Ray Manisha, Sable Mukund Namdev, Sarkar Saurav, Hallur Vinaykumar
Department of Pathology & Lab Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha 751019, India.
Department of ENT, All India Institute of Medical Sciences, Bhubaneswar, Odisha 751019, India.
Meta Gene. 2021 Feb;27:100844. doi: 10.1016/j.mgene.2020.100844. Epub 2020 Dec 17.
The currently emerging pathogen SARS-CoV-2 has produced the global pandemic crisis by causing COVID-19. The unique and novel genetic makeup of SARS-CoV-2 has created hurdles in biological research, due to which the potential drug/vaccine candidates have not yet been discovered by the scientific community. Meanwhile, the advantages of bioinformatics in viral research had created a milestone since last few decades. The exploitation of bioinformatics tools and techniques has successfully interpreted this viral genomics architecture. Some major in silico studies involving next-generation sequencing, genome-wide association studies, computer-aided drug design etc. have been effectively applied in COVID-19 research methodologies and discovered novel information on SARS-CoV-2 in several ways. Nowadays the implementation of in silico studies in COVID-19 research has not only sequenced the SARS-CoV-2 genome but also properly analyzed the sequencing errors, evolutionary relationship, genetic variations, putative drug candidates against SARS-CoV-2 viral genes etc. within a very short time period. These would be very needful towards further research on COVID-19 pandemic and essential for vaccine development against SARS-CoV-2 which will save public health.
目前新出现的病原体严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引发了新冠肺炎疫情，导致全球大流行危机。SARS-CoV-2独特新颖的基因构成给生物学研究带来了障碍，因此科学界尚未发现潜在的药物/疫苗候选物。与此同时，几十年来，生物信息学在病毒研究中的优势创造了一个里程碑。利用生物信息学工具和技术成功解析了这种病毒的基因组结构。一些主要的计算机模拟研究，包括下一代测序、全基因组关联研究、计算机辅助药物设计等，已有效地应用于新冠肺炎研究方法中，并以多种方式发现了有关SARS-CoV-2的新信息。如今，计算机模拟研究在新冠肺炎研究中的应用不仅对SARS-CoV-2基因组进行了测序，还在很短的时间内对测序错误、进化关系、基因变异、针对SARS-CoV-2病毒基因的潜在药物候选物等进行了恰当分析。这些对于新冠肺炎大流行的进一步研究非常必要，对于研发针对SARS-CoV-2的疫苗至关重要，而这将拯救公众健康。
