Phylogenetic Analysis and Structural Prediction of NSP9 and NSP11 of SARS-CoV-2 Variants Across the Globe
Rabia Nawaz1*, Mohi-Ud-Din Nasir1, Muhammad Khizar1, Haroon Riaz1,
Jalees ul Hassan2, Ammara Ahad1, Ghazanfar Ali1, Zohal Hassan1, M. Mushtaq1, M. Shahid3 and Uqba Mehmood1
1Department of Biological Sciences, The Superior University, Lahore
2Department of Fisheries, University of Veterinary and Animal Sciences, Lahore
3Center of Excellence in Molecular Biology, University of the Punjab, Lahore
ABSTRACT
In December 2019, a new disease appeared in Wuhan, China, later called Coronavirus disease 2019 (COVID-19). The causative agent was named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). It has four structural and sixteen nonstructural proteins. Nonstructural proteins (NSP1 to NSP16) are encoded by virus but are not a part of viral particles. In this study, the In Silico analysis of SARS-CoV-2 selective non-structural proteins, NSP9 (genomic region 4141-4253) and NSP11 (genomic region 4393-4405) for the years of 2020-2022 was performed. Phylogenetic analysis of NSP9 and NSP11 was performed by the Neighbor-Joining method through CLC-Sequence Viewer 8.0 version. The reference sequences of the coronavirus variants of concern Alpha, Kappa, Delta, Omicron, and initial refseq from China were taken to determine the similarities and differences between these sequences among different countries. We conclude that in NSP9 the rate of genetic mutation was far higher as compared to NSP11 which in turn means that NSP11 was more conserved. The structural prediction had been done in order to observe the protein sequences of Alpha, Delta, Omicron, and refseq for NSP9 and NSP11 of SARS-CoV-2 using the Swiss Model. We observed that the behavior of viruses and mutations across the globe are closely related to each other.
Article Information
Received 07 October 2022
Revised 05 February 2024
Accepted 27 February 2024
Available online 09 August 2024
(early access)
Published 19 July 2025
Authors’ Contribution
RN, MDN and MK participated in the experimental design, material collection and wrote the manuscript. HR and JH participated in the bioinformatics analysis. AA, GA and ZH helped in writing manuscript. All authors read and approved the final manuscript.
Key words
SARS-CoV-2, Selected protein NSP9, NSP11, Phylogenetic analysis, Structural prediction, 3d structure
DOI: https://dx.doi.org/10.17582/journal.pjz/20221107051149
* Corresponding author: [email protected]
0030-9923/2025/0005-2051 $ 9.00/00
Copyright 2025 by the authors. Licensee Zoological Society of Pakistan.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
INTRODUCTION
The coronavirus disease appeared in Wuhan, China, and rapidly turned into a huge global challenge. Previously two other human viruses from the same family emerged in 2002 and 2012, named severe acute respiratory syndrome (SARS-CoV) and Middle East respiratory syndrome (MERS), respectively. There are four structural proteins, spike, envelope, membrane, and nucleocapsid in SARS-CoV-2. The virus recognizes a specific receptor which is found in many parts of the body such as the heart, lungs, intestine, and kidney. The receptor is known as angiotensin-converting enzyme receptor (ACE2). The membrane protein defines the shape of viral envelope. The virus and our body cells work together to make viral proteins. The nucleocapsid or N protein plays multiple functions. In particular, it provokes the defense mechanism of host cells and allows the replication of viral RNA and the development of new viral particles (Hasöksüz et al., 2020).
Nonstructural proteins (NSPs) are encoded by a virus but are not a part of viral particles. There are a total of 16 NSPs (NSP1-NSP16). NSP9 has a length of 113 amino acids and the range is 4141 to 4253 on the genome it is bound with helicase enzyme (Yadav et al., 2021) The NSP9-NSP8 complex is essential for the replication of RNA and functions as a viral virulence factor (Raj, 2021). NSPs plays a vital role in primase activity (Reshamwala, et al., 2021) The NSP11 is similar to the first segment of NSP12 the range is 4393 to 4405 on the genome and has a length of 13 amino acid. The NSP11 plays a part in the action of the endoribonuclease. It appears that NSP11 participates in the replication process. NSP11 is regarded as a target for the development of medications against coronavirus 2 (Yadav et al., 2021).
