RESUMEN
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.
Asunto(s)
Enzima Convertidora de Angiotensina 2/metabolismo , Interacciones Huésped-Patógeno/genética , Procesamiento Proteico-Postraduccional , SARS-CoV-2/metabolismo , Glicoproteína de la Espiga del Coronavirus/metabolismo , Sistemas de Transporte de Aminoácidos Neutros/química , Sistemas de Transporte de Aminoácidos Neutros/genética , Sistemas de Transporte de Aminoácidos Neutros/metabolismo , Enzima Convertidora de Angiotensina 2/química , Enzima Convertidora de Angiotensina 2/genética , Sitios de Unión , COVID-19/genética , COVID-19/metabolismo , COVID-19/virología , Biología Computacional/métodos , Proteínas de la Envoltura de Coronavirus/química , Proteínas de la Envoltura de Coronavirus/genética , Proteínas de la Envoltura de Coronavirus/metabolismo , Proteínas de la Nucleocápside de Coronavirus/química , Proteínas de la Nucleocápside de Coronavirus/genética , Proteínas de la Nucleocápside de Coronavirus/metabolismo , Humanos , Proteínas de Transporte de Membrana Mitocondrial/química , Proteínas de Transporte de Membrana Mitocondrial/genética , Proteínas de Transporte de Membrana Mitocondrial/metabolismo , Proteínas del Complejo de Importación de Proteínas Precursoras Mitocondriales , Modelos Moleculares , Imitación Molecular , Neuropilina-1/química , Neuropilina-1/genética , Neuropilina-1/metabolismo , Fosfoproteínas/química , Fosfoproteínas/genética , Fosfoproteínas/metabolismo , Unión Proteica , Conformación Proteica en Hélice alfa , Conformación Proteica en Lámina beta , Dominios y Motivos de Interacción de Proteínas , Mapeo de Interacción de Proteínas/métodos , Multimerización de Proteína , SARS-CoV-2/química , SARS-CoV-2/genética , Glicoproteína de la Espiga del Coronavirus/química , Glicoproteína de la Espiga del Coronavirus/genética , Proteínas de la Matriz Viral/química , Proteínas de la Matriz Viral/genética , Proteínas de la Matriz Viral/metabolismo , Proteínas Viroporinas/química , Proteínas Viroporinas/genética , Proteínas Viroporinas/metabolismo , Replicación ViralRESUMEN
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.