. 2022 Mar 15:717:109124.

doi: 10.1016/j.abb.2022.109124. Epub 2022 Jan 24.

The importance of accessory protein variants in the pathogenicity of SARS-CoV-2

Sk Sarif Hassan¹, Pabitra Pal Choudhury², Guy W Dayhoff 2nd³, Alaa A A Aljabali⁴, Bruce D Uhal⁵, Kenneth Lundstrom⁶, Nima Rezaei⁷, Damiano Pizzol⁸, Parise Adadi⁹, Amos Lal¹⁰, Antonio Soares¹¹, Tarek Mohamed Abd El-Aziz¹², Adam M Brufsky¹³, Gajendra Kumar Azad¹⁴, Samendra P Sherchan¹⁵, Wagner Baetas-da-Cruz¹⁶, Kazuo Takayama¹⁷, Ãngel Serrano-Aroca¹⁸, Gaurav Chauhan¹⁹, Giorgio Palu²⁰, Yogendra Kumar Mishra²¹, Debmalya Barh²², Raner Jośe Santana Silva²³, Bruno Silva Andrade²⁴, Vasco Azevedo²⁵, Aristóteles Góes-Neto²⁶, Nicolas G Bazan²⁷, Elrashdy M Redwan²⁸, Murtaza Tambuwala²⁹, Vladimir N Uversky³⁰

Affiliations

¹ Department of Mathematics, Pingla Thana Mahavidyalaya, Maligram, 721140, India. Electronic address: sarimif@gmail.com.
² Applied Statistics Unit, Indian Statistical Institute, Kolkata, 700108, West Bengal, India.
³ Department of Chemistry, College of Art and Sciences, University of South Florida, Tampa, FL, 33620, USA.
⁴ Department of Pharmaceutics and Pharmaceutical Technology, Yarmouk University-Faculty of Pharmacy, Irbid, 566, Jordan.
⁵ Department of Physiology, Michigan State University, East Lansing, MI, 48824, USA.
⁶ PanTherapeutics, Rte de Lavaux 49, CH1095, Lutry, Switzerland. Electronic address: lundstromkenneth@gmail.com.
⁷ Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran; Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Stockholm, Sweden.
⁸ Italian Agency for Development Cooperation - Khartoum, Sudan Street 33, Al Amarat, Sudan.
⁹ Department of Food Science, University of Otago, Dunedin, 9054, New Zealand.
¹⁰ Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA.
¹¹ Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229-3900, USA.
¹² Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229-3900, USA; Zoology Department, Faculty of Science, Minia University, El-Minia, 61519, Egypt.
¹³ University of Pittsburgh School of Medicine, Department of Medicine, Division of Hematology/Oncology, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.
¹⁴ Department of Zoology, Patna University, Patna, 800005, Bihar, India.
¹⁵ Department of Environmental Health Sciences, Tulane University, New Orleans, LA, 70112, USA.
¹⁶ Translational Laboratory in Molecular Physiology, Centre for Experimental Surgery, College of Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
¹⁷ Center for iPS Cell Research and Application, Kyoto University, Japan.
¹⁸ Biomaterial and Bioengineering Lab, Translational Research Centre San Alberto Magno, Catholic University of Valencia San Vicente M'artir, c/Guillem de Castro 94, 46001, Valencia, Spain.
¹⁹ School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, 64849, Monterrey, Nuevo León, Mexico.
²⁰ Department of Molecular Medicine, University of Padova, Via Gabelli 63, 35121, Padova, Italy.
²¹ University of Southern Denmark, Mads Clausen Institute, NanoSYD, Alsion 2, 6400, Sønderborg, Denmark.
²² Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, WB, India; Departamento de Genética, Ecologia e Evolucao, Instituto de Cîencias Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
²³ Departamento de Ciencias Biologicas (DCB), Programa de Pos-Graduacao em Genetica e Biologia Molecular (PPGGBM), Universidade Estadual de Santa Cruz (UESC), Rodovia Ilheus-Itabuna, km 16, 45662-900, Ilheus, BA, Brazil.
²⁴ Laboratório de Bioinformática e Química Computacional, Departamento de Ciências Biológicas, Universidade Estadual do Sudoeste da Bahia (UESB), Jequié, 45206-190, Brazil.
²⁵ Departamento de Genética, Ecologia e Evolucao, Instituto de Cîencias Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
²⁶ Laboratório de Biologia Molecular e Computacional de Fungos, Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.
²⁷ Neuroscience Center of Excellence, School of Medicine, LSU Health New Orleans, New Orleans, LA, 70112, USA.
²⁸ King Abdulaz University, Faculty of Science, Department of Biological Science, Saudi Arabia.
²⁹ School of Pharmacy and Pharmaceutical Science, Ulster University, Coleraine, BT52 1SA, Northern Ireland, UK.
³⁰ Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA; Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy pereulok, 9, Dolgoprudny, 141700, Moscow region, Russia. Electronic address: vuversky@usf.edu.

