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SARS-CoV-2 结构蛋白中潜在表位的免疫信息学作图。

Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins.

机构信息

Department of Molecular Biology and Biotechnology, Tezpur University, Napaam, Assam, India.

National Institute of Immunology, Aruna Asaf Ali Marg, Jawaharlal Nehru University, New Delhi, India.

出版信息

PLoS One. 2021 Nov 15;16(11):e0258645. doi: 10.1371/journal.pone.0258645. eCollection 2021.

Abstract

All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.

摘要

所有已批准使用的新型冠状病毒病 (COVID-19) 疫苗均安全、有效,并降低重症风险。尽管关于 COVID-19 患者免疫表现的数据有限,但越来越多的实验证据支持 B 细胞和 T 细胞对严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 感染的缓解具有重要作用。尽管有几种 COVID-19 疫苗具有高功效,但仍需要更有效的疫苗来预防 SARS-CoV-2 的新变体。我们采用了全面的免疫信息学预测算法,并利用与 SARS-CoV 的遗传关系,预测了 SARS-CoV-2 结构蛋白中的潜在免疫表位。SARS-CoV-2 和 SARS-CoV 的 S 和 N 蛋白是抗体检测的主要靶标,这促使我们设计了基于 SARS-CoV-2 结构蛋白 B 细胞和 T 细胞表位的四种多表位疫苗。疫苗构建体中选择的主要表位预计具有抗原性、非变应原性和细胞因子诱导特性。此外,一些预测的表位已在已发表的论文中得到实验验证。此外,我们使用 C-ImmSim 服务器来预测基于表位的疫苗诱导的有效免疫反应。总之,本研究中预测的免疫表位为未来的实验验证提供了一个平台,这可能有助于开发有效的疫苗候选物和基于表位的血清学诊断检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/314d/8592446/ccee406795a2/pone.0258645.g001.jpg

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