Novel Mutations in the Non-Structure Protein 2 of SARS-CoV-2

Mohsen Nakhaie1,2,*, Zohreh-al-sadat Ghoreshi3,4,*, Mohammad Rezaei Zadeh Rukerd2,5, Hedyeh Askarpour3 and Nasir Arefinia3,6.

Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran.
2 Gastroenterology and Hepatology Research Center, Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences, Kerman, Iran.
3 School of Medicine, Jiroft University of Medical Sciences, Jiroft, Iran.
4 Student Research Committee Jiroft University of Medical Sciences, Jiroft, Iran.
5 Universal Scientific Education and Research Network (USERN), Tehran, Iran.
6 Bio Environmental Health Hazard Research Center, Jiroft University of Medical Sciences, Jiroft, Iran.
* The authors equally contributed to the work.

Correspondence to: Nasir Arefinia, School of Medicine, Jiroft University of Medical Sciences, Jiroft, Iran. Tel: +9834-42652781, FAX: +9871-42710780. E-mail:,

Published: November 1, 2023
Received: June 10, 2023
Accepted: October 12, 2023
Mediterr J Hematol Infect Dis 2023, 15(1): e2023059 DOI 10.4084/MJHID.2023.059

This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Introduction: Mutation in the genome of SARS-CoV-2 may play a role in immune evasion, pathogenicity, and speed of its transmission. Our investigation aimed to evaluate the mutations that exist in the NSP2.
Materials and Method: RNA was extracted from nasopharyngeal swabs from 100 COVID-19 patients. RT-PCR was performed on all samples using NSP2-specific primers. Following gel electrophoresis, the bands were cut, purified, and sequenced using the Sanger method. After sequencing, 90 sequences could be used for further analysis. Bioinformatics analysis was conducted to investigate the effect of mutations on protein structure, stability, prediction of homology models, and phylogeny tree.
Results: The patients' mean age was 51.08. The results revealed that 8 of the 17 NSP2 mutations (R207C, T224I, G262V, T265I, K337D, N348S, G392D, and I431M) were missense. One deletion was also found in NSP2. Among NSP2 missense mutations studied, K337D and G392D increased structural stability while the others decreased it. The homology-designed models demonstrated that the homologies were comparable to the sequences of the Wuhan-HU-1 virus.
Conclusion: Our study suggested that the mutations K337D and G392D modulate the stability of NSP2, and tracking viral evolution should be implemented and vaccine development updated.


Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the COVID-19 disease, is a highly contagious respiratory pathogen.[1] COVID-19 initially emerged in Wuhan, China, in December 2019 and has spread rapidly worldwide, leading to a global pandemic.[2,3] COVID-19 symptoms can manifest in a range of mild to severe forms, including fever, cough, shortness of breath, fatigue, loss of taste or smell, and more rarely, gastrointestinal bleeding, pneumonia, acute respiratory distress syndrome (ARDS), and even death.[4-6] As of May 21, 2023, approximately 766 million cases of SARS-CoV-2 have been recorded, along with 6.9 million reported deaths.[7,8] The genome sequencing analysis of SARS-CoV-2 and SARS, conducted through the novel Coloured Genomic Bootstrap (CGB) barcoding method, reveals that despite the presence of genomic regions with mixed ancestry derived from horseshoe bat viruses, a predominant over 97% of their genomes originates from bats located in Yunnan, China.[9,10] However, another possibility is that the virus could have infected other mammals and transferred to the human population through the live animal market in Wuhan.[11,12]
The SARS-CoV-2 genome has an approximate size of 29.8 kb and consists of 14 open reading frames (ORFs).[13] ORF1a and ORF1b are cleaved into 15 non-structural proteins (NSP) including NSP1 to NSP10, and NSP12 to NSP16, by enzymatic function of NSP3 (papain-like protease) and NSP5 (chymotrypsin like protease).[14,15] The NSP2 disrupts host signaling during infection by interacting with Prohibitin 1 (PHB1) and Prohibitin 2 (PHB2), which are components of the mitochondrial prohibitin complex.[16,17] In addition, NSP2 plays a role in regulating calcium homeostasis within cells, post-transcriptional suppression, and associates with seven cellular proteins involved in vesicular trafficking.[14,18,19] Finally, NSP2, by initiating translational suppression, not only enables SARS-CoV-2 to evade the Interferon type I response but also contributes to inflammation by activating NF-κB.[20,21]
SARS-CoV-2 mutations can significantly affect viral circulation, immune evasion, and pathogenicity.[22] Frequent genetic variations in viruses can often result in drug resistance or the evasion of effective vaccination strategies.[23-25] As the virus spreads, it can help to survive in the host cell by introducing mutations and altering the structure of its proteins.[26] Viral polymerase, due to its limited or absent proof-reading activity, can lead to frequent mutations.[27] One of the key areas of concern has been the genetic variability in SARS-CoV-2 genomes. Recent research has identified sixty-one mutations, primarily concentrated in NSP3, RNA-directed RNA polymerase (RdRp), and Nucleocapsid proteins.[28] In-depth analysis of 59,541 SARS-CoV-2 genomic sequences revealed significant mutations, with certain mutations such as T85I and Q57H proving deleterious, while P323L exhibited a stabilizing effect, offering insights into the virus's evolutionary dynamics and potential impact on pathogenesis.[29] The rapid mutation rate of SARS-CoV-2 has resulted in the emergence of new viral variants, particularly in the spike protein's receptor-binding domain (RBD). These mutations can potentially enhance viral transmission, increase disease severity, and potentially reduce the effectiveness of immune responses, monoclonal antibody treatments, and vaccines.[30] Additionally, distinctive mutations in the SARS-CoV-2 ORF1ab polyprotein (265 T→I, 4715 P→L, 5828 P→L, and 5865Y→C) serve as a signature for the United States, altering nonstructural protein structures and emphasizing their relevance in antiviral therapeutic design.[31]
 The absence of the NSP2 protein may compromise viral replication, leading to a defect;[32,33] however, it is important to note that viable viruses can still be produced despite its removal.[34,35] Furthermore, genome sequencing of SARS-CoV-2 variants during the COVID-19 pandemic revealed sites of positive selection in NSP2, indicating the adaptation of humans as a specific host following successful zoonotic co-transmission.[36] Importantly, the observed inability to rescue this defect by expressing NSP2 from an alternative genomic site highlights the indispensable role of the timing of NSP2 expression.[37,38] Despite the recent decrease in infected cases, the possibility of further waves of infection is worrying. However, there is also optimism that these potential outbreaks can be prevented or reduced with careful measures and surveillance.[25]
The studies of many researchers have been realized on the SARS-CoV-2 replication mechanism, pathogenicity, and therapeutic strategies. The aim of this study was to provide information about virus mutation, which has important implications for disease progression and the development of drugs or vaccines. In order to achieve this aim, the Open Reading Frame 1ab (ORF1ab) of SARS-CoV-2 was analyzed to evaluate the mutations caused by selection pressure on the virus and their impact on viral protein stability to infect human hosts, thereby promoting epidemic spread.

Materials and Methods

Participants and Study Design. 100 COVID-19 patients were selected for the study from June to September 2022 at Shafa Hospital, affiliated with Kerman University of Medical Science, Kerman, Iran. The inclusion criteria for the study involved patients who satisfied the diagnostic standard for COVID-19.[39] The other inclusion criteria for study participants encompass the following conditions: 1) purification kit (Qiagen GmbH, Germany). After purification, it is sent to Baseline 1 (Gemini) company for sequencing via the Applied Biosystems 3730xl DNA Analyzer. Of the total sequences submitted, 90 Confirmation of SARS-CoV-2 infection through a throat swab with a cycle threshold (Ct) value less than 24, 2) Manifestation of clinical symptoms such as chest pain, cough with bloody or purulent sputum, diarrhea, dehydration, vomiting, and dyspnea, 3) Absence of reported symptoms associated with underlying medical conditions, and 4) Non-receipt of any of the existing COVID-19 vaccinations. A structured questionnaire was obtained for demographic information, medical history, breath number, and temperature. Before participation, all individuals provided written informed consent, and the Ethics Committee of Kerman University of Medical Sciences approved the study (IR.KMU.REC.1402.024).
Samples. All patients underwent nasopharyngeal sample collection through the use of a specific swab. Samples are transferred to viral transfer media (VTM) and then translocated by a cool box.
Extraction of RNA. RNA isolation kit (Product no: 11856022001, Roje) was utilized to extract viral RNA from oropharynx/nasopharynx samples following the manufacturer's instructions. The concentration and purity of the extracted RNA were evaluated by measuring 1 μl of each sample with NanoDrop™ 2000 (Thermo Scientific, USA). Also, RNA integrity was assessed for its quality control by running 4 μl of the extracted RNA along with 2 μl Loading Day on 2% agarose gel.
Sequencing of NSP2. The extracted RNA samples were converted to complementary DNA (cDNA) using cDNA synthesis kits (Yekta-Tajhiz, Iran) according to the manufacturer’s instructions. The sequencing of NSP2 of the ORF1ab gene was performed on 90 confirmed cases of COVID-19. The NCBI database and AlleleID software were used to extract the sequence of NSP2 and the design of specific primers for the target region, respectively. Conventional PCR techniques with Eppendorf Mastercycler were used to amplify the NSP2. PCR conditions included 1X PCR buffer, 300 - 400 ng of template cDNA, 1 mM MgCl2, 100 mM deoxynucleotide triphosphates (dNTPs), 10 pmol of each primer, and 0.5 U of Taq polymerase in a total volume of 25 µL. The PCR thermal profile was 95°C for 5 min, followed by 40 cycles of 95°C for 45 second, 59.4°C for 45 second, 72°C for 35 second, and a final extension for 5 min at 72°C. The primer sequence and annealing temperatures used for NSP2 amplification have been shown in Table 1.

