The goal of this project is to identify potential interactions between Angiotensin-converting enzyme 2 (ACE2) and other human proteins that have been implicated in human health problems related to covid-19 infection. ACE2 is the human cell receptor that the corona virus SARS-CoV-2 binds to and uses to enter and infect human cells. It also regulates blood pressure and is involved in digestion. Identifying previously undescribed ACE2 protein interactions will advance our understanding of its biological functions and its contribution to covid-19 pathology. A better understanding of the proteins with which ACE2 interacts can help identify therapeutic targets and lead to reducing the severity of covid-19 pathologies and complications, a key broader impact of this project.

The project will use a novel computational and evolutionary approach to identifying candidate ACE2 interacting proteins based on a set of mammalian proteins that “coevolve” with ACE2. The approach, termed “evolutionary rate correlation” (ERC) detects proteins that show highly correlated evolutionary rates during mammalian evolution. Such proteins are strong candidates for biological interactions with the ACE2 receptor. Preliminary results have identified candidate interacting proteins that are not currently known to be ACE2 interactors, but which are relevant to covid-19 pathologies. Among the top 20 coevolving proteins with highly significant correlations, four are involved in the blood coagulation cascade and six additional ones are implicated in blood cell related phenotypes. Three other proteins are implicated in inflammatory processes or endotoxic shock. These are striking findings, with clear potential implications to major covid-19 pathologies, including severe thrombosis (blood clotting), and Kawasaki-like syndromes in children. A strong association between ACE2 protein and these blood associated proteins has not previously been reported. Also detected are strong ERCs to lipid metabolism proteins. Based on these ERCs, the project will develop a protein interaction network, and expand the analysis to additional candidate coronavirus interacting proteins. This RAPID award is made by the Evolutionary Processes Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Environmental Biology (DEB)
Type
Standard Grant (Standard)
Application #
2034507
Program Officer
Samuel Scheiner
Project Start
Project End
Budget Start
2020-06-01
Budget End
2021-05-31
Support Year
Fiscal Year
2020
Total Cost
$17,361
Indirect Cost
Name
University of Rochester
Department
Type
DUNS #
City
Rochester
State
NY
Country
United States
Zip Code
14627