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CATH-FunVar - Predicting Viral and Human Variants Affecting COVID-19 Susceptibility and Severity and Repurposing Therapeutics

Reference	BB/W003368/1
Principal Investigator / Supervisor	Professor Christine Orengo
Co-Investigators / Co-Supervisors
Institution	University College London
Department	Structural Molecular Biology
Funding type	Research
Value (£)	116,828
Status	Completed
Type	Research Grant
Start date	10/05/2021
End date	09/05/2022
Duration	12 months

Abstract

unavailable

Summary

SARS-CoV-2 has caused a pandemic resulting in millions of deaths worldwide and significant social and economic disruption. Although vaccine trials have been encouraging vaccines must be distributed globally and therapeutic interventions will be needed for some time. It is clear that some human populations are much more vulnerable to the disease. For example older men and black and Asian communities. The factors causing these differences are still unclear and whilst social, economic and cultural issues are likely to be important, genetic factors could also play a role. Furthermore, the biological mechanisms by which severe responses arise and increase morbidity are still not known. In this project we will analyse genetic variations (causing reside mutations in the proteins) in diverse human populations (e.g. gender, ethnicity, people with severe responses) and in SARS-CoV-2. We will use structural and evolutionary data to determine whether the mutations could affect binding between the virus and human proteins. Human proteins in which mutations do affect binding will be mapped to protein networks to identify biological pathways that could be affected. We have powerful tools for functionally annotating proteins and the pathway modules in which they operate. Our data will rationalise the impacts on disease severity and improve diagnostics for populations at risk. Finally, proteins in these pathways are likely to be effective drug targets and we will use our protein family data to identify or repurpose suitable drugs having low side effects. We will also analyse related coronaviruses to identify future risks. We have already established a website (https://funvar.cathdb.info/uniprot/dataset/covid) providing mapping of SARS-CoV-2 viral proteins, functional annotations and proximity of mutations to known/predicted functional sites. This is currently populated with preliminary pilot data. It will be extended to host interactors and provide information on pathways andrepurposed drugs. Research Plan We will: (a) Classify 'human interactor' proteins interacting with viral proteins into CATH-FunFams to extract known or predicted structures and map variants (residue mutations) from different genders and populations onto these structures. (b) Perform FunVar analyses to identify mutations in human interactor and SARS-CoV-2 proteins likely to have functional impacts. (c) Map human interactors to a protein network to highlight biological processes implicated in host response and differentially affected between different genders/ethnicities (d) Identify human interactors which have clinically approved drugs or which map to FunFams from which clinically approved drugs can be repurposed. (e) Disseminate information via FunVar-COVID19 pages Our pipeline will detect diverse variants in different human populations, likely to be impacting functions and affecting Covid-19 response. It will also analyse available drug data to suggest possible therapeutics. Furthermore, our pipeline will be generic and will also be used to analyse other closely related coronavirus genomes that could pose future risks.

Committee	Not funded via Committee
Research Topics	Microbiology, Structural Biology
Research Priority	X – Research Priority information not available
Research Initiative	Covid19 Rapid Response [2020]
Funding Scheme	X – not Funded via a specific Funding Scheme

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