Table 1
Table 1. The NSP2-specific primer sequences utilized for RT-PCR.

For band detection, the products of the PCR amplification were subjected to electrophoresis on a 1.5% agarose gel using a 100 bp molecular weight marker. The bands corresponding to the 970bp studied region were located and excised from the gel for purification through the MinElute electrophoresis band results were clear and perfect for further analysis, including CLC6 and Clustal Omega for aligning and supplementing to obtain the sequence. The sequences were cross-referenced with existing databases to validate the results using the BLAST online search tool at Furthermore, the sequences were compared to the reference strain Wuhan-Hu to identify any related mutations by utilizing Clustal Omega.
Variations of nucleotide. We conducted multiple sequence alignments to identify any nucleotide variations by using Clustal Omega.[40] The reference genome was the Whuhan-Hu-1 strain sequence, with GenBank accession number 045512. Clustal Omega's MVIEW program was used to analyze the alignment file.[41]
Variations of amino acid. Each protein's multiple sequence alignment was analyzed using MVIEW after being aligned again with Clustal Omega. In addition, amino acid variation was detected by comparing it to the reference strain protein.
The impacts of genetic mutations. Different prediction tools were employed to examine missense mutations' stability change and structural consequences. Specifically, I-mutant was utilized to determine structure stability.[26] Furthermore, Mutpred2 was employed to predict the molecular consequences and functional impact of missense mutations.[42]
Molecular Dynamic Simulations. Molecular dynamic (MD) simulations were performed using GROMACS96 43a1 program with CHARMM27 force field.[43] Each system was solvated with TIP3P water with a minimal distance of 1.0 nm between the solute and the wall of the dodecahedron box. Ionization states were assigned to titratable residues corresponding to the pH 7.0 condition. A proper amount of Na and Cl ions was added instead of water molecules to imitate an ionic strength of 0.15 M. The system was then energy minimized using the steepest descent algorithm with an initial step size of 0.01 nm for a maximum force of 1000 kJ/mol/nm and a maximum of 50,000 steps. Then, a 100-ps-long unconstrained equilibration MD simulation was done at a constant temperature (300 K) and pressure using Berendsen and Parrinello–Rahman coupling methods. Pressure coupling was performed using a reference pressure of 1.0 bar and a time constant of 1.0 ps. Finally, a 50-ns-long production MD simulation was performed at a constant temperature of 300 K, maintained by the v-rescale thermostat.
Phylogenetic analysis. Phylogenetic and sequence analyses were conducted to investigate the evolutionary relationships between different isolates. Of the 90 samples with clear and complete sequencing results, 39 were selected for constructing the phylogenetic tree. The remaining cases were excluded either due to the similarity in their mutations or the absence of mutations in their sequences, which would hinder the construction of the phylogenetic tree. Reference sequences from the Wuhan strain and concerning variants, including B.1.1.617.2, B.1.1.7, B.1.1.529, B.1.351, and P.1, were used for analysis and phylogenetic tree construction. Clustering of sequences was performed with MEGA 11software, followed by inference of evolutionary history using the Maximum Likelihood method with ~1000 bootstrap iterations.


Demographic data. Out of the total submitted sequences, 90 results for NSP2 having clear and complete sequencing were included. The nucleic acid sequences were obtained from 48 males and 42 females, and patients' mean ages were 51.08.
The SARS-CoV-2 variant classification. The SARS-CoV-2 variant classification refers to categorizing different strains or variants of the SARS-CoV-2 virus based on specific genetic mutations or changes in its genome. These variants are identified through genomic sequencing and analysis, which helps understand the spread, evolution, and potential impact of different viral lineages. The classification typically involves assigning names or designations to different variants based on their specific mutations, such as Alpha/B.1.1.7, Beta/B.1.351, Gamma/P.1, Delta/B.1.1.617.2, Omicron/B.1.1.529, and so on. The variant classification provides important information for monitoring the virus's global spread assessing its transmissibility, virulence, and potential impact on diagnostics, therapeutics, and vaccines. It helps researchers, public health authorities, and healthcare professionals to track and respond to the emergence and prevalence of different SARS-CoV-2 variants.
Mutations found in SARS-CoV-2 isolates from Kerman. All 90 Kerman isolates' analysis showed 17 Single-nucleotide polymorphisms (SNP) in the NSP2. A deletion was also identified for NSP2 isolate (Table 2). Out of 17 mutations, there were 8 missense mutations in positions 207, 224, 262, 265, 337, 348, 392, and 431, whereas the remaining mutations were synonymous (Table 3).

