Chen Yuanguang chose to work with Levitt instead. Levitt shared some of the latest scientific developments with him, while he tried to find a concrete solution.
"Yuanguang, the virus is mutating too quickly.
Do you think we could use vaccines to induce its directed evolution, gradually reducing its virulence until it falls below even that of influenza?"
After becoming familiar with Chen Yuanguang, Levitt liked calling him by his Chinese name.
Through Chen Yuanguang's paper on protein-directed evolution, he had thought of using induced evolution to actively choose the direction of evolution.
Chen Yuanguang replied over the phone, "Professor, I had previously been thinking of developing a Broad-spectrum Vaccine to combat its continual mutations.
But now, combining induced directed evolution with a Broad-spectrum Vaccine should allow us to solve the virus in four or five vaccinations."
Once they had an idea, they got to work.
"Yuanguang, this idea is brilliant. We should identify the most common mutation sites among the existing strains.
Then we can design antigens that cover the sites with the highest mutation frequencies, minimizing the immune escape capabilities of current and future viral variants as much as possible.
Yuanguang, your thinking is correct."
"Yuanguang, sever the binding ability between the S Protein and the ACE Receptor. That would reduce the virus's transmissibility. Given that common mutations have already appeared across viral lineages, such as the D614G observed at Harvard and the del69-70 observed in China, we now need to identify the common mutations among them."
"The current data is insufficient. We need more data for verification."
"Yuanguang, since the mutation data is insufficient, there's no problem with using computer simulations to calculate mutation patterns.
But there is one issue: how can you ensure that the high-frequency common mutations you calculate match those in the real world?
That is extremely difficult. If the algorithm is designed incorrectly, the antigen design will fail to achieve the expected broad-spectrum effect."
"Yuanguang, you truly are a genius. Based on the latest variant strains detected in cities such as New York, Tokyo, and Johannesburg, the common mutations produced by our algorithmic simulations were an exact match. We've found the way forward!"
"Yuanguang, we can absolutely prepare to submit the paper now. If the subsequent Broad-spectrum Vaccine design adopts our approach, then considering its value, our achievement will be enough to win next year's Nobel Prize!"
"Yuanguang, I deeply regret not fighting to have you pursue your doctorate under me back then."
Levitt's attitude had shifted from cooperation at the beginning to complete admiration later on. He even felt as though he were riding Chen Yuanguang's coattails.
As for Bawendi, after learning of Chen Yuanguang's work, he said directly, "Yuanguang, once this result is complete, I think you can receive your doctoral degree. Neither MIT nor I have much more to teach you.
Your accomplishments in computational chemistry have already far surpassed mine, and you are not particularly interested in conducting experiments. I believe entering the next stage sooner will be more beneficial to your growth."
After MIT organized experts to review the paper, it received extraordinarily high praise. After it was accepted by Science, MIT specially invited frontline researchers from around the world working in this field to hold a remote video conference.
"Given the limited circumstances, we can only introduce to everyone online the outstanding contribution made by Mr. Light Chen, a doctoral student in our university's chemistry department, to the fight against the virus."
Professor Lan Ke was a biology professor at a 985 University in China. Since the outbreak began, he had been conducting related research and had paid close attention to seminars and lectures at top overseas universities.
Some of the group chats among researchers at related universities also shared information. Online conferences on MIT's scale, with two thousand participants, were still relatively rare.
Because everyone in the group said MIT attached great importance to this meeting, and some prominent figures claimed it was an unprecedented breakthrough result, he signed up.
Lan Ke discovered that the slots were already gone just five minutes after he registered in the group.
Backed by the names of MIT and Levitt, this seminar became hugely popular.
Lan Ke knew who Levitt was, but Light Chen was Chinese, and the problem was that he had never heard of such a person before.
The paper had only been accepted by Science and had not yet been published. Furthermore, Chen Yuanguang's previous papers in top journals had been concentrated more in computational chemistry and computational biology. Vaccine research was the domain of virology experts, so it was perfectly normal that people did not know him.
Why did this person look somewhat familiar? And he looked rather young. After entering the Zoom video conference room, Lan Ke muttered to himself.
"Broad-spectrum Vaccine design is not a simple addition of mutation sites. It requires a rigorous combined analysis of bioinformatics calculations and experimental evidence.
Nor are more mutation sites necessarily better. The most important thing is accurate data. We need to find their commonalities; the more pronounced those commonalities are, the more significant the serial immunization effect will be.
The problem we faced this time was enormously challenging. Global health was under attack. We could not wait for viral mutation data to accumulate to a certain extent before designing a Broad-spectrum Vaccine.
So, without enough viral strains or enough mutation sites, we could not identify commonalities. Yet we still had to create a Broad-spectrum Vaccine, because even traditional vaccines, including mRNA vaccines, only provide coverage for a limited time. Judging by the virus's current mutation patterns, that coverage period would be extremely, extremely short.
Faced with this dilemma, my solution was simulated evolution: simulating viral evolution, then analyzing the simulated viral mutation sites alongside real viral mutation sites to identify commonalities. Simply put."
Speaking to the video conference caused him no pressure whatsoever.
If everyone had not been muted, the rising and falling gasps from two thousand people would have drowned out his voice.
As Lan Ke listened, he thought, This was absurd. Designing a vaccine based on simulated viruses—how could you guarantee that the virus would actually evolve according to the mutation sites you simulated?
This was not science. It was mysticism. Even wrapped in the guise of data analysis and data modeling, it was still mysticism.
Until he saw the final data comparison: the variant viruses they had simulated in April had actually appeared in the global surveillance report in July. Lan Ke's jaw dropped onto the table.
Before you continue