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Volume 35 Issue 3
June 2020

    Wei Chen, Pengmian Feng, Kewei Liu, Meng Wu and Hao Lin. Computational Identification of Small Interfering RNA Targets in SARS-CoV-2[J]. Virologica Sinica, 2020, 35(3): 359-361. doi: 10.1007/s12250-020-00221-6
    Citation: Wei Chen, Pengmian Feng, Kewei Liu, Meng Wu, Hao Lin. Computational Identification of Small Interfering RNA Targets in SARS-CoV-2 .VIROLOGICA SINICA, 2020, 35(3) : 359-361.  http://dx.doi.org/10.1007/s12250-020-00221-6
    shu

    新型冠状病毒基因组中小干扰RNA靶位点预测

    • 1.

      成都中医药大学中医药创新研究院, 成都 611137

    • 2.

      华北理工大学生命科学学院, 唐山 063000

    • 3.

      电子科技大学生命科学与技术学院, 成都 610054

    • 通讯作者： 陈伟, greatchen@ncst.edu.cn, ORCID: http://orcid.org/0000-0002-6857-7696
      ; 林昊, hlin@uestc.edu.cn, ORCID: http://orcid.org/0000-0001-6265-2862
    • 收稿日期： 2020-03-06
      录用日期： 2020-04-03
      出版日期： 2020-04-15
    • 严重急性呼吸综合征冠状病毒2(SARS-CoV-2)已在世界范围爆发与流行, 但目前仍缺乏有效的疫苗及治疗药物。因此迫切需要寻找一种预防或治疗SARS-CoV-2的疫苗和药物。本研究采用生物信息学方法, 通过分析SARS-CoV-2基因组(MN908947)的二级结构, 获得了病毒基因组中长度在21~25nt可作为小干扰RNA的潜在靶点。进一步分析表明这些靶点在不同冠状病毒毒株中具有很强的保守性。希望本研究结果能够有助于治疗SARS-CoV-2的药物开发。

    Computational Identification of Small Interfering RNA Targets in SARS-CoV-2

    • 1.

      Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China

    • 2.

      Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan 063210, China

    • 3.

      Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China

    • Corresponding author: Wei Chen, greatchen@ncst.edu.cn Hao Lin, hlin@uestc.edu.cn
    • ORCID: http://orcid.org/0000-0002-6857-7696; http://orcid.org/0000-0001-6265-2862
    • Received Date: 06 March 2020
      Accepted Date: 03 April 2020
      Published Date: 15 April 2020
    • With the epidemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) worldwide and in the absence of any effective vaccine, there is an urgent need to find a specific anti- SARS-CoV-2 agent. In this study, by analyzing the secondary structures of the SARS-CoV-2 genome (MN908947), several 21~25 base-long segments were obtained and selected as the potential targets of small interfering RNA duplexes. Moreover, it was also found that these targets are conserved among different strains. We hope the results will contribute to the pharmaceutical research and therapy of the SARS-CoV-2.
    • 加载中

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      Computational Identification of Small Interfering RNA Targets in SARS-CoV-2

        Corresponding author: Wei Chen, greatchen@ncst.edu.cn
        Corresponding author: Hao Lin, hlin@uestc.edu.cn
      • 1. Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
      • 2. Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan 063210, China
      • 3. Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
      • Received Date: 06 March 2020
      • Accepted Date: 03 April 2020
      • Published Date: 15 April 2020

      Abstract: With the epidemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) worldwide and in the absence of any effective vaccine, there is an urgent need to find a specific anti- SARS-CoV-2 agent. In this study, by analyzing the secondary structures of the SARS-CoV-2 genome (MN908947), several 21~25 base-long segments were obtained and selected as the potential targets of small interfering RNA duplexes. Moreover, it was also found that these targets are conserved among different strains. We hope the results will contribute to the pharmaceutical research and therapy of the SARS-CoV-2.

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