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A display of “Intel”ligence

Senior Clare Zhu has been chosen as one of 40 finalists in the INTEL Science Talent Search, considered the “the nation’s oldest and most prestigious” research competition. The Northwood Howler sat down with this STEM queen to talk about her project.

Deena Saadi: Can you describe what your project is?
Clare Zhu:I wrote a computational drug design tool. Most drugs nowadays work by binding drugs to the proteins and then causing changes within the cells. When you look at these proteins under an extremely intense microscope you see that they are not static: they move all the time. It’s important for scientists to know exactly how they move and what kind of movements correspond to what kind of reactions within the body. So my tool uses the proteins’ motions to try to determine what effect the drug will have on the body.

DS:How did you get interested in protein movement and drugs?
CZ: I’ve always been pretty interested in computer science. I was looking for a lab to work in sophomore year, and I found a computational drug design lab; it sounded like something I would be interested in. Over the summer, when I was in Baltimore—they have a really big heroin problem there, in fact, the drug abuse research center was right next to the drug abuse rehab center—I met a lot of people who were former addicts or current addicts. They would ask what I was doing there. I said I was doing research, and they were amazed. It actually gave them so much hope that there were people out there who were doing research to fix their problems. Those were really inspiring moments for me.

DS: How did you come up with the idea for a computational drug design tool?
CZ: Well, the lab gave me the basic problem to work with, the overall big picture of what they wanted by the end of the summer. From there I had free reign to do whatever I wanted. I picked the programs that I’d be using to write the code and test the code and everything. A pretty big portion was done by me.

DS: Did you have a mentor or someone to help you through this process?
CZ: I had a mentor! On the first day, he gave me five [research] papers to read by the end of the week. He said, “We want to solve this problem, so tell me what you think.” He was very hands off which was good for me, because I really like exercising my creativity. I’m not allowed to publicly state who he is though because it might affect the judging.

DS: What was the result of the project?
CZ: I used the tool to see if there was anything interesting about these proteins. Because my tool is computational, it basically spits numbers out at me and it’s up to me to determine what the numbers mean. I noticed about four major discoveries. I don’t know how in depth you want me to go since they’re pretty detailed.
DS: No, go ahead! Hopefully, they’re not to difficult.
CZ: Ok ok, So the first one confirmed what we already knew in the field. This was a sanity check to make sure that my tool was actually confirming the results of other scientists. I combed through like 20 different papers and looked for what the scientists noticed as the main changes when the GPCR protein, which is the protein I studied, is activated. I cross-checked them with my numbers, and they were good!
From there, I moved onto the second stage, which was to see if my tool could detect changes that other people hadn’t detected. I noticed three different things. The first thing was when I tested a partial agonist with the protein. A partial agonist is between a full agonist and nothing at all. I wanted to see if the tool was sensitive enough to detect that this wasn’t a full activation, just a partial activation. And it was! I noticed that the movements were really small compared to the movements during full activation. This confirmed the sensitivity of my tool.
The second new discovery was about the binding site within a protein. [Binding sites are where the drug binds to]. Other scientists in the field noticed that the binding site contracts but they were really vague about it. So I ran my tool to see what actually contracts, how the shape changes. What I noticed was that some parts of the binding site actually contract but some parts were also expanding. That means there’s also a change in shape, not just a change in size.
My third major discovery was [about the differences in the proteins]. One GPCR protein can be involved in multiple signaling pathways. I wanted to see if there was any difference between proteins involved in different signaling proteins. I ran my tool and I saw some really noticeable changes.

DS: And you were the first person in the whole scientific community to make those discoveries?
CZ: Yeah.
DS: Congratulations!

DS: How long have you been involved with this project?
CZ: I’ve been involved with computational drug design since the summer of my sophomore year, so I have a pretty strong background. This particular project took about 8-10 weeks. It was a full time job, so I was at the lab for at least 40 hours a week—coding, testing debugging, coding, testing, debugging. But I also did my homework so-to-speak, like I took a lot of papers home and read them which took about an extra five hours per week. It was over the summer, which just meant I had to push all my summer homework to the last few weeks of summer.

DS: Where do you see yourself in five years?
CZ: I don’t know. I’ve tried to leave things as open as possible. I can see myself doing a lot of different things. I can be doing research, I could be getting a job in the pahrmeactucial industry, the technology industry…

DS: Many see this as a get-into-college-free card—that now that you’ve done this you can get into any college you want. How do you see it?
CZ: That’s an interesting question. A lot of the finalists that I’ve talked to have already gotten into college. They were impressive enough before the competition. For me, I got deferred from my two early colleges and I was a bit despondent about that. I think this a boost to my chances, but it’s not going to automatically get me into anywhere because the colleges that I’m applying to are holistic.
Intel is such a crapshoot. No one can say, “Oh I’m going to do research and become an Intel finalist.” That wasn’t my goal at all. I was mostly thinking, “I am learning so much.”