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基于多个 T 细胞和 B 细胞表位的 SARS-CoV-2 疫苗候选物的计算机设计。

In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes.

机构信息

Department of Biochemistry, McPherson University, Seriki Sotayo, Ogun State, Nigeria.

Biotechnology Unit, Department of Biological Sciences, Kings University, Odeomu, Nigeria.

出版信息

Arch Razi Inst. 2021 Nov 30;76(5):1191-1202. doi: 10.22092/ari.2020.351605.1526. eCollection 2021 Nov.

DOI:10.22092/ari.2020.351605.1526
PMID:35355741
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8934067/
Abstract

Coronaviruses (2019-nCoV) are large single-stranded RNA viruses that usually cause respiratory infections with a crude lethality ratio of 3.8% and high levels of transmissibility. There is yet no applicable clinical evaluation to assess the efficacy of various therapeutic agents that have been suggested as investigational drugs against the viruses despite their respective supposed hypothetical claims due to their antiviral potentials. Moreover, the development of a safe and effective vaccine has been suggested as an intervention to control the 2019-nCoV pandemic. However, a major concern in the development of a 2019-nCoV vaccine is the possibility of stimulating a corresponding immune response without enhancing the induction of the disease and associated side effects. The present investigation was carried out by predicting the antigenicity of the primary sequences of 2019-nCoV structural proteins and identification of B-cell and T-cell epitopes through the Bepipred and PEPVAC servers, respectively. The peptides of the vaccine construct include the selected epitopes based on the VaxiJen score with a threshold of 1.0 and β-defensinas an adjuvant. The putative binding of the vaccine constructs to intracellular toll-like receptors (TLRs) was assessed through molecular docking analysis and molecular dynamics simulations. The selected epitopes for the final vaccine construct are DPNFKD, SPLSLN, and LELQDHNE as B-cell epitopes and EPKLGSLVV, NFKDQVILL, and SSRSSSRSR as T-cell epitopes. The molecular docking analysis showed the vaccine construct could have favorable interactions with TLRs as indicated by the negative values of the computed binding energies. The constructed immunogen based on the immune informatics study could be employed in the strategy to develop potential vaccine candidates against 2019-nCoV.

摘要

冠状病毒(2019-nCoV)是大型单链 RNA 病毒,通常会引起呼吸道感染,粗死亡率为 3.8%,传染性很强。尽管具有抗病毒潜力,但由于其各自的假设性主张,目前尚无可用的临床评估来评估各种治疗药物的疗效,这些药物被认为是针对病毒的研究药物。此外,已提出开发安全有效的疫苗作为控制 2019-nCoV 大流行的干预措施。然而,2019-nCoV 疫苗开发的一个主要关注点是在不增强疾病诱导和相关副作用的情况下刺激相应免疫反应的可能性。本研究通过预测 2019-nCoV 结构蛋白的主要序列的抗原性,并分别通过 Bepipred 和 PEPVAC 服务器识别 B 细胞和 T 细胞表位来进行。疫苗构建体的肽包括基于 VaxiJen 评分选择的表位,阈值为 1.0,β-防御素作为佐剂。通过分子对接分析和分子动力学模拟评估疫苗构建体与细胞内 Toll 样受体(TLR)的假定结合。最终疫苗构建体的选定表位为 B 细胞表位的 DPNFKD、SPLSLN 和 LELQDHNE,以及 T 细胞表位的 EPKLGSLVV、NFKDQVILL 和 SSRSSSRSR。分子对接分析表明,疫苗构建体可能与 TLR 具有有利的相互作用,这由计算结合能的负值表示。基于免疫信息学研究构建的免疫原可用于开发针对 2019-nCoV 的潜在疫苗候选物的策略。

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