B*44:03 with candidate epitope was analyzed by Chimera and PyMOL software, and Plus PLIP web server to predict interaction preview between HLA and epitope (Fig 4 and Table 3).

 

Fig 4. The molecular interaction between HLA-B*44:03 and epitope 1-7. The interaction was analyzed by Plus PLIP software. Figure A-G shows epitope 1-7

 

Table 3. Autodock Vina scored the binding affinity score molecular interaction between HLA-B*44:03 with candidate epitope values.

Epitope

Binding Affinity Score (kcal/mol)

RMSD u.b

1

-8.7

2.004

2

-7.4

5.198

3

-7.4

12.013

4

-11.0

2.441

5

-10.4

10.708

6

-8.9

17.764

7

-5.8

10.50

 

Molecular docking of epitope with HLA II (PDB HLA DRB-1*04:01: 6BIJ). Autodock Vina scored binding affinity values, Visualization HLA DRB-1*07:01 with candidate epitope was analyzed by PyMOL, and interaction preview between HLA and epitope was described by Plus PLIP (Fig 5 and Table 4).

 

Fig 5. The molecular interaction between HLA DRB-1*04:01 and epitope 1-7. PLIP analysed interaction. Figure A-G shows visualization of epitopes 1-7

 

Table 4. Autodock Vina scored the binding affinity score molecular interaction between HLA DRB-1*04:01 with candidate epitope values.

Epitope

Binding Affinity Score (kcal/mol)

RMSD u.b

1

-7.4

11.678

2

-7.0

11.757

3

-8.5

2.610

4

-10.4

3.149

5

-11.2

11.847

6

-9.6

2.184

7

-6.5

13.40

 

Epitope candidates were analyzed using the prediction of toxicity to see the toxicity of the candidate epitope (Table 5).

 

Table 5. The results of prediction of toxicity properties of several epitopes using the ToxinPred software.

Epitope

Peptide Sequences

Prediction score

Comment

Hydrophilicity

Mol wt

1

FLVLLPLVSSQCVNL

-1.01

Non-Toxin

-1.07

1645.27

2

ILPDPSKPSKRS

-0.88

Non-Toxin

0.78

1324.70

3

YQPYRVVVL

-1.20

Non-Toxin

-0.86

1136.49

4

YGFQPTNGV

-1.37

Non-Toxin

-0.70

982.19

5

YFPLQSYGF

-0.49

Non-Toxin

-1.21

1121.38

6

VNSVLLFLAFVVFLLVTLASS

-1.45

Non-Toxin

-1.24

2253.09

7

LYIIKLIFLWLLWPVTLACFVLAAVY

-1.34

Non-Toxin

-1.49

3083.33

 


Researcher initiated to study peptide based-vaccine as a safe alternative. We have successfully identified several epitopes derived from spike, envelope and membrane protein using immunoinfomatic tools. Analysis of potential epitope identification was carried out by antigenicity and epitope mapping tests on B cells using Kolaskar and Tongaonkar Antigenicity and Linear Epitope Prediction Bepired software (http://www.iedb.org). B-cells are a significant component of humoral immunity as long as the adaptive immune response produces antibodies that recognize antigens. The results showed that seven potential epitopes showed potential as vaccine candidates. This study's results are in line with previous studies that predict the epitope of potential spike and envelope protein 16,17, although we did not use linker to generate multiple epitopes.

 

Peptides from protein sequences that are predicted as epitope regions need to be ensured that these sequences are conserved areas that do not undergo mutation. The analysis was performed using bio edit software, and it was found that the seven-candidate epitopes from this study after alignment did not experience mutations in these sequences. These results indicate that the epitope candidate from the spike, envelope, and membrane proteins can be recommended as candidate materials for the Covid-19 vaccine. The recombinant RBD protein S consisting of multiple epitopes which cause high antibody titers that be used as a neutralizer against SARS-CoV-218. Envelope protein is an important virulence factor19. In addition, it has been reported that the transmembrane domain of M protein containing epitope groups of T cells was able to induce cellular immune response20. In addition, M protein is highly conserved in several different species21,22.

