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Modeling SARS-CoV-2 proteins in the CASP-commons experiment.
Andriy Kryshtafovych1, John Moult2, Wendy M Billings3
1Genome Center, University of California, Davis, Davis, California, USA.
Proteins
|August 31, 2021
Summary
The Critical Assessment of Structure Prediction (CASP) project computed SARS-CoV-2 protein structures. AlphaFold2 models showed high accuracy, closely matching experimentally determined structures.
Area of Science:
- Computational Biology
- Structural Biology
- Virology
Background:
- The Critical Assessment of Structure Prediction (CASP) initiative drives advancements in protein structure computation.
- The SARS-CoV-2 pandemic prompted a CASP project focused on predicting structures of challenging viral proteins.
Purpose of the Study:
- To assess the accuracy of computational models for SARS-CoV-2 proteins.
- To evaluate the performance of different structure prediction methods.
Main Methods:
- Forty-seven research groups submitted over 3000 3D models for 10 SARS-CoV-2 proteins.
- Accuracy estimates were provided for models and experimentally determined structures (ORF3a, ORF8).
Main Results:
- AlphaFold2 models demonstrated strong agreement with experimental structures.
- Main chain GDT_TS accuracy scores for AlphaFold2 ranged from 63 to 87.
Conclusions:
- Computational protein structure prediction methods, particularly AlphaFold2, are highly effective.
- Accurate structure models can be rapidly generated for emerging viral threats.