A missense variant effect prediction and annotation resource for SARS-CoV-2

• DOI: 10.1101/2021.02.24.432721
• Publication Date: 2021-02-25T03:15:15Z
• Authors: Alistair Dunham; Gwendolyn M Jang; Monita Muralidharan; Danielle Swaney; Pedro Beltrao
• Keywords: Infectivity; Complement

Abstract The COVID19 pandemic is a global crisis severely impacting many people across the world. An important part of response monitoring viral variants and determining impact they have on properties, such as infectivity, disease severity interactions with drugs vaccines. In this work we generate make available computational variant effect predictions for all possible single amino-acid substitutions to SARS-CoV-2 in order complement facilitate experiments expert analysis. resulting dataset contains from evolutionary conservation protein complex structural models, combined phosphosites, experimental results frequencies. We demonstrate predictions’ effectiveness by comparing them expectations frequency prior experiments. then identify higher significant predicted effects well finding measured antibody binding that are least likely other functions. A web portal at sars.mutfunc.com , where can be searched downloaded.