Table 2 Table 2. Demographic information of the study patients.

Table 3 Table 3. The type of mutation and the position of the mutations detected in amino acid and nucleotide in NSP2.

Effects of various mutations in NSP2. Six of the eight missense mutations identified in NSP2 indicated decreased structural stability. In addition, two remaining mutations have an increase in stability of structural (Table 4).

Table 4
Table 4. Predicting the stability of NSP's structure under the influence of missense mutations.

Root mean square deviation. Root mean square deviation (RMSD) was also used to investigate the stability of the structures further. It was assessed during the 50-ns MD simulation runs for WT nsp2 and R207C, T224I, G262V, T265I, K337D, N348S, G392D, I431M nsp2 systems. Unlike other mutations, the RMSD in the K337D (Purple) and the G392D (Brown) mutation were lower compared to the wild variant, indicating that these mutations were more structurally stable (Figure 1).

Figure 1
Figure 1. Root mean square deviation (RMSD) in nm was depicted for wild-type (WT) (Blue), R207C (Orange), T224I (Dark blue), G262V (Yellow), T265I 
(Light gray), K337D (Light blue), N348S (Green), G392D (Brown), I431M (Dark gray) NSP2s during the 50-ns molecular dynamic (MD) simulations.

Anticipation and verification of homology model predictions. Nine models were produced for NSP2 using the PDB ID 7MSX as a template: the eight models were for the Kerman isolate, and the remaining one was for the reference strain. Mutant models 1 to 8 are designed for R207C, T224I, G262V, T265I, K337D, N348S, G392D, and I431M mutations, respectively. The reliability of these 8 models was assessed with validation assessment scores, which were similar to the template (Table 5).

Table 5
Table 5. Reliability assessment of different mutant Models.

Phylogenetic analysis. In this study, we compared the NSP2 sequencing results to globally registered concern variants and provided detailed specifications in Figure 2. According to our study, the predominant SARS-CoV-2 viruses circulating were comparable to the Delta/B.1.617.2 variant (Figure 2). In addition, we found that the NSP2 variant of concern (VOCs) prevalence with Pangolin Lineages Delta was 89.74% while Omicron/B.1.1.529 accounted for 5.1% (Figure 2).

Figure 2
Figure 2.. Phylogenetic tree. The evolutionary NSP2 was depicted through a phylogenetic tree. The tree was constructed using MEGA software, the Maximum 
Likelihood method (~1000 bootstrap), and the Tamura model.


