Computational predictions of protein structures associated with COVID-19

The scientific community has galvanised in response to the recent AlphaFold system by releasing structure predictions of several under-studied proteins associated with SARS-CoV-2, the virus that causes COVID-19. We emphasise that these structure predictions have not been experimentally verified, but hope they may contribute to the scientific community’s interrogation of how the virus functions, and serve as a hypothesis generation platform for future experimental work in developing therapeutics. We’re indebted to the work of many other labs: this work wouldn’t be possible without the efforts of researchers across the globe who have responded to the COVID-19 outbreak with incredible agility.

Knowing a protein’s structure provides an important resource for understanding how it functions, but experiments to determine the structure can take months or longer, and some prove to be intractable. For this reason, researchers have been developing computational methods to predict protein structure from the amino acid sequence. In cases where the structure of a similar protein has already been experimentally determined, algorithms based on “template modelling” are able to provide accurate predictions of the protein structure. AlphaFold, our difficult for template modeling. While these understudied proteins are not the main focus of current therapeutic efforts, they may add to researchers’ understanding of SARS-CoV-2.

Normally we’d wait to publish this work until it had been peer-reviewed for an academic journal. However, given the seriousness and time-sensitivity of the CASP_Commons site, a collaborative effort of members of the CASP (Critical Assessment of Structure Prediction) community. CASP_Commons encourages research groups to share structure predictions for proteins with high biological significance. This spring, they collected predictions for a number of SARS-CoV-2 proteins, and we submitted several models for the 5 listed above, plus ORF3a.On June 17, an here.

Citation: John Jumper, Kathryn Tunyasuvunakool, Pushmeet Kohli, Demis Hassabis, and the AlphaFold Team, “Computational predictions of protein structures associated with COVID-19”, Version 3, DeepMind website, 4 August 2020,