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Comprehensive analysis of the host-virus interactome of SARS-CoV-2
Zhen Chen; Chao Wang; Xu Feng; Litong Nie; Mengfan Tang; Huimin Zhang; Yun Xiong; Samuel K Swisher; Mrinal Srivastava; Junjie Chen.
Affiliation
  • Zhen Chen; The University of Texas MD Anderson Cancer Center
  • Chao Wang; MD anderson Cancer Center
  • Xu Feng; The University of Texas MD Anderson Cancer Center
  • Litong Nie; The University of Texas MD Anderson Cancer Center
  • Mengfan Tang; The University of Texas MD Anderson Cancer Center
  • Huimin Zhang; The University of Texas MD Anderson Cancer Center
  • Yun Xiong; The University of Texas MD Anderson Cancer Center
  • Samuel K Swisher; The University of Texas MD Anderson Cancer Center
  • Mrinal Srivastava; The University of Texas MD Anderson Cancer Center
  • Junjie Chen; The University of Texas MD Anderson Cancer Center
Preprint in En | PREPRINT-BIORXIV | ID: ppbiorxiv-424961
ABSTRACT
Host-virus protein-protein interaction is the key component of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lifecycle. We conducted a comprehensive interactome study between the virus and host cells using tandem affinity purification and proximity labeling strategies and identified 437 human proteins as the high-confidence interacting proteins. Functional characterization and further validation of these interactions elucidated how distinct SARS-CoV-2 viral proteins participate in its lifecycle, and discovered potential drug targets to the treatment of COVID-19. The interactomes of two key SARS-CoV-2 encoded viral proteins, NSP1 and N protein, were compared with the interactomes of their counterparts in other human coronaviruses. These comparisons not only revealed common host pathways these viruses manipulate for their survival, but also showed divergent protein-protein interactions that may explain differences in disease pathology. This comprehensive interactome of coronavirus disease-2019 provides valuable resources for understanding and treating this disease.
License
cc_by_nc_nd
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Type of study: Prognostic_studies Language: En Year: 2021 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Type of study: Prognostic_studies Language: En Year: 2021 Document type: Preprint