The COVID-19 pandemic has emerged as a worldwide crisis.[24] Viral genome mutations and subsequent modification of viral proteins are common ways for viruses to escape from the immune system response and survive within the host for extended periods.[34,37] Although cases of the disease have decreased recently, there are still concerns about the possibility of further waves of infection.[36,38] This study analyzed the sequencing of SARS-CoV-2 in Kerman, Iran, and identified variations that could offer insights into the virus's pathogenesis, genetic diversity of NSP2, and the potential impact of mutations. A total of 17 mutations were detected; 8 mutations were related to missense mutation, including R207C, T224I, G262V, T265I, K337D, N348S, G392D, I431M, and N348S, and one mutation was related to deletion.
The NSP2 contains two functional clusters, one containing three proteins involved in vesicle transport.[44] In our study, some mutations, such as V1883T and R207C, occurred in this cluster, which may result in the effective virus release from the endosome. The remaining cluster comprises eight proteins associated with ribosome assembly and has the potential to obstruct the transcription and translation process of human mRNAs.[45] Other mutations in this cluster include T224I, G262V, and T265I, which may alter the pathogenic pathway of SARS-CoV-2 by interfering with proteins or cellular signaling. A prior investigation has demonstrated that NSP2 may impact calcium homeostasis, and alterations such as N348S and I431M mutations could potentially modify its function. This modification is significant because apoptosis is a crucial mechanism for host cell defense against SARS-CoV-2 infection.[46] According to the identification of these mutations in our study, it is possible that the variants caused by mutations can alter cell apoptosis by altering calcium homeostasis. On the other hand, some RNA-binding proteins, such as STAU2, play an anti-apoptotic role in DNA replication and genome integrity maintenance.[47] The binding of SARS-CoV-2 NSP2 protein to STAU2 may inhibit its anti-apoptotic function,[48] and the mutations in NSP2 may affect this interaction.
The NSP2 can interact with some of the guanine nucleotide exchange factors such as RAP1GDS1, and by changing the activity of some small GTPases, it might aggravate or alleviate lung inflammation during SARS-2 infection,[14,49] which is consistent with the mutations identified in our study. Many organelles, including endosomes, lysosomes, and exosomes, have protein complexes such as V-ATPase in their membranes, which transfer protons to the organelle to maintain the acidic environment. During SARS-CoV-2 infection, researchers have demonstrated that NSP2 interacts with some subunits of V-ATPase and is involved in transporting substances such as Ca2+.[50] Therefore, some mutations that occurred in NSP2 can change the interaction between it and V-ATPase and may participate in induced during endocytosis.
In addition, NSP2 could be considered one of the targets of laboratory diagnosis for SARS-CoV-2 by rapid and real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). In their study, Yip et al. identified a 154 nucleotide fragment as a conserved region for detecting SARS-CoV-2.[51] Therefore, any mutation at the 1867 position in our study could potentially fail to identify SARS-CoV-2 patients. Continuously monitoring mutations will be crucial to track the virus's spread among individuals and across different regions.
Another mutation was responsible for deletion. Large deletion mutations can cause a defect in the production and function of the desired protein. In this regard, some scientists have suggested that large deletions in OFR1ab may not encode the target protein.[52] Large deletion mutations have also been found in the studies of other scientists; for instance, an 80-nucleotide deletion in ORF7a was also reported in a study conducted in Arizona.[53]
In concordance with our study, Banerjee et al. identified a prevalent mutation, specifically T265I, within the NSP2 gene. Their research spanned 31 different states across the United States, involving the examination of 867 complete protein sequences of ORF1ab. Notably, they found that among the genes comprising the ORF1ab region, which constitutes approximately two-thirds of the SARS-CoV-2 genome, the T265I mutation exhibited the highest incidence, accounting for around 50%. These findings are consistent with our investigation, as the NSP gene is known to influence mitochondrial function, manage cellular stress, and modulate host cell survival signaling pathways by interacting with PHB and PHB2 proteins within the host organism. Consequently, the T265I mutation in this gene may confer advantages to the virus in these processes.[31] In alignment with the findings of Koyama et al., our study has also highlighted the significance of the G392D mutation in the context of SARS-CoV-2 evolution and its potential impact on viral stability. Koyama et al.'s comprehensive analysis of over 10,000 SARS-CoV-2 genomes from diverse geographical regions revealed a spectrum of genetic variants, including the G392D mutation.[54]


Our study delves into the intricate realm of SARS-CoV-2 evolution, shedding light on crucial aspects contributing to its adaptability and potential impact on public health. Notably, we have elucidated a spectrum of variations within NSP2, uncovering a nuanced narrative of viral stability. While some genetic variations may undermine NSP2 stability, intriguingly, others, such as K337D and G392D, appear to bolster it. This dualistic insight into NSP2's stability diversification adds a novel layer to our understanding of the virus's adaptive mechanisms. Our work also extends beyond the realm of basic research. The homology models we have meticulously designed to elucidate the structural consequences of NSP2 mutations provide a valuable resource for future studies aiming to decipher the functional implications of these genetic changes. Importantly, these models align with the Wuhan strain and reveal a striking resemblance to the Delta variant, underscoring the relevance of our findings in the context of contemporary viral evolution.
Furthermore, our findings carry significant implications for public health. We emphasize the pressing need for continuous surveillance of genomic variations within SARS-CoV-2, especially in the face of emerging variants like Delta, to inform the development of effective treatment strategies and updated vaccines. In conclusion, our research offers a comprehensive and nuanced perspective on SARS-CoV-2 evolution, accentuating our unique insights into NSP2 variations, their structural implications, and their relevance in contemporary viral landscapes. This multi-faceted contribution advances our understanding of the virus and provides a foundation for future investigations to combat the ongoing global health challenge.


The authors thank the Research Consultation Center for improving the article's writing.


This work was supported by Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran (Grant numbers 401000085). Author Mohsen Nakhaie has received research support from the Kerman University of Medical Sciences.

Author Contributions

NA, ZG designed the study, and NA Analyzed the data. NA and MN Contributed new methods or models. NA and ZG wrote the paper. MRZR, NA, and MN reviewed and finalized the manuscript. All authors read and approved the final manuscript.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Kerman University of Medical Science (IR.KMU.REC.1402.024).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent to publish.

The authors affirm that human research participants provided informed consent for publication.