PMID: 35085577
PMCID: PMC8785432
DOI: 10.1016/j.abb.2022.109124

The importance of accessory protein variants in the pathogenicity of SARS-CoV-2

Sk Sarif Hassan et al. Arch Biochem Biophys. 2022.

. 2022 Mar 15:717:109124.

doi: 10.1016/j.abb.2022.109124. Epub 2022 Jan 24.

Authors

Affiliations

¹ Department of Mathematics, Pingla Thana Mahavidyalaya, Maligram, 721140, India. Electronic address: sarimif@gmail.com.
² Applied Statistics Unit, Indian Statistical Institute, Kolkata, 700108, West Bengal, India.
³ Department of Chemistry, College of Art and Sciences, University of South Florida, Tampa, FL, 33620, USA.
⁴ Department of Pharmaceutics and Pharmaceutical Technology, Yarmouk University-Faculty of Pharmacy, Irbid, 566, Jordan.
⁵ Department of Physiology, Michigan State University, East Lansing, MI, 48824, USA.
⁶ PanTherapeutics, Rte de Lavaux 49, CH1095, Lutry, Switzerland. Electronic address: lundstromkenneth@gmail.com.
⁷ Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran; Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Stockholm, Sweden.
⁸ Italian Agency for Development Cooperation - Khartoum, Sudan Street 33, Al Amarat, Sudan.
⁹ Department of Food Science, University of Otago, Dunedin, 9054, New Zealand.
¹⁰ Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA.
¹¹ Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229-3900, USA.
¹² Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229-3900, USA; Zoology Department, Faculty of Science, Minia University, El-Minia, 61519, Egypt.
¹³ University of Pittsburgh School of Medicine, Department of Medicine, Division of Hematology/Oncology, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.
¹⁴ Department of Zoology, Patna University, Patna, 800005, Bihar, India.
¹⁵ Department of Environmental Health Sciences, Tulane University, New Orleans, LA, 70112, USA.
¹⁶ Translational Laboratory in Molecular Physiology, Centre for Experimental Surgery, College of Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
¹⁷ Center for iPS Cell Research and Application, Kyoto University, Japan.
¹⁸ Biomaterial and Bioengineering Lab, Translational Research Centre San Alberto Magno, Catholic University of Valencia San Vicente M'artir, c/Guillem de Castro 94, 46001, Valencia, Spain.
¹⁹ School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, 64849, Monterrey, Nuevo León, Mexico.
²⁰ Department of Molecular Medicine, University of Padova, Via Gabelli 63, 35121, Padova, Italy.
²¹ University of Southern Denmark, Mads Clausen Institute, NanoSYD, Alsion 2, 6400, Sønderborg, Denmark.
²² Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, WB, India; Departamento de Genética, Ecologia e Evolucao, Instituto de Cîencias Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
²³ Departamento de Ciencias Biologicas (DCB), Programa de Pos-Graduacao em Genetica e Biologia Molecular (PPGGBM), Universidade Estadual de Santa Cruz (UESC), Rodovia Ilheus-Itabuna, km 16, 45662-900, Ilheus, BA, Brazil.
²⁴ Laboratório de Bioinformática e Química Computacional, Departamento de Ciências Biológicas, Universidade Estadual do Sudoeste da Bahia (UESB), Jequié, 45206-190, Brazil.
²⁵ Departamento de Genética, Ecologia e Evolucao, Instituto de Cîencias Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
²⁶ Laboratório de Biologia Molecular e Computacional de Fungos, Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.
²⁷ Neuroscience Center of Excellence, School of Medicine, LSU Health New Orleans, New Orleans, LA, 70112, USA.
²⁸ King Abdulaz University, Faculty of Science, Department of Biological Science, Saudi Arabia.
²⁹ School of Pharmacy and Pharmaceutical Science, Ulster University, Coleraine, BT52 1SA, Northern Ireland, UK.
³⁰ Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA; Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy pereulok, 9, Dolgoprudny, 141700, Moscow region, Russia. Electronic address: vuversky@usf.edu.

PMID: 35085577
PMCID: PMC8785432
DOI: 10.1016/j.abb.2022.109124

Abstract

The coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS- CoV-2) with an estimated fatality rate of less than 1%. The SARS-CoV-2 accessory proteins ORF3a, ORF6, ORF7a, ORF7b, ORF8, and ORF10 possess putative functions to manipulate host immune mechanisms. These involve interferons, which appear as a consensus function, immune signaling receptor NLRP3 (NLR family pyrin domain-containing 3) inflammasome, and inflammatory cytokines such as interleukin 1β (IL-1β) and are critical in COVID-19 pathology. Outspread variations of each of the six accessory proteins were observed across six continents of all complete SARS-CoV-2 proteomes based on the data reported before November 2020. A decreasing order of percentage of unique variations in the accessory proteins was determined as ORF3a > ORF8 > ORF7a > ORF6 > ORF10 > ORF7b across all continents. The highest and lowest unique variations of ORF3a were observed in South America and Oceania, respectively. These findings suggest that the wide variations in accessory proteins seem to affect the pathogenicity of SARS-CoV-2.

