Sharma Ruchika, Patil C R, Kumar Anoop, Sharma Kalicharan
Department of Pharmaceutical Biotechnology, Delhi Pharmaceutical Science, and Research University, New Delhi, 110017 India.
Centre for Precision Medicine and Pharmacy, Delhi Pharmaceutical Science, and Research University, New Delhi, 110017 India.
In Silico Pharmacol. 2022 Jul 26;10(1):12. doi: 10.1007/s40203-022-00128-y. eCollection 2022.
Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization, cloning and immune simulation profile was found to be satisfactory. Overall, the designed vaccine candidate has a potential against variant of SARS-Cov-2. However, further experimental studies are required to confirm.
尽管有新冠病毒疫苗可用，但仍需要更有效的疫苗来应对严重急性呼吸综合征冠状病毒2（SARS-CoV-2）出现的变异毒株。在本研究中，我们利用免疫信息学方法确定了一种针对奥密克戎（B.1.1.529）的有前景的候选疫苗。使用了各种可用工具，如免疫表位数据库服务器资源和NetCTL-1.2，来确定有前景的T细胞和B细胞表位。进行分子对接以检查TLR-3受体的相互作用并验证候选疫苗的3D模型。随后使用SnapGene进行密码子优化和克隆。最后，还检查了计算机免疫模拟概况。已根据其抗原性（VaxiJen v2.0）和致敏性（AllerTOP v2.0）选择了鉴定出的T细胞和B细胞表位。将具有抗原性和非致敏性的鉴定表位与特定肽接头融合。此外，通过PHYRE2服务器构建3D模型并使用ProSA-web进行验证。经过验证的3D模型进一步与Toll样受体3（TLR3）对接，并与氨基酸显示出良好的相互作用，这表明是一种有前景的针对SARS-CoV-2奥密克戎变异株的候选疫苗。最后，发现密码子优化、克隆和免疫模拟概况令人满意。总体而言，设计的候选疫苗对SARS-CoV-2变异株具有潜力。然而，需要进一步的实验研究来证实。