  1. Lai CC, Shih TP, Ko WC, Tang HJ, Hsueh PR. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges. Int J Antimicrob Agents. 2020 Mar;55(3):105924. PMid:32081636 PMCid:PMC7127800  
  2. Shi J, Chen F, Chen S, Ling HQ. COVID-19 over the last three years in China, what we've learned. Front Public Health. 11:1209343. PMid:37522001 PMCid:PMC10374005  
  3. Listings of WHO's response to COVID-19 [Internet]. [cited 2023 Sep 29]. Available from:  
  4. Arefinia N, Ghoreshi Z al S, Alipour AH, Reza Molaei H, Samie M, Sarvari J. Gastrointestinal Manifestations in Patients Infected with SARS-CoV-2. Iran J Med Microbiol. 2022 Jul 10;16(4):271-81.  
  5. Shafieipour S, Mohammadi E, Rukerd MRZ, Momenai R, Lashkarizadeh MM, Zahedi MJ, et al. Gastrointestinal Bleeding: Prevalence, Etiology, and Outcomes in COVID-19 Inpatients. GOVARESH. 2023 May 24;28(1):30-5.
  6. COVID-19 symptoms and severity [Internet]. [cited 2023 Sep 29]. Available from:
  7. Weekly epidemiological update on COVID-19 - 25 May 2023 [Internet]. [cited 2023 Jul 14]. Available from:  
  8. St Clair LA, Chan LLY, Boretsky A, Lin B, Spedding M, Perera R. High-throughput SARS-CoV-2 antiviral testing method using the Celigo Image Cytometer. J Fluoresc. 2023;1-10. PMid:37310590 PMCid:PMC10261830  
  9. Wang LF, Eaton BT. Bats, civets and the emergence of SARS. Wildl Emerg Zoonotic Dis Biol Circumst Consequences Cross-Species Transm. 2007;325-44. PMid:17848070 PMCid:PMC7120088  
  10. Hassanin A, Rambaud O. Retracing Phylogenetic, Host and Geographic Origins of Coronaviruses with Coloured Genomic Bootstrap Barcodes: SARS-CoV and SARS-CoV-2 as Case Studies. Viruses. 2023;15(2):406. PMid:36851620 PMCid:PMC9961909  
  11. Zhang N, Wang L, Deng X, Liang R, Su M, He C, et al. Recent advances in the detection of respiratory virus infection in humans. J Med Virol. 2020;92(4):408-17. PMid:31944312 PMCid:PMC7166954  
  12. Brüssow H. Viral infections at the animal-human interface-Learning lessons from the SARS‐CoV‐2 pandemic. Microb Biotechnol. 2023; PMid:37338856 PMCid:PMC10281366  
  13. Zhang Y, Huang Z, Zhu J, Li C, Fang Z, Chen K, et al. An updated review of SARS‐CoV‐2 detection methods in the context of a novel coronavirus pandemic. Bioeng Transl Med. 2023;8(1):e10356. PMid:35942232 PMCid:PMC9349698  
  14. Zheng YX, Wang L, Kong WS, Chen H, Wang XN, Meng Q, et al. Nsp2 has the potential to be a drug target revealed by global identification of SARS-CoV-2 Nsp2-interacting proteins. Acta Biochim Biophys Sin. 2021 Aug 31;53(9):1134-41. PMid:34159380  
  15. Agrawal PK, Agrawal C, Blunden G. Antiviral and Possible Prophylactic Significance of Myricetin for COVID-19. Nat Prod Commun. 2023;18(4):1934578X231166283.  
  16. Cornillez-Ty CT, Liao L, Yates JR 3rd, Kuhn P, Buchmeier MJ. Severe acute respiratory syndrome coronavirus nonstructural protein 2 interacts with a host protein complex involved in mitochondrial biogenesis and intracellular signaling. J Virol. 2009 Oct;83(19):10314-8. PMid:19640993 PMCid:PMC2748024  
  17. Kabekkodu SP, Chakrabarty S, Jayaram P, Mallya S, Thangaraj K, Singh KK, et al. Severe acute respiratory syndrome coronaviruses contributing to mitochondrial dysfunction: Implications for post-COVID complications. Mitochondrion. 2023;69:43-56. PMid:36690315 PMCid:PMC9854144  
  18. Davies JP, Almasy KM, McDonald EF, Plate L. Comparative multiplexed interactomics of SARS-CoV-2 and homologous coronavirus non-structural proteins identifies unique and shared host-cell dependencies. bioRxiv : the preprint server for biology. United States; 2020.  
  19. Senthilazhagan K, Sakthimani S, Kallanja D, Venkataraman S. SARS-CoV-2: analysis of the effects of mutations in non-structural proteins. Arch Virol. 2023 Jun 21;168(7):186. PMid:37344726  