Keywords: ORF10; ORF3a; ORF6; ORF7a; ORF7b; ORF8; Pathogenicity; SARS-CoV-2.

PubMed Disclaimer

Conflict of interest statement

The authors do not have any conflicts of interest to declare.

Figures

**Fig. 1**
ClustalW alignment of SARS-CoV-2 and RaTG13 ORF3 proteins shows 98.5% sequence identity.

**Fig. 2**
ClustalW alignment of SARS-CoV-2 (NCBI GenBank ID BCA87365.1) and RaTG13 (NCBI GenBank ID MN996532.2, translated 5′3′ frame 1) ORF6 proteins show 100% sequence identity, despite up to 89 years of genetic diversion.

**Fig. 3**
ClustalW alignment of SARS-CoV-2 (NCBI GenBank ID BCA87366.1) and RaTG13 (NCBI GenBank ID MN996532.2, translated 5′3′ frame 2) The ORF7a proteins show 97.5% sequence identity, despite up to 89 years of genetic diversion.

**Fig. 4**
ClustalW alignment of SARS-CoV-2 (NCBI GenBank ID BCB15096.1) and Ratg13 (NCBI GenBank ID MN996532.2, translated 5′3′ frame 2) ORF7b proteins shows 97.6% sequence identity, despite up to 89 years of genetic diversion.

**Fig. 5**
ClustalW alignment of SARS-CoV-2 (NCBI GenBank ID BCA87366.1) and RaTG13 (NCBI GenBank ID MN996532.2, translated 5′3′ frame 2) ORF8 proteins show a 95% sequence identity, despite up to 89 years of genetic diversion.

**Fig. 6**
ClustalW alignment of SARS-CoV-2 (NCBI GenBank ID BCA87369.1) and RaTG13 (NCBI GenBank ID MN996532.2, translated 5′3′ frame 2) ORF10 proteins show a 97.3% sequence identity, despite up to 89 years of genetic diversion.

**Fig. 7**
Number of unique accessory proteins across six continents.

**Fig. 8**
Bar representations of percentages of continental variations (A), and the percentage of unique accessory proteins (B).

**Fig. 9**
Quantitative information of the accessory proteins.

**Fig. 10**
Identical pairs of accessory protein sequences across all continents.

**Fig. 11**
SARS-CoV-2 ORF3a amino acid phylogeny after group clustering.

**Fig. 12**
SARS-CoV-2 ORF6 amino acid phylogeny after group clustering. Phylogenetic analysis identified four well-defined groups.

**Fig. 13**
SARS-CoV-2 ORF7a amino acid phylogeny after group clustering. Two well-defined groups can be identified.

**Fig. 14**
SARS-CoV-2 ORF7b amino acid phylogeny after group clustering. Analysis identified three well-defined groups.

**Fig. 15**
Phylogenetic analysis of SARS-CoV-2 ORF8 protein identified three well-defined groups.

**Fig. 16**
SARS-CoV-2 ORF10 amino acid phylogenetic analysis identified four well-defined groups.

**Fig. 17**
Effect of mutations observed in unique natural variants of the SARS-CoV-2 accessory proteins on their overall intrinsic disorder predisposition evaluated in terms of percent of predicted intrinsically disordered residues (PPIDR) and mean disorder score (MDS). These data were generated using the PONDR® FIT [42] algorithm, which is a meta predictor that combines outputs of six predictors of intrinsic disorder, PONDR® VLXT [43], PONDR® VSL2 [44,45], PONDR® VL3 [46], FoldIndex [47], IUPred [48], and TopIDP [49]. PONDR® FIT is moderately more accurate than each of its component predictors [42]. For each mutant, the predicted percentage of intrinsically disordered residues (PPIDR) and mean disorder score (MDS) were calculated based on the outputs of this per-residue disorder predictors. Here, PPIDR in a query protein represents a percentage of residues with disorder scores exceeding 0.5. In this study, protein residues and regions were classified as disordered or flexible if their predicted disorder scores were above 0.5, or ranged between 0.15 and 0.5, respectively.

**Fig. 18**
Per-residue intrinsic disorder profiles generated for the SARS-CoV-2 accessory proteins and their natural variants by PONDR® VSL2, which systematically shows good performance in various comparative analyses, including recently conducted Critical assessment of protein intrinsic disorder prediction (CAID) experiment, where this tool was recognized as #3 predictor of 43 evaluated methods [31].

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The importance of accessory protein variants in the pathogenicity of SARS-CoV-2

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The importance of accessory protein variants in the pathogenicity of SARS-CoV-2

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