Sequence Analysis and Structure Prediction of SARS-CoV-2 Accessory Proteins 9b and ORF14: Evolutionary Analysis Indicates Close Relatedness to Bat Coronavirus

Baruah, Chittaranjan; Devi, Papari; Sharma, Dhirendra Kumar

doi:10.26434/chemrxiv.12424958

Cited by 2 publications

(1 citation statement)

References 42 publications

(61 reference statements)

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“…Millions of proteins are still uncharacterized and therefore, unveiling the biological functions and characteristics of these uncharacterized proteins of different organisms is now a common practice in the fields of bioinformatics [26][27][28]. SARS-CoV has a number of functional proteins [29,30], of which many are still unknown or poorly understood [31,32]. Advances in computer biology have created a variety of platforms and methods for predicting protein structure, binding sites, and biological activity [33,34].…”

Section: Introductionmentioning

confidence: 99%

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Rahman¹,

Hasan²,

Biswas³

et al. 2023

Genomics Inform

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Characterization as well as prediction of the secondary and tertiary structure of hypothetical proteins from their amino acid sequences uploaded in databases by in silico approach are the critical issues in computational biology. Severe acute respiratory syndrome–associated coronavirus (SARS-CoV), which is responsible for pneumonia alike diseases, possesses a wide range of proteins of which many are still uncharacterized. The current study was conducted to reveal the physicochemical characteristics and structures of an uncharacterized protein Q6S8D9_SARS of SARS-CoV. Following the common flowchart of characterizing a hypothetical protein, several sophisticated computerized tools e.g., ExPASy Protparam, CD Search, SOPMA, PSIPRED, HHpred, etc. were employed to discover the functions and structures of Q6S8D9_SARS. After delineating the secondary and tertiary structures of the protein, some quality evaluating tools e.g., PROCHECK, ProSA-web etc. were performed to assess the structures and later the active site was identified also by CASTp v.3.0. The protein contains more negatively charged residues than positively charged residues and a high aliphatic index value which make the protein more stable. The 2D and 3D structures modeled by several bioinformatics tools ensured that the proteins had domain in it which indicated it was functional protein having the ability to trouble host antiviral inflammatory cytokine and interferon production pathways. Moreover, active site was found in the protein where ligand could bind. The study was aimed to unveil the features and structures of an uncharacterized protein of SARS-CoV which can be a therapeutic target for development of vaccines against the virus. Further research are needed to accomplish the task.

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Section: Introductionmentioning

confidence: 99%

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Rahman¹,

Hasan²,

Biswas³

et al. 2023

Genomics Inform

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Association of SARS-CoV-2 Nucleocapsid Protein Mutations with Patient Demographic and Clinical Characteristics during the Delta and Omicron Waves

Alsuwairi

Al-Saleh

Alsanea

et al. 2023

Preprint

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SARS-CoV-2 genomic mutations outside the spike protein that may increase transmissibility and disease severity have not been well characterized. This study identified mutations in the nucleocapsid protein and their possible association with patient characteristics. We analyzed 695 samples from patients with confirmed COVID-19 in Saudi Arabia between April 1, 2021, and April 30, 2022. Nucleocapsid protein mutations were identified through whole genome sequencing.Χ2 tests and T tests assessed associations between mutations and patient characteristics. Logistic regression estimated risk of intensive care unit (ICU) admission or death. Of 60 mutations identified, R203K was most common followed by G204R, P13L, and E31del, R32del, and S33del. These mutations were associated with reduced risk of ICU admission. P13L, E31del, R32del, and S33del were also associated with reduced risk of death. By contrast, D63G, R203M, and D377Y were associated with increased risk of ICU admission. Most mutations were detected in the SR-rich region, which was associated with low risk of death. C-tail and central linker regions were associated with increased risk of ICU admission, whereas the N-arm region was associated with reduced ICU admission risk. Some SARS-CoV-2 nucleocapsid amino acid mutations may enhance viral infection and COVID-19 disease severity.

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Sequence Analysis and Structure Prediction of SARS-CoV-2 Accessory Proteins 9b and ORF14: Evolutionary Analysis Indicates Close Relatedness to Bat Coronavirus

Cited by 2 publications

References 42 publications

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Association of SARS-CoV-2 Nucleocapsid Protein Mutations with Patient Demographic and Clinical Characteristics during the Delta and Omicron Waves

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