  20. Xu Z, Choi JH, Dai DL, Luo J, Ladak RJ, Li Q, et al. SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation. Proc Natl Acad Sci U S A. 2022 Aug 9;119(32):e2204539119. PMid:35878012 PMCid:PMC9371684  
  21. Lacasse É, Gudimard L, Dubuc I, Gravel A, Allaeys I, Boilard É, et al. SARS-CoV-2 Nsp2 Contributes to Inflammation by Activating NF-κB. Viruses. 2023 Jan 24;15(2):334. PMid:36851549 PMCid:PMC9964531  
  22. Sun C, Xie C, Bu GL, Zhong LY, Zeng MS. Molecular characteristics, immune evasion, and impact of SARS-CoV-2 variants. Signal Transduct Target Ther. 2022 Jun 28;7:202. PMid:35764603 PMCid:PMC9240077  
  23. Delshad M, Sanaei MJ, Pourbagheri-Sigaroodi A, Bashash D. Host genetic diversity and genetic variations of SARS-CoV-2 in COVID-19 pathogenesis and the effectiveness of vaccination. Int Immunopharmacol. 2022;109128. PMid:35963158 PMCid:PMC9359488
  24. Yuen KS, Ye ZW, Fung SY, Chan CP, Jin DY. SARS-CoV-2 and COVID-19: The most important research questions. Cell Biosci. 2020;10(1):1-5. PMid:32190290 PMCid:PMC7074995  
  25. Khailany RA, Safdar M, Ozaslan M. Genomic characterization of a novel SARS-CoV-2. Gene Rep. 2020;19:100682. PMid:32300673 PMCid:PMC7161481  
  26. Capriotti E, Fariselli P, Casadio R. I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 2005 Jul 1;33(suppl_2):W306-10. PMid:15980478 PMCid:PMC1160136
  27. Herman C, Bradley C, Gordon A, Wang C, Cooke M, Kohrn B, et al. RNA polymerase inaccuracy underlies SARS-CoV-2 variants and vaccine heterogeneity. Research square. United States; 2022.  
  28. Periwal N, Rathod SB, Pal R, Sharma P, Nebhnani L, Barnwal RP, et al. In silico characterization of mutations circulating in SARS-CoV-2 structural proteins. J Biomol Struct Dyn. 2022 Nov;40(18):8216-31. PMid:33797336 PMCid:PMC8043164
  29. Periwal N, Rathod SB, Sarma S, Johar GS, Jain A, Barnwal RP, et al. Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations. Microbiol Spectr. 2022 Oct 26;10(5):e0121922. PMid:36069583 PMCid:PMC9603882  
  30. Flores-Vega VR, Monroy-Molina JV, Jiménez-Hernández LE, Torres AG, Santos-Preciado JI, Rosales-Reyes R. SARS-CoV-2: Evolution and Emergence of New Viral Variants. Viruses. 2022 Mar 22;14(4):653. PMid:35458383 PMCid:PMC9025907  
  31. Banerjee S, Seal S, Dey R, Mondal KKr, Bhattacharjee P. Mutational spectra of SARS‐CoV‐2 orf1ab polyprotein and signature mutations in the United States of America. J Med Virol. 2021 Mar;93(3):1428-35. PMid:32779784 PMCid:PMC7436414  
  32. Meshram CD, Lukash T, Phillips A, Akhrymuk I, Frolova EI, Frolov I. Lack of nsP2-specific nuclear functions attenuates chikungunya virus replication both in vitro and in vivo. Virology. 2019 Aug;534:14-24. PMid:31163352 PMCid:PMC7204530  
  33. Cherkashchenko L, Rausalu K, Basu S, Alphey L, Merits A. Expression of Alphavirus Nonstructural Protein 2 (nsP2) in Mosquito Cells Inhibits Viral RNA Replication in Both a Protease Activity-Dependent and -Independent Manner. Viruses. 2022 Jun 17;14(6):1327. PMid:35746799 PMCid:PMC9228716  
  34. Graham RL, Sims AC, Brockway SM, Baric RS, Denison MR. The nsp2 replicase proteins of murine hepatitis virus and severe acute respiratory syndrome coronavirus are dispensable for viral replication. J Virol. 2005 Nov;79(21):13399-411. PMid:16227261 PMCid:PMC1262610  
  35. Zhang L, Shen M, Ma X, Su S, Gong W, Wang J, et al. What is required to prevent a second major outbreak of SARS-CoV-2 upon lifting quarantine in Wuhan City, China. The Innovation. 2020;1(1):100006. PMid:33458717 PMCid:PMC7237941
