Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India.
Monoclon Antib Immunodiagn Immunother. 2020 Dec;39(6):204-216. doi: 10.1089/mab.2020.0035. Epub 2020 Oct 30.
A web-based resource CoronaVIR (https://webs.iiitd.edu.in/raghava/coronavir/) has been developed to maintain the predicted and existing information on coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have integrated multiple modules, including "Genomics," "Diagnosis," "Immunotherapy," and "Drug Designing" to understand the holistic view of this pandemic medical disaster. The genomics module provides genomic information of different strains of this virus to understand genomic level alterations. The diagnosis module includes detailed information on currently-in-use diagnostics tests as well as five novel universal primer sets predicted using tools. The Immunotherapy module provides information on epitope-based potential vaccine candidates (e.g., LQLPQGTTLPKGFYA, VILLNKHIDAYKTFPPTEPKKDKKKK, EITVATSRTLS, GKGQQQQGQTV, SELVIGAVILR) predicted using state-of-the-art software and resources in the field of immune informatics. These epitopes have the potential to activate both adaptive (e.g., B cell and T cell) and innate (e.g., vaccine adjuvants) immune systems as well as suitable for all strains of SARS-CoV-2. Besides, we have also predicted potential candidates for siRNA-based therapy and RNA-based vaccine adjuvants. The drug designing module maintains information about potential drug targets, tertiary structures, and potential drug molecules. These potential drug molecules were identified from FDA-approved drugs using the docking-based approach. We also compiled information from the literature and Internet on potential drugs, repurposing drugs, and monoclonal antibodies. To understand host-virus interaction, we identified cell-penetrating peptides in the virus. In this study, state-of-the-art techniques have been used for predicting the potential candidates for diagnostics and therapeutics.
已开发了一个基于网络的资源 CoronaVIR（https://webs.iiitd.edu.in/raghava/coronavir/），用于维护有关冠状病毒严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）的预测信息和现有信息。我们已经整合了多个模块，包括“基因组学”、“诊断”、“免疫疗法”和“药物设计”，以了解这场大流行医学灾难的整体情况。基因组学模块提供了该病毒不同毒株的基因组信息，以了解基因组水平的变化。诊断模块包括有关当前使用的诊断测试的详细信息，以及使用工具预测的五个新的通用引物组。免疫疗法模块提供了基于表位的潜在疫苗候选物（例如，LQLPQGTTLPKGFYA、VILLNKHIDAYKTFPPTEPKKDKKKK、EITVATSRTLS、GKGQQQQGQTV、SELVIGAVILR）的信息，这些候选物是使用免疫信息学领域的最新软件和资源预测的。这些表位有可能激活适应性（例如，B 细胞和 T 细胞）和固有（例如，疫苗佐剂）免疫系统，并且适合 SARS-CoV-2 的所有毒株。此外，我们还预测了基于 siRNA 的治疗和基于 RNA 的疫苗佐剂的潜在候选物。药物设计模块维护有关潜在药物靶标、三级结构和潜在药物分子的信息。这些潜在的药物分子是使用基于对接的方法从 FDA 批准的药物中鉴定出来的。我们还从文献和互联网上收集了有关潜在药物、重新利用药物和单克隆抗体的信息。为了了解宿主-病毒相互作用，我们在病毒中鉴定了穿膜肽。在这项研究中，使用了最先进的技术来预测诊断和治疗的潜在候选物。
