Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Quantitative and Computational Biosciences Graduate Program, Baylor College of Medicine, Houston, TX 77030, USA.
Bioinformatics. 2021 Nov 18;37(22):4033-4040. doi: 10.1093/bioinformatics/btab406.
Since the first recognized case of COVID-19, more than 100 million people have been infected worldwide. Global efforts in drug and vaccine development to fight the disease have yielded vaccines and drug candidates to cure COVID-19. However, the spread of SARS-CoV-2 variants threatens the continued efficacy of these treatments. In order to address this, we interrogate the evolutionary history of the entire SARS-CoV-2 proteome to identify evolutionarily conserved functional sites that can inform the search for treatments with broader coverage across the coronavirus family.
Combining coronavirus family sequence information with the mutations observed in the current COVID-19 outbreak, we systematically and comprehensively define evolutionarily stable sites that may provide useful drug and vaccine targets and which are less likely to be compromised by the emergence of new virus strains. Several experimentally validated effective drugs interact with these proposed target sites. In addition, the same evolutionary information can prioritize cross reactive antigens that are useful in directing multi-epitope vaccine strategies to illicit broadly neutralizing immune responses to the betacoronavirus family. Although the results are focused on SARS-CoV-2, these approaches stem from evolutionary principles that are agnostic to the organism or infective agent.
The results of this work are made interactively available at http://cov.lichtargelab.org.
Supplementary data are available at Bioinformatics online.
自首例 COVID-19 病例被确认以来,全球已有超过 1 亿人感染。全球在药物和疫苗开发方面为抗击该疾病做出了努力,已研发出治疗 COVID-19 的疫苗和候选药物。然而,SARS-CoV-2 变体的传播威胁到这些治疗方法的持续疗效。为了解决这个问题,我们探究了整个 SARS-CoV-2 蛋白质组的进化历史,以确定进化上保守的功能位点,从而为寻找更广泛覆盖冠状病毒家族的治疗方法提供信息。
我们结合冠状病毒家族的序列信息以及当前 COVID-19 爆发中观察到的突变,系统而全面地定义了进化稳定的位点,这些位点可能提供有用的药物和疫苗靶点,并且不太可能因新病毒株的出现而受到影响。几种经过实验验证的有效药物与这些提议的靶位相互作用。此外,相同的进化信息可以优先考虑交叉反应性抗原,这些抗原在指导多表位疫苗策略方面非常有用,可以诱导针对β冠状病毒家族的广泛中和免疫反应。尽管结果主要集中在 SARS-CoV-2 上,但这些方法源于与生物体或感染因子无关的进化原则。
这项工作的结果可在 http://cov.lichtargelab.org 上进行交互式访问。
补充数据可在生物信息学在线获得。