 

With a help of Human HLA mimicry analysis, the similarities between epitope and peptide sequences in humans can be identified. The similarity in molecular structure between class II HLA genes and exogenous antigens can reflect autoimmunity through the concept of molecular mimicry. The similarity in molecular structure between class II HLA genes and exogenous antigens can cause autoimmunity23,24. The mimicry analysis results show that all epitope candidates did not show any similarity to human HLA, so the candidate epitopes in our study can be considered safe from autoimmunity. Some of the peptides on the SARSCoV-2 spike, which is the epitope, were analyzed for their similarity to the Homo sapiens body receptor's cell surface. The results show that some of these epitopes have nothing in common with the cell surface receptors of the Homo sapiens body5,25.

 

ModLoop is an online web tools for the automatic protein structure modelling (http://salilab.org/bioinformatics_resources.shtml)21. The spike protein epitope used modeling of the 6ZGI protein (epitope 1= red color, epitope 2=yellow color, epitope 3=blue color, epitope 4=cyan color, epitope 5=orange color). Visualization of the SARS CoV2 spike protein using PDB: 6ZGI has the same value as 96.7%26,27. Visualization of epitope six by PDB 2MM4 (magenta color). PDB: 2MM4 represents the coronavirus protein envelope / SARS-CoV-2 envelope28, has a similarity value of 91.4% with the SARS-CoV-2 envelope. Visualization of epitope seven, like the visualized structure of Mycobacterium tuberculosis29, has a similarity value of 42,3% of membrane glycoprotein SARSCoV-2.

 

Protein Plus and PLIP web server described visualization of docking analysis results between epitope and HLA I was analyzed by Chimera and PyMOL and interaction preview between HLA and epitope. Visualization of the docking analysis results between the epitopes and HLA II was also analyzed using Chimeras and PyMOL. Protein Plus and PLIP web server described an interaction preview between HLA and epitope. The results of binding affinity score molecular interaction between HLA with candidate epitope values were scored by Autodock Vina30. The affinity binding between HLA I and the epitope is as follows: -8.7; -7.4; -7.4; -11.0; -10.4; -8.9; -5.8 for epitope 1, 2, 3, 4, 5, 6, 7 subsequently. Meanwhile, the binding affinity between HLA II and the epitope is as follows: -7.4; -7.0; -8.5; -10.4; -11.2; -9.6; -6.5. The docking simulation results between peptide and HLA can be recommended for use as vaccine candidates due to low energy affinity score. The lowest binding energy as the result of molecular docking, the higher probability the formation of molecular complex31. Hydrogen bonding and hydrophobicity will affect the molecular bond energy score32. The immune response of B cells is influenced by the stability of the molecular complex33.

 

The peptide candidate we obtained is a material that is safe to use as a vaccine candidate. Vaccine candidate materials are declared safe and meet the requirements for vaccine candidates if they are not toxins. The results of the toxicity analysis showed that the 7 peptides we obtained were not toxic.

 

CONCLUSION:

Our finding has identified high potential seven epitopes as vaccine candidate Sars-Cov-2. However, the proposed epitope requires trials through in vitro and in vivo studies.

 

ACKNOWLEDGMENTS:

Authors acknowledge to PT Anak Bangsa Bioteknologi that given financial assistance about this analysis. We thank EJA Team, Indonesia for editing the manuscript.

 

CONFLICT OF INTEREST:

The authors confirm that this article content has no conflicts

 

REFERENCE:

1.      Ansori ANM. Nidom RV. Kusala MKJ. Indrasari S. Normalina I. Nidom AN. Afifah B et al. Viroinformatics investigation of B-cell epitope conserved region in SARS-CoV-2 lineage B.1.1.7 isolates originated from Indonesia to develop vaccine candidate against COVID-19. Journal of Pharmacy & Pharmacognosy Research 2021; 9(6):766-779.

