ABSTRACT
We modeled 3D structures of all SARS-CoV-2 proteins, generating 2,060 models that span 69% of the viral proteome and provide details not available elsewhere. We found that Ë6% of the proteome mimicked human proteins, while Ë7% was implicated in hijacking mechanisms that reverse post-translational modifications, block host translation, and disable host defenses; a further Ë29% self-assembled into heteromeric states that provided insight into how the viral replication and translation complex forms. To make these 3D models more accessible, we devised a structural coverage map, a novel visualization method to show what is-and is not-known about the 3D structure of the viral proteome. We integrated the coverage map into an accompanying online resource (https://aquaria.ws/covid) that can be used to find and explore models corresponding to the 79 structural states identified in this work. The resulting Aquaria-COVID resource helps scientists use emerging structural data to understand the mechanisms underlying coronavirus infection and draws attention to the 31% of the viral proteome that remains structurally unknown or dark.
Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , Host-Pathogen Interactions/genetics , Protein Processing, Post-Translational , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/metabolism , Amino Acid Transport Systems, Neutral/chemistry , Amino Acid Transport Systems, Neutral/genetics , Amino Acid Transport Systems, Neutral/metabolism , Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/genetics , Binding Sites , COVID-19/genetics , COVID-19/metabolism , COVID-19/virology , Computational Biology/methods , Coronavirus Envelope Proteins/chemistry , Coronavirus Envelope Proteins/genetics , Coronavirus Envelope Proteins/metabolism , Coronavirus Nucleocapsid Proteins/chemistry , Coronavirus Nucleocapsid Proteins/genetics , Coronavirus Nucleocapsid Proteins/metabolism , Humans , Mitochondrial Membrane Transport Proteins/chemistry , Mitochondrial Membrane Transport Proteins/genetics , Mitochondrial Membrane Transport Proteins/metabolism , Mitochondrial Precursor Protein Import Complex Proteins , Models, Molecular , Molecular Mimicry , Neuropilin-1/chemistry , Neuropilin-1/genetics , Neuropilin-1/metabolism , Phosphoproteins/chemistry , Phosphoproteins/genetics , Phosphoproteins/metabolism , Protein Binding , Protein Conformation, alpha-Helical , Protein Conformation, beta-Strand , Protein Interaction Domains and Motifs , Protein Interaction Mapping/methods , Protein Multimerization , SARS-CoV-2/chemistry , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/genetics , Viral Matrix Proteins/chemistry , Viral Matrix Proteins/genetics , Viral Matrix Proteins/metabolism , Viroporin Proteins/chemistry , Viroporin Proteins/genetics , Viroporin Proteins/metabolism , Virus ReplicationABSTRACT
CATH (https://www.cathdb.info) identifies domains in protein structures from wwPDB and classifies these into evolutionary superfamilies, thereby providing structural and functional annotations. There are two levels: CATH-B, a daily snapshot of the latest domain structures and superfamily assignments, and CATH+, with additional derived data, such as predicted sequence domains, and functionally coherent sequence subsets (Functional Families or FunFams). The latest CATH+ release, version 4.3, significantly increases coverage of structural and sequence data, with an addition of 65,351 fully-classified domains structures (+15%), providing 500 238 structural domains, and 151 million predicted sequence domains (+59%) assigned to 5481 superfamilies. The FunFam generation pipeline has been re-engineered to cope with the increased influx of data. Three times more sequences are captured in FunFams, with a concomitant increase in functional purity, information content and structural coverage. FunFam expansion increases the structural annotations provided for experimental GO terms (+59%). We also present CATH-FunVar web-pages displaying variations in protein sequences and their proximity to known or predicted functional sites. We present two case studies (1) putative cancer drivers and (2) SARS-CoV-2 proteins. Finally, we have improved links to and from CATH including SCOP, InterPro, Aquaria and 2DProt.