Have you ever thought how exactly coronavirus looks like? And, how this microscopic pathogen sounds or invades your body and binds to the cells? No? What if we say that you can see and hear the novel virus? Yes, you read it right. Also Read - Coronavirus Can Stay on Face Masks for a Week, Last on Banknotes, Steel & Plastic For Days: Study

A scientist at the Massachusetts Institute of Technology (MIT), has created something astonishing that can leave you surprised. Markus Buehler, a professor at MIT and a musician, has made musical notes on coronavirus using artificial intelligence. And, what’s more flabbergasting is that this creation can help in preventing the virus from replicating. Also Read - Ravichandran Ashwin Questions as People Burst Crackers During PM Narendra Modi's #9pm9min Initiative Amid Coronavirus Lockdown



Before knowing much about the audible material manifestation of SARS-CoV-2 protein, let us hear it out. Also Read - Jaws Actor Lee Fierro Passes Away at 91 Due to Coronavirus Complications

Here is the link where you can find the music:



The sound that you just listened to, represents different aspects of the popular spike-protein present on the surface of coronavirus. These spikes are made of a combination of amino acids. They help in latching onto the body cells of the host. The scientists actually used a new technique called sonification to assign each amino acid a unique note in a musical scale.

What was the need behind turning the structure of virus into music?

According to scientists, the recently created musical sound can help in finding sites on the spike protein where antibodies can bind, by just looking for specific musical sequences that corresponds to these sites. And, by comparing this musical sequence to a large database of other sonified proteins, it may become possibility to find a drug that can stick to the spike and prevent viral infection in the cells. Also, this method of studying protein is being considered faster and more intuitive than conventional methods like molecular modeling.