2.      Devi KN. Rosy JS. ECMO therapy for COVID-19. Asian Journal of Nursing Education and Research 2021; 11(2):299-301.

3.      Ansori ANM. Kharisma VD. Fadholly A. Tacharina MR. Antonius Y. Parikesit AA. Severe acute respiratory syndrome coronavirus-2 emergence and its treatment with alternative medicines: A review. Research Journal of Pharmacy and Technology. 2021; 14(10).

4.      Nidom RV. Ansori ANM. Indrasari S. Normalina I. Kusala MKJ. Saefuddin A. Nidom CA. Recent updates on COVID-19 vaccine platforms and its immunological aspects: A review. Systematic Reviews in Pharmacy. 2020; 11(10):807-818.

5.      Fernandes M. Thakur JR. Gavanje MS. A study to assess knowledge regarding covid-19 among Nursing students. Asian Journal of Nursing Education and Research. 2021; 11(1):65-67.

6.      Turista DDR. Islamy A. Kharisma VD. Ansori ANM. Distribution of COVID-19 and phylogenetic tree construction of SARS-CoV-2 in Indonesia. Journal of Pure and Applied Microbiology. 2020; 14:1035-1042.

7.      Rai P. Roy D. Death and scarcity of life saving PPEs: Where is the life of heroes?. Asian Journal of Nursing Education and Research. 2021; 11(1):157-160.

8.      Zheng M. Song L. Novel antibody epitopes dominate the antigenicity of spike glycoprotein in SARS-CoV-2 compared to SARS-CoV. Cellular & Molecular Immunology. 2020; 17:536-538.

9.      Ansori ANM. Kharisma VD. Muttaqin SS. Antonius Y. Parikesit AA. Genetic variant of SARS-CoV-2 isolates in Indonesia: Spike glycoprotein gene. Journal of Pure Applied Microbiology. 2020; 14:971-978.

10.   Kharisma VD. Ansori ANM. Construction of epitope-based peptide vaccine against SARS-CoV-2. Immunoinformatics study. Journal of Pure Applied Microbiology. 2020; 14(suppl 1):999-1005.

11.   Fahmi M. Kharisma VD. Ansori ANM. Ito M. Retrieval and investigation of data on SARS-CoV-2 and COVID-19 using bioinformatics approach. Advances in Experimental Medicine and Biology. 2021; 1318:839-857.

12.   Joshi A. Joshi BC. Mannan MA. Kaushik A. Epitope based vaccine prediction for SARS-CoV-2 by deploying immune-informatics approach. Informatics in Medicine Unlocked. 2020; 19:100338.

13.   Armiyanti Y. Arifianto RP. Nurmariana E. Senjarini K. Widodo. Fitri LE. Sardjono TW. Identification of antigenic proteins from salivary glands of female Anopheles maculatus by proteomic analysis. Asian Pacific Journal of Tropical Biomedicine. 2016; 6(11):930-936.

14.   Mufida DC. Handono K. Sumarno RP. Santoso S. Identification of hemagglutinin protein from Streptococcus pneumoniae pili as a vaccine candidate by proteomic analysis. Turkish Journal of Immunology. 2018; 6(1):8−15.

15.   Abdelmageed MI. Abdelmoneim AH. Mustafa MI. Elfadol NM. Murshed NS. Shantier SW. Makhawi AM. Design of multi epitope-based peptide vaccine against E protein of human COVID-19: An immunoinformatics approach. BioMed Research International. 2020; 2020:2683286.

16.   Pradana KA. Anekson M. Wahjudi M. Indonesians human leukocyte antigen (HLA) distributions and correlations with global diseases. Immunological Investigations. 2019; 1-31.

17.   Trott A. Olson J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. Journal of Computational Chemistry. 2010; 31:455-461.

