Small SARS-CoV-2 protein may have huge ramifications for future COVID-19 medicines

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• Source: Penn State


• Date: 12 Apr,2021

A very small protein of SARS-CoV-2, the coronavirus that gives rise to COVID-19, may have big implications for future therapies, according to a team of Penn State researchers.

Using a novel toolkit of approaches, the scientists uncovered the first full structure of the Nucleocapsid (N) protein and discovered how antibodies from COVID-19 patients interact with that protein. They also determined that the structure appears similar across many coronaviruses, including recent COVID-19 versions — making it an ideal target for innovative treatments and vaccines.

Most of the diagnostic tests and available vaccines for COVID-19 were created based on a bigger SARS-CoV-2 protein — the Spike protein — where the virus attaches to healthy cells to begin the invasion process.

The Pfizer/BioNTech and Moderna vaccines were designed to help recipients produce antibodies that protect against the Spike protein. However, Kelly said, the Spike protein can easily mutate, leading to the versions that have emerged in the United Kingdom, South Africa, Brazil and throughout america.

Contrary to the outer Spike protein, the N protein is encased in the virus, protected from environmental pressures which cause the Spike protein to change. In the blood, but the N protein floats freely after it’s released from infected cells. The free-roaming protein induces a strong immune response, causing the production of protective antibodies. Most antibody-testing kits look for the N protein to determine if a person was previously infected with the virus — instead of diagnostic tests that look for the Spike protein to determine if a man is currently infected.

“Everybody is looking at the Spike protein, and there are fewer studies being performed on the N protein,” explained Michael Casasanta, first author on the paper and a postdoctoral fellow at the Kelly laboratory. “There was this difference. We saw a chance — we had the ideas and the resources to find out what the N protein resembles.”

Initially, the researchers analyzed the N protein sequences from humans, as well as different creatures thought to be potential sources of the pandemic, such as bats, civets and pangolins. They looked similar but distinctly different, according to Casasanta.

“The sequences can predict the structure of each of these N proteins, but you can’t get all of the information from a prediction — you will need to see the actual 3D structure,” Casasanta said. “We converged the tech to see a new thing in a new way.”

The researchers used an electron microscope to image both the N protein and the site on the N protein in which electrons bind, using serum from COVID-19 patients, and developed a 3D computer model of the arrangement. They revealed that the antibody binding site remained the same across every sample, which makes it a possible target to treat individuals with any of the known COVID-19 variants.

“If a therapeutic can be designed to target the N protein binding site, it may decrease the inflammation and other lasting immune responses to COVID-19, especially in COVID long haulers,” Kelly said, referring to individuals who experience COVID-19 symptoms for six weeks or more.

The microchips are made from silicon nitride, instead of a more conventional porous carbon, and they contain thin wells with special coatings that bring the N proteins to the surface. Once prepared, the samples were flash frozen and analyzed through cryo-electron microscopy.

Kelly credited her team’s unique combination of microchips, thinner ice cubes and Penn State’s advanced electron microscopes outfitted with state-of-the-art detectors, customized from the company Direct Electron, for delivering the highest-resolution visualization of low-weight molecules from SARS-CoV-2 up to now.

“The technology combined led to a unique finding,” Kelly said. “Before, it was like looking at something frozen in the middle of the lake. Now, we’re looking at it through an ice cube. We can see smaller entities with a lot more details and higher accuracy.”