VarEPS: an evaluation and prewarning system of known and virtual variations of SARS-CoV-2 genomes

Author:

Sun Qinglan12,Shu Chang13,Shi Wenyu12,Luo Yingfeng134,Fan Guomei12,Nie Jingyi134,Bi Yuhai5,Wang Qihui5,Qi Jianxun5,Lu Jian6ORCID,Zhou Yuanchun7,Shen Zhihong7,Meng Zhen7,Zhang Xinjiao12,Yu Zhengfei12,Gao Shenghan13,Wu Linhuan12ORCID,Ma Juncai132,Hu Songnian134

Affiliation:

1. Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China

2. Chinese National Microbiology Data Center (NMDC), Beijing 100101, China

3. State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

5. CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China

6. State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China

7. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China

Abstract

Abstract The genomic variations of SARS-CoV-2 continue to emerge and spread worldwide. Some mutant strains show increased transmissibility and virulence, which may cause reduced protection provided by vaccines. Thus, it is necessary to continuously monitor and analyze the genomic variations of SARS-COV-2 genomes. We established an evaluation and prewarning system, SARS-CoV-2 variations evaluation and prewarning system (VarEPS), including known and virtual mutations of SARS-CoV-2 genomes to achieve rapid evaluation of the risks posed by mutant strains. From the perspective of genomics and structural biology, the database comprehensively analyzes the effects of known variations and virtual variations on physicochemical properties, translation efficiency, secondary structure, and binding capacity of ACE2 and neutralizing antibodies. An AI-based algorithm was used to verify the effectiveness of these genomics and structural biology characteristic quantities for risk prediction. This classifier could be further used to group viral strains by their transmissibility and affinity to neutralizing antibodies. This unique resource makes it possible to quickly evaluate the variation risks of key sites, and guide the research and development of vaccines and drugs. The database is freely accessible at www.nmdc.cn/ncovn.

Funder

National Key Research Program of China

Chinese Academy of Sciences

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics

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