18.   Luckner SR. Machutta CA. Tonge PJ. Kisker C. Crystal structures of Mycobacterium tubercolosis KasA show mode of action within cell wall biosynthesis and its inhibition by thiolactomycin. Structure. 2009; 15:17(7): 10041013.

19.   Naresh BV. A review of the 2019 novel coronavirus (COVID-19) pandemic. Asian Journal of Pharmaceutical Research. 2020; 10(3):233-238.

20.   Bhattacharya M. Sharma AR. Patra P. Ghosh P. Sharma G. Patra BC. Lee SS et al. Development of epitope‐based peptide vaccine against novel coronavirus 2019 (SARS‐COV‐2): Immunoinformatics approach. Journal of Medical Virology. 2020; 114.

21.   Rokade M. Khandagale P. Coronavirus disease: A review of a new threat to public health. Asian Journal of Pharmaceutical Research. 2020; 10(3):241-244.

22.   Dawood AA. Should we worry that the COVID-19 could be transmitted with the semen?. Asian Journal of Pharmaceutical Research. 2020; 10(4):319-320.

23.   Kalita P, Padhi AK, Zhang KYJ, Tripathi T. Design of a peptide-based subunit vaccine against novel coronavirus SARS-CoV-2. Microbial Pathogenesis. 2020; 145:104236.

24.   Jarag PL. Kengar MD. Jadhav RR. Shinde AS. Koli SS. Honmane PP. On overview- corona virus and hanta virus disease. Asian Journal of Pharmaceutical Research. 2020; 10(3):178-182.

25.   Zhu X. Liu Q. Du L. Lu L. Jiang S. Receptor-binding domain as a target for developing SARS vaccines. Journal of Thoracic Disease. 2013; 5(Suppl. 2):S142S148.

26.   Nieto-Torres JL. DeDiego ML. Verdia-Baguena C. Jimenez-Guardeno JM. Regla-Nava JA. Fernandez-Delgado R. Castano-Rodriguez C et al. Severe acute respiratory syndrome coronavirus envelope protein ion channel activity promotes virus fitness and pathogenesis. PLoS Pathogens. 2014; 10:e1004077.

27.   Liu J. Sun Y. Qi J. Chu F. Wu H. Gao F. Li T. The membrane protein of severe acute respiratory syndrome coronavirus acts as a dominant immunogen revealed by a clustering region of novel functionally and structurally defined cytotoxic T-lymphocyte epitopes. The Journal of Infectious Diseases. 2010; 202:11711180.

28.   Neuman BW. Kiss G. Kunding AH. Bhella D. Baksh MF. Connelly S. Droese B et al. A structural analysis of M protein in coronavirus assembly and morphology. Journal of Structural Biology. 2011; 174:1122.

29.   Zanelli E. Breedveld FC. de Vries RR. HLA class II association with rheumatoid arthritis: Facts and interpretations. Human Immunology. 2000; 61(12):12541561.

30.   Fiser A. Sali A. ModLoop: Automated modeling of loops in protein structures. Bioinformatics. 2003; 19(18):25002501

31.   Ansori ANM. Kusala MKJ. Normalina I. Indrasari S. Alamudi MY. Nidom RV. Santoso KP et al. Immunoinformatic investigation of three structural protein genes in Indonesian SARS-CoV-2 isolates. Systematic Reviews in Pharmacy. 2020; 11(7):422-434.

32.   Li Y. Surya W. Claudine S. Torres J. Structure of a conserved Golgi complex-targeting signal in coronavirus envelope proteins. Journal of Biological Chemistry. 2014; 289:12535-12549.

 

 

 

Received on 07.04.2021 Modified on 04.07.2021

Accepted on 10.08.2021 RJPT All right reserved

Research J. Pharm.and Tech 2022; 15(4):1437-1442.

DOI: 10.52711/0974-360X.2022.00238