Last month, 17-year-old Eric Chen from San Diego, California became the third Grand Prize winner in Google Science Fair history. Judges awarded him $50,000, a 10-day trip to the Galapagos Islands, a year of mentoring, and other prizes. At a meeting in Google Headquarters after the awards were announced, Chen spoke about how he created 6 new flu drug candidates, and why more kids should be doing research
What inspired your project?
I live in San Diego, where some of the first cases of 2009 h1n1 swine flu took place in the U.S. It was then that I made the realization that flu isn’t just this benign virus. It can kill a lot of people. I started tracking the flu news, and I watched as the situation got worse and worse. I thought, “Why can’t we use the new computer power at our fingertips to speed up drug discovery and find new flu medicine?”
What was your first step?
I knew I wanted to do some computational research, so I looked for a computational lab to work at. I came across Dr. Rommie Amaro at the University of California, San Diego, and she was willing to let me work in her lab. Because this field was completely new to me, a lot of the initial steps were figuring out what this field was about, what are the possible tools I might use in this field, and how I might implement them.
You decided to look for chemical compounds that would target a particular protein inside the virus and, essentially, disarm it. But you went about it in a novel way: by combining computer research with biological research.
I was sort of bouncing between a computer lab and a biological wet lab. I first used computers to screen through a library of almost half a million compounds and reduce that to a top 237. Then I took those 237 and went to a biological lab and actually tested them for activity against the flu target. So, I used computer models to make predictions, then biological testing to validate things that came out of the computational testing, and then I went back to the computational lab to think about how I might further develop these findings. I ended up with 6 top inhibitors.
One of the strategies you used is called molecular dynamic simulation. What does it do?
It uses supercomputer power to simulate every atom of a [flu] protein moving in solution. Previously, scientists had worked with crystal structures, which are static snapshots of this same protein.
With molecular dynamic simulation, you can see all of the possible pockets within a protein that you could build your inhibitor into, and what fraction of the time these pockets appear. That’s very important, because you want a really comprehensive understanding of what you are going to target before you go ahead and actually find something to plug it with.
What are the next steps for your project?
These are still pretty early in the drug discover pipeline. I haven’t done any animal studies. What I’m now working on is optimizing these inhibitors, giving them good drug-like traits. They have to be very, very potent, first of all, but they also can’t be toxic – you don’t want your drugs killing people rather than the flu.
Do you have any drug company interest?
I do, actually. I have a patent on these compounds through UCSD.
What sorts of careers might you pursue?
I’m looking at two different possibilities right now. One would be becoming a university professor, because I love teaching. That would let me do both research and teaching at the same time.
The other possibility would be going into business and becoming an entrepreneur. I’ve seen the power of doing these interdisciplinary approaches, and I think being able to bring the power of that to business would be great.
You also do a lot of science outreach to younger kids, helping schools set up science fairs and the Science Olympiad competition. Why is that important to you?
Ever since I was 15, I was very, very driven to do research, and because of that I ran right through obstacles, such as e-mailing professors I didn’t know. But a lot of these younger students, they’re afraid to try. They see a lot of obstacles in science, and that really turns them away from the field.
I’m really trying to dig in the idea that, when you do scientific research, you’re doing stuff that nobody has done before -- I felt like that was a very important idea, at least for myself. If I can give them a taste of that discovery feeling, they will hopefully be willing to face obstacles in the future. And doing research is not just something that stays in the field. Even if they decide not to pursue research in the future, they will have gained things like communication skills, and the ability to share their ideas and thought processes, how to tackle a problem, the willingness to face obstacles. That can go into any field they choose in life.
UPDATE: On Dec. 10, 2013, Chen went on to win a grand prize at the annual Siemens Competition for Math, Science & Technology. The prize earned him a $100,000 scholarship and praise from judges for his "outstanding interdisciplinary approach to research."