Due to their increased transmissibility, the potential for significant effects, and/or ability to evade neutralizing antibodies, new SARS-CoV-2 lineages have attracted great attention globally. The initial SARS-CoV-2 variant of concern (VOC), VOC Alpha (B.1.1.7), has been reported to have a 43–90% greater reproduction rate and a 75% more infectiousness than the preceding strains, and it has now become the predominant variety in the United Kingdom and endemic globally. The rate of B.1.1.7 transmission also increased with age and viral load. After that, the Delta (B.1.617.2) variety spread throughout India, outcompeting earlier lineages like B.1.1.7 (Alpha), and COVID-19 cases shot up quickly in various nations throughout the world. These variations are thought to be more infectious and harmful because they manage to elude neutralizing antibodies (Zhao et al., 2022; Shahzaib et al., 2023).
We analyzed the non-structural proteins 9 and 11 for phylogenetic analysis to find the evolutionary relationship amongst these proteins between different variants of the virus from neighboring countries. In this analysis, we used multiple sequence alignment to form an evolutionary tree. The protein structural prediction had been done using the Swiss Model, in order to observe any visible conformational difference among different variants. Ramachandran plot shows the statistical distribution of the combinations of the backbone dihedral angles ϕ and ψ.
MATERIALS AND METHODS
Sequence retrieval from NCBI and phylogenetic analysis
152 sequences of NSP9 (4141-4253) and NSP11(4393-4405) for SARS-COV-2 from USA, Germany, India, Japan, France, Bangladesh, Nepal, Pakistan, Turkey, and reference sequences for variants Alpha, Delta, Kappa, Omicron, First China were retrieved from NCBI (https://www.ncbi.nlm.nih.gov/) (Tables I and II). The sequence alignment was done using CLC-sequence viewer 8.0 under the following parameters: gap open cost, 10; gap extension cost, 1.0 and very accurate progressive algorithm. The phylogenetic analysis showed the differences in the form of distance of different sequences which reveals the close evolutionary relationship and shows common ancestry. Phylogenetic tree of 152 sequences of NSP9 and NSP11 of SARS-CoV-2 was constructed using the neighbor-joining method to confirm the accuracy of phylogenetic tree and the circular cladogram layout was selected in CLC-sequencer viewer 8.0.
Structure prediction
The structural prediction to observe the protein sequences of Alpha, Delta, Omicron, and Original China for NSP9 and NSP11 amino acid length for SARS-CoV-2 using the Swiss Model (Table II). The visualization and analysis of selected SARS-CoV-2 variants for protein structure homology modeling were done using Swiss model. Ramachandran plot, which plots a graph that explains the nature and structure of the amino acid sequence, is also useful in validating the 3D structure of protein.
Table I. Accession numbers of selected NSP9 (4141-4253) and NSP11 (4393-4405) of SARS-CoV-2 from USA, Germany, Japan, India, France, Bangladesh, China, Nepal, Pakistan, Australia, and Turkey.
|
USA |
OK096410, OK096405, OK096405, OP341944, OP341943, OP341942, OP341941, OP341940, OP341939, OP34 1937 OP341938, OP341936, OP341935, OP341934, OP341933, OP341932, OP341931, OP341930, OP341929 OP341928, OP341927, OP341926, OK096397, OK096407, OK096415, OK096416, OK096398, OK096400, OK096401, OK096402, OK096403, OK096399, OK096404, OK096406, OK096408, OK096409, OK096411, OK096412, OK096414, MT558706, MT558705, MT558707, MT558702, MT558703 |
|
Germany |
MT560669, MT560668, MT560670, MT560671, MT560672, MT560674, MT560673, MT560675, MT560677, MT560679, MT560680, MT560682, MT560690, MT560689, MT560694, MT560693, OU975109, OU975111, OU975113, OU975114, OU974925, OU974926, OU974927, OU974929 |
|
India |
MT560669, MT560668, MT560670, MT560671, MT560672, MT560674, MT560673, MT560675, MT560677, MT560679, MT560680, MT560682, MT560690, MT560689, MT560694, MT560693 |
|
Japan |
ON444132, ON444134, ON444137, ON444139, ON444141, ON444143, ON444145, ON444146, ON444153, ON444147, BS005267, BS005268, BS005269, BS005270 |
|
France |
ON444132, ON444134, ON444137, ON444139, ON444141, ON444143, ON444145, ON444146, ON444153, ON444147 |
|
Bangladesh |
MT566434, MT566435, MT566436, MT566437, MT566438, MT566 |
|
China |
ON965799, ON965800, ON965801, ON965802, ON965803 |
|
Nepal |
MZ 157009, MZ157010, MZ157011, MZ157012 |
|
Pakistan |
MT879619, MT560679, MW400961, MW411960 |
|
Australia |
ON819429, ON532671, ON532673, ON532672 |
|
Turkey |
MT560531, MT560530, MT560525 |
Results
Tables I-II shows accession numbers for all the sequence. CLC-sequencer 8.0 provides statistically improved correct alignment for NSP9 (4141-4253) and NSP11 (4393-4405) of SARS-COV-2. A total of 16 mutations were found in the NSP9 region from 2020, 2021, 2022 while 9 mutations were found in NSP11. The phylogenetic analysis showed the differences in the form of distance of different sequences which reveals the close evolutionary relationship and show common ancestry. Phylogenetic tree of 152 sequences of NSP9 and NSP11 of SARS-CoV-2 was constructed using neighbor joining method in CLC-sequencer viewer 8.0 (Fig. 1).
