A. Ansori, V. D. Kharisma, Y. Antonius, Martia Rani Tacharina, F. Rantam
{"title":"印度尼西亚严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)免疫生物信息学分析及系统发育树构建:刺突糖蛋白基因","authors":"A. Ansori, V. D. Kharisma, Y. Antonius, Martia Rani Tacharina, F. Rantam","doi":"10.29238/teknolabjournal.v9i1.221","DOIUrl":null,"url":null,"abstract":"The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has spread worldwide and as a result, the World Health Organization (WHO) declared it a pandemic. At present, there are no approved vaccines against SARS-CoV-2. Therefore, the aim of this study was to predict epitope-based vaccines using bioinformatics approaches and phylogenetic tree construction of SARS-CoV-2 against the backdrop of the COVID-19 pandemic. In this study, we employed 27 isolates of SARS-CoV-2 spike glycoprotein genes retrieved from GenBank® (National Center for Biotechnology Information, USA) and the GISAID EpiCoV™ Database (Germany). We analyzed the candidate epitopes using the Immune Epitope Database and Analysis Resource. Furthermore, we performed a protective antigen prediction with VaxiJen 2.0. Data for B-cell epitope prediction, protective antigen prediction, and the underlying phylogenetic tree of SARS-CoV-2 were obtained in this research. Therefore, these data could be used to design an epitope-based vaccine against SARS-CoV-2. However, the advanced study is recommended for confirmation (in vitro and in vivo).","PeriodicalId":31934,"journal":{"name":"Jurnal Teknologi Laboratorium","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Immunobioinformatics analysis and phylogenetic tree construction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indonesia: spike glycoprotein gene\",\"authors\":\"A. Ansori, V. D. Kharisma, Y. Antonius, Martia Rani Tacharina, F. Rantam\",\"doi\":\"10.29238/teknolabjournal.v9i1.221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has spread worldwide and as a result, the World Health Organization (WHO) declared it a pandemic. At present, there are no approved vaccines against SARS-CoV-2. Therefore, the aim of this study was to predict epitope-based vaccines using bioinformatics approaches and phylogenetic tree construction of SARS-CoV-2 against the backdrop of the COVID-19 pandemic. In this study, we employed 27 isolates of SARS-CoV-2 spike glycoprotein genes retrieved from GenBank® (National Center for Biotechnology Information, USA) and the GISAID EpiCoV™ Database (Germany). We analyzed the candidate epitopes using the Immune Epitope Database and Analysis Resource. Furthermore, we performed a protective antigen prediction with VaxiJen 2.0. Data for B-cell epitope prediction, protective antigen prediction, and the underlying phylogenetic tree of SARS-CoV-2 were obtained in this research. Therefore, these data could be used to design an epitope-based vaccine against SARS-CoV-2. However, the advanced study is recommended for confirmation (in vitro and in vivo).\",\"PeriodicalId\":31934,\"journal\":{\"name\":\"Jurnal Teknologi Laboratorium\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Teknologi Laboratorium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29238/teknolabjournal.v9i1.221\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknologi Laboratorium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29238/teknolabjournal.v9i1.221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Immunobioinformatics analysis and phylogenetic tree construction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indonesia: spike glycoprotein gene
The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has spread worldwide and as a result, the World Health Organization (WHO) declared it a pandemic. At present, there are no approved vaccines against SARS-CoV-2. Therefore, the aim of this study was to predict epitope-based vaccines using bioinformatics approaches and phylogenetic tree construction of SARS-CoV-2 against the backdrop of the COVID-19 pandemic. In this study, we employed 27 isolates of SARS-CoV-2 spike glycoprotein genes retrieved from GenBank® (National Center for Biotechnology Information, USA) and the GISAID EpiCoV™ Database (Germany). We analyzed the candidate epitopes using the Immune Epitope Database and Analysis Resource. Furthermore, we performed a protective antigen prediction with VaxiJen 2.0. Data for B-cell epitope prediction, protective antigen prediction, and the underlying phylogenetic tree of SARS-CoV-2 were obtained in this research. Therefore, these data could be used to design an epitope-based vaccine against SARS-CoV-2. However, the advanced study is recommended for confirmation (in vitro and in vivo).