  36. Zhao J, Sun J, He WT, Ji X, Gao Q, Zhai X, et al. Snapshot of the evolution and mutation patterns of SARS-CoV-2. bioRxiv. 2020 Jan 1;2020.07.04.187435.
  37. Gadlage MJ, Graham RL, Denison MR. Murine coronaviruses encoding nsp2 at different genomic loci have altered replication, protein expression, and localization. J Virol. 2008 Dec;82(23):11964-9. PMid:18815297 PMCid:PMC2583644
  38. Hodcroft EB, Domman DB, Oguntuyo K, Snyder DJ, Diest M Van, Densmore KH, et al. Emergence in late 2020 of multiple lineages of SARS-CoV-2 Spike protein variants affecting amino acid position 677. medRxiv. 2021 Jan 1;2021.02.12.21251658.
  39. Emergency F, Only U, Only R. Real-Time RT-PCR Diagnostic Panel For Emergency Use Only. 2021.
  40. Madeira F, Park Y mi, Lee J, Buso N, Gur T, Madhusoodanan N, et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019 Jul 2;47(W1):W636-41. PMid:30976793 PMCid:PMC6602479 
  41. Malik JA, Ahmed S, Mir A, Shinde M, Bender O, Alshammari F, et al. The SARS-CoV-2 mutations versus vaccine effectiveness: New opportunities to new challenges. J Infect Public Health. 2022;15(2):228-40. PMid:35042059 PMCid:PMC8730674  
  42. Pejaver V, Urresti J, Lugo-Martinez J, Pagel KA, Lin GN, Nam HJ, et al. Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nat Commun. 2020;11(1):1-13. PMid:33219223 PMCid:PMC7680112  
  43. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015 Sep 1;1-2:19-25.  
  44. Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K, White KM, et al. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. 2020;583(7816):459-68. PMid:32353859 PMCid:PMC7431030 
  45. Banerjee AK, Blanco MR, Bruce EA, Honson DD, Chen LM, Chow A, et al. SARS-CoV-2 Disrupts Splicing, Translation, and Protein Trafficking to Suppress Host Defenses. Cell. 2020 Nov;183(5):1325-1339.e21. PMid:33080218 PMCid:PMC7543886  
  46. Daniloski Z, Jordan TX, Wessels HH, Hoagland DA, Kasela S, Legut M, et al. Identification of Required Host Factors for SARS-CoV-2 Infection in Human Cells. Cell. 2021 Jan;184(1):92-105.e16. PMid:33147445 PMCid:PMC7584921  
  47. Zhang X, Trépanier V, Beaujois R, Viranaicken W, Drobetsky E, DesGroseillers L. The downregulation of the RNA-binding protein Staufen2 in response to DNA damage promotes apoptosis. Nucleic Acids Res. 2016 May;44(8):3695-712. PMid:26843428 PMCid:PMC4856980  
  48. Oberdoerffer S, Moita LF, Neems D, Freitas RP, Hacohen N, Rao A. Regulation of CD45 alternative splicing by heterogeneous ribonucleoprotein, hnRNPLL. Science. 2008 Aug;321(5889):686-91. PMid:18669861 PMCid:PMC2791692
  49. Hamel B, Monaghan-Benson E, Rojas RJ, Temple BRS, Marston DJ, Burridge K, et al. SmgGDS is a guanine nucleotide exchange factor that specifically activates RhoA and RhoC. J Biol Chem. 2011;286(14):12141-8. PMid:21242305 PMCid:PMC3069418
  50. Zhao W, Gao X, Qiu S, Gao B, Gao S, Zhang X, et al. A subunit of V-ATPases, ATP6V1B2, underlies the pathology of intellectual disability. EBioMedicine. 2019 Jul;45:408-21. PMid:31257146 PMCid:PMC6642280
  51. Yip CCY, Ho CC, Chan JFW, To KKW, Chan HSY, Wong SCY, et al. Development of a Novel, Genome Subtraction-Derived, SARS-CoV-2-Specific COVID-19-nsp2 Real-Time RT-PCR Assay and Its Evaluation Using Clinical Specimens. Int J Mol Sci. 2020 Apr;21(7). PMid:32276333 PMCid:PMC7177594
  52. Alam S, Mahfujur M, Morshed N. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information. 2020;(January).
  53. Mercatelli D, Giorgi FM. Geographic and genomic distribution of SARS-CoV-2 mutations. Front Microbiol. 2020;11:1800. PMid:32793182 PMCid:PMC7387429
  54. Koyama T, Platt D, Parida L. Variant analysis of SARS-CoV-2 genomes. Bull World Health Organ. 2020 Jul 1;98(7):495-504. PMid:32742035 PMCid:PMC7375210