Structural prediction for NSP9 of SARS-CoV-2
The protein sequence of SARS-CoV-2, non-structural protein 9 of Alpha-variant, Delta-varient, Omicron-varient and first China-variant was extracted from NCBI in FASTA format. The structure prediction of the NSP 9 FASTA sequence was conducted using Swiss-model. Because of the absence of apparent differences in the predicted structures of various SARS-CoV-2 variants, only the structure of the alpha variant is shown in Figure 2A as a reference. The Z-Scores of all predicted structures is given in Table III.
Table II. Accession numbers of reference genomic sequences for phylogenetic tree generation and proteomic sequences for structural prediction of NSP9 and NSP11 of the SARS-CoV-2 Alpha (UK), Delta (India), Omicron (South Africa), First China, and Kappa (USA) were retrieved from NCBI.
|
Reference genomic sequences |
Proteomic sequences |
|
|
Alpha (UK) |
OW998408 |
UKQ11044 |
|
Delta (India) |
OX014251 |
QUX81271 |
|
Omicron (South Africa) |
OP093374 |
UUB67348 |
|
Original China |
NC045512 |
YP_009724389 |
|
Kappa (USA) |
MZ157006 |
Ramachandran plot of SARS-CoV-2 NSP9
A protein sequence for NSP9 of SARS-CoV-2 φ (phi) and ψ (psi) torsion angles are plotted in Ramachandra plot shows in Figure 3A.
Structural production for NSP11 of SARS-CoV-2
The protein sequence of SARS-CoV-2, non-structural protein 11 of Alpha-variant, Delta-variant, Omicron-variant and first China-variant was extracted from NCBI in FASTA format. The structural prediction of the NSP11 FASTA sequence was accomplished using Swiss-model. Notably, the structural predictions for various SARS-CoV-2 variants did not reveal any significant differences. Therefore, the structure of alpha variant is shown in Figure 2 as a reference. The Z-Score of predicted SARS-CoV-2 variants is given in Table III.
Table III. QMEAN Z-scores of SARS-CoV-2 NSP9 and SARS-CoV-2 NSPII variants.
|
S. No. |
SARS-CoV-2 variants |
QMEAN Z-score |
||||
|
QMEAN |
Cβ |
All Atom |
Solvation |
Torsion |
||
|
NSP9 |
||||||
|
1 |
Alpha variants |
-2.22 |
-0.91 |
-1.44 |
-1.70 |
-1.35 |
|
2 |
Delta variants |
-1.68 |
-1.06 |
-1.24 |
-0.68 |
-1.63 |
|
3 |
Omicron variants |
-1.41 |
1.26 |
-1.20 |
-0.45 |
-1.49 |
|
4 |
China variants |
-1.68 |
-1.06 |
-1.24 |
0.68 |
-1.63 |
|
NSPII |
||||||
|
1 |
Alpha variants |
-1.08 |
-0.63 |
-1.07 |
-3.31 |
0.58 |
|
2 |
Delta variants |
-2.64 |
-0.88 |
-0.85 |
-3.85 |
-1.22 |
|
3 |
Omicron variants |
-1.02 |
-0.38 |
-0.88 |
-2.52 |
0.15 |
|
4 |
China variants |
-2.67 |
-0.39 |
-0.67 |
-3.31 |
-1.74 |
Ramachandran plot of SARS-CoV-2 NSP11
Protein sequence variant structures for NSP11 of SARS-CoV-2 φ (phi) and ψ (psi) torsion angles are plotted in Ramachandra plot shown in Figure 3B.
DISCUSSION
The coronavirus disease appeared in Wuhan, China, and rapidly turned into a huge global challenge. The NSP9 plays a vital role in RNA binding subunit in the RNA-synthesizing apparatus in the SARS-CoV-2 replication complex. The NSP11 plays a supportive role in the action of the endoribonuclease. It appears that NSP11 participates in the replication process. NSP11 is regarded as a target for the development of medications against coronavirus 2 (Gadhave et al., 2021). Phylogenetic analysis is conducted to find evolutionary relationships within viral genomes from neighboring countries. In this analysis, we used multiple sequence alignment to form an evolutionary tree.
