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

SARS-CoV-2已引起大流行，导致全球数百万人死亡，并造成严重的社会和经济破坏。尽管疫苗试验令人鼓舞，但在一段时间内，必须在全球范围内分发疫苗，并需要治疗性干预措施。很明显，一些人群更容易感染这种疾病。比如老年男性、黑人和亚裔社区。造成这些差异的因素尚不清楚，虽然社会、经济和文化问题可能很重要，但遗传因素也可能起作用。此外，产生严重反应和增加发病率的生物学机制仍不清楚。在这个项目中，我们将分析不同人群（例如性别、种族、有严重反应的人群）和SARS-CoV-2中的遗传变异（导致蛋白质的驻留突变）。我们将使用结构和进化数据来确定突变是否会影响病毒与人类蛋白质之间的结合。突变确实影响结合的人类蛋白质将被映射到蛋白质网络，以确定可能受到影响的生物学途径。我们有功能强大的工具来对蛋白质和它们运作的途径模块进行功能注释。我们的数据将合理化对疾病严重程度的影响，并改善对高危人群的诊断。最后，这些途径中的蛋白质可能是有效的药物靶点，我们将使用我们的蛋白质家族数据来识别或重新设计副作用低的合适药物。我们还将分析相关冠状病毒，以确定未来的风险。我们已经建立了一个网站（https://funvar.cathdb.info/uniprot/dataset/covid），提供SARS-CoV-2病毒蛋白的图谱、功能注释以及突变与已知/预测功能位点的接近度。这是目前填充的初步试点数据。它将扩展到宿主相互作用者，并提供有关途径和重新利用药物的信息。研究计划我们将：(a)将与病毒蛋白相互作用的“人类相互作用”蛋白分类到cat - funfams中，以提取已知或预测的结构，并将来自不同性别和种群的变体（残基突变）映射到这些结构上。(b)进行FunVar分析，以确定可能产生功能影响的人类相互作用物和SARS-CoV-2蛋白的突变。(c)将人类相互作用者映射到蛋白质网络，以突出与宿主反应有关的生物过程，并在不同性别/种族之间受到不同影响(d)确定具有临床批准药物的人类相互作用者，或映射到临床批准的药物可以重新利用的FunFams。(e)通过funvar - Covid-19页面传播信息。我们的管道将在不同人群中检测可能影响功能并影响Covid-19应对措施的各种变体。它还将分析现有的药物数据，以提出可能的治疗方法。此外，我们的产品线将是通用的，也将用于分析其他密切相关的、可能构成未来风险的冠状病毒基因组。

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 and repurposed drugs.Research PlanWe 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.