Khan Md Tahsin, Islam Md Jahirul, Parihar Arpana, Islam Rahatul, Jerin Tarhima Jahan, Dhote Rupali, Ali Md Ackas, Laura Fariha Khan, Halim Mohammad A
Division of Infectious Diseases, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215, Bangladesh.
Department of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh.
Inform Med Unlocked. 2021;24:100578. doi: 10.1016/j.imu.2021.100578. Epub 2021 Apr 21.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their cloning in expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)是一种具有高度传染性和致病性的人类冠状病毒,它引发了名为COVID-19的急性呼吸综合征大流行,对全球卫生安全构成了重大威胁。本研究的目的是通过计算机设计一种针对SARS-CoV-2的有效的基于肽的多表位疫苗(MEV)。对候选疫苗的整体模型质量、免疫原性、致敏性和理化分析进行了研究和验证。分子动力学研究证实了候选疫苗的稳定性。模拟过程中的对接复合物显示MEV与人及小鼠的Toll样受体(TLR)、TLR3和TLR4之间存在强烈且稳定的结合相互作用。最后,对候选疫苗密码子进行了优化,以便在表达系统中进行克隆,以确认表达增加。所提出的MEV可能是对抗SARS-CoV-2的潜在候选疫苗,但需要进行实验验证以确保其安全性和免疫原性状况。