The great majority of SARS-CoV-2 mutations were found to be almost certainly neutral in the beginning of the pandemic (Cagliani et al., 2020). In NSP9 the rate of genetic mutation was far higher as compared to NSP11 which in turn means that NSP11 was more conserved. A total of 16 mutations were found in NSP9 region from 2020, 2021, 2022 while 9 mutations were found in NSP11.
To create a neighbor-joining tree that visually depicts the genetic links and distances among mutants dispersed throughout several nations, we chose the VOC Alpha, Omicron, Wild strain, Kappa, and Delta lineages. Due to host selection forces, mutations may differ between countries. The regional differences in the genome sequence are clear, and some mutation sites are constant throughout nations. Sawmya et al. (2022) performed the phylogenetic analysis of SAR-CoV-2 strains across the globe. Their study revealed that the genomic sequences of China and Italy were closely related to each other. They also found out that the strain of USA, Germany, Qatar, and Poland were similar. In our study for NSP9 region, three Turkish samples fell in the cluster of US. In this cluster, European sequences were also present. Rehman et.al, found the same thing in novel mutations in SARS-CoV-2 isolates from Turkey (Rehman et al., 2020).
We also observed that one of the Pakistani samples was part of the cluster pertaining to other European and Turkey samples cluster. Castillo et al. (2020) this study found out that the European sequences fell in Asian cluster. Other two samples of Pakistan fell in the Asian cluster in which majority of the sequences were from Bangladesh and Japan, while one sample was German, and one was American. American samples were part of almost all the clusters which might indicate frequent travel and introduction of the variants back and forth in American territory. Two major clusters were made up of almost all American samples. Further smaller clusters in these American clusters were observed. One was made up of Australian, China, and German samples. In the 2nd one, German and Indian samples were present. American and German samples tended to fall close to each other in several instances.
A major cluster was made up of Japanese samples, in which two samples were from India, two from Germany, three from Nepal and another from France. Ko et al. (2021) found the Asian sample fell in European countries of whole genome sequences (WGS) of SARS-CoV-2 from throughout Japan and study was subjected to evolutionary analysis by neighbor joining (NJ) method.
First case of Omicron variant was reported from South Africa. For NSP9, the omicron variant fell into the cluster of US, France, Germany, Japan, and Nepal. Jia et al. (2022) and Rehman et al. (2022) found the same thing in the study of SARS-CoV-2 Omicron variant sequences.
NSP11 genomic sequences formed one major cluster and the majority of sequences here were from America. The other samples fell in the Asian subcluster in which majority were from India, Japan, Bangladesh, Nepal, China, Bangladesh, Turkey, Pakistan, and Australia. NSP11 was found to be more conserved.
These findings suggest that while some mutations are inherent in the evolution of SARS-CoV-2, other modifications may result from the virus’s adaptation to a particular country’s social and economic conditions, medical care, sex-age ratio, and environmental factors. The identification of certain substitutions is useful for virus tracing for strains that have established stable Lineage. Further research is needed to determine whether and how these mutations affect the infectivity and immunogenicity of SARS-CoV-2.
On close protein sequences analysis, we found that Alpha and first China variant showed VAL position at 4 b-sheet but delta and omicron showed VAL at 7b-sheet. Some changes were predicted in receptor-binding domain resulting in the reduction of antibody interaction. Although none of the variants have shown any visible change in 3d structure, the local quality estimates and Z-Scores vary for all.
To improve global viral surveillance, we must actively monitor the effects of current genetic changes and keep an eye out for any new ones. To stop widespread local transmission, imported illnesses should be quarantined and watched over. In order to make preventive and control policy more accurate and scientific in the future, normalized epidemic prevention and control measures must be optimized.
Conclusion
We conclude that the rate of genetic mutation was far higher in the NSP9 region as compared to NSP11. American samples were part of almost all the clusters which might indicate frequent travel and introduction of the variants back and forth in American territory. In this study we observed that the behavior of viruses and mutations of different countries are closely related to each other. Observing the genomic behavior of viruses is important in order to find out the nature of the viral mutations, any patterns hidden in those to tackle further complications that can arise in future. Region-wise monitoring of genetic changes can also play a role in development of specified vaccines and help regulatory agencies to plan an appropriate strategy to fight the virus.
Statement of conflict of interest
The authors have decalred no conflict of interest.
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