Computers in Biology and Medicine ( IF 7.7 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.compbiomed.2020.104158 Rajiv Kangabam 1 , Susrita Sahoo 2 , Arpan Ghosh 3 , Riya Roy 1 , Yumnam Silla 4 , Namrata Misra 3 , Mrutyunjay Suar 3
The COVID-19 pandemic has affected 215 countries and territories around the world with 60,187,347 coronavirus cases and 17,125,719 currently infected patients confirmed as of the 25th of November 2020. Currently, many countries are working on developing new vaccines and therapeutic drugs for this novel virus strain, and a few of them are in different phases of clinical trials. The advancement in high-throughput sequence technologies, along with the application of bioinformatics, offers invaluable knowledge on genomic characterization and molecular pathogenesis of coronaviruses. Recent multi-disciplinary studies using bioinformatics methods like sequence-similarity, phylogenomic, and computational structural biology have provided an in-depth understanding of the molecular and biochemical basis of infection, atomic-level recognition of the viral-host receptor interaction, functional annotation of important viral proteins, and evolutionary divergence across different strains. Additionally, various modern immunoinformatic approaches are also being used to target the most promiscuous antigenic epitopes from the SARS-CoV-2 proteome for accelerating the vaccine development process. In this review, we summarize various important computational tools and databases available for systematic sequence-structural study on coronaviruses. The features of these public resources have been comprehensively discussed, which may help experimental biologists with predictive insights useful for ongoing research efforts to find therapeutics against the infectious COVID-19 disease.
中文翻译:
用于冠状病毒研究的下一代计算工具和资源:从检测到疫苗发现
截至2020年11月25日,COVID-19大流行已影响全球215个国家和地区,共有60,187,347例冠状病毒病例和17,125,719名当前感染患者确诊。目前,许多国家正在致力于针对这种新型病毒株开发新疫苗和治疗药物,其中一些正处于临床试验的不同阶段。高通量测序技术的进步以及生物信息学的应用,为冠状病毒的基因组特征和分子发病机制提供了宝贵的知识。最近使用序列相似性、系统基因组学和计算结构生物学等生物信息学方法的多学科研究提供了对感染的分子和生化基础、病毒-宿主受体相互作用的原子水平识别、病毒-宿主受体相互作用的功能注释的深入了解。重要的病毒蛋白以及不同病毒株之间的进化差异。此外,各种现代免疫信息学方法也被用于针对 SARS-CoV-2 蛋白质组中最混杂的抗原表位,以加速疫苗开发过程。在这篇综述中,我们总结了可用于冠状病毒系统序列结构研究的各种重要计算工具和数据库。这些公共资源的特征已得到全面讨论,这可能有助于实验生物学家获得预测性见解,从而有助于正在进行的研究工作,以找到针对传染性 COVID-19 疾病的治疗方法。