Big Compute - The Power of Plants to Pulverize Coronavirus

Episode Date: November 12, 2020

What if that plant on your desk could hold the key to stopping your stuffy nose?  From morphine to chemotherapy drugs, plants have played a vital role in developing pharmaceuticals to treat all kinds of ailments.  We talk to undercover superhero, Jerome Baudry of the University of Alabama in Huntsville, about his computational search through hundreds of thousands of chemical compounds from plants around the world, on the hunt for a therapeutic that can seek out and stop the one hindrance on all of our minds -- the coronavirus.

I swear the loudest lawnmower of my life is just outside my house. Oh, the joys of working from your closet. Hello, everyone. I'm Jolie Hales. And I'm Ernest DeLeon. And welcome to the Big Compute Podcast. Here we celebrate innovation in a world of virtually unlimited compute, and we do it one important story at a time. We're talking about the stories behind scientists and engineers who are embracing the power of high performance computing to better the lives of all of us.

From the products we use every day to the technology of tomorrow, high-performance computing plays a direct role in making it all happen, whether people know it or not. Okay, Ernest, so to kick this off, I have a question for you. What is your favorite national park? So this may surprise many people, but it's Joshua Tree. Oh, really? That's not too far away from me. No, it's not. I happened upon it on accident driving between California and Texas one year.

Oh, really? Did you just get lost and end up in a national park? No, what ended up happening was I was driving back home and I hadn't decided where I was going to stop the first day. And I happened upon Joshua Tree and I liked the area. So I said, well, I'll just stay here the night. So I stayed at some random like holiday inn or something. I don't even remember what the hotel was. But so I went in and kind of drove around in there and was amazed by it. This is the first time I went there. Then obviously I went back to it later and stayed for a few days in the area and kind of, you know, walked around the entire area several times after that. And to this day, it's my favorite national park. Yeah, I haven't been to Joshua. For

me, it's tough to pick. I grew up in Utah, so I was totally spoiled by being surrounded by all these beautiful national parks. But I guess if I had to pick a favorite national park it would probably be glen canyon and that's only because it includes lake powell and lake powell is where i spent a lot of my childhood and i have a lot of crazy memories there both the awesome memories but also like completely terrifying am i going to survive this sort of memories like in a lightning storm my boat sank when I was on it in the middle of the lake and I was marooned on an island. But all of those memories, just, I don't know, I've got this kind of special place in my heart for Lake Powell. Yeah, lakes in general are great. I don't know, there's something about just being out in the water, in nature. But have you ever heard of,

and this has to do with our episode, right? Transition into our actual subject. Have you ever heard of Gifford Pinchot National Forest? No, I haven't. Okay. I hadn't heard of it either. Apparently it's in Washington state and it's near Mount St. Helens, which you've probably heard of. Yes. And so as you might imagine, it's filled with like lush green trees that are stretching up to the sky. You've got

your flowing streams, your cute little squirrels and your animal life, mountain views, pretty much everything that you might expect from a national park in a state that gets a lot of rain. So everything's pretty green. Right. And back in August of 1962, something happened there that later resulted in saving and extending the lives of millions of people. I want to take you back to that day in August in 1962, and I want you to imagine that it's this nice cool summer day it's at this Washington National Park the temperature was in the low 60s with clouds overhead and then there was this guy so imagine this man in his 30s standing and looking at a group of trees with his hands on his hips so this man's

name is Arthur Barkley, and he's a Harvard-trained botanist who works for the US Department of Agriculture. And he's basically nearing the end of his four-month trip across the Western United States, where he's been collecting samples of trees and weeds and shrubs and seeds, anything plant-related that he can find.

And the hope was that something he collected would contain natural chemicals that could potentially be used in medicines down the line. So here he was, he's standing in Gifford Pinchot National Forest and he's looking at this 25 foot tall evergreen tree. And it's not like an evergreen tree that looks like a Christmas tree like we might think of as an evergreen tree. And it's not like an evergreen tree that looks like a Christmas tree like we might think of as an evergreen tree. Instead it has these thin kind of crooked branches that spread out in every which way and it's covered in flat wide needle-like leaves and little red berry looking things. And Arthur Barclay casually just basically pointed to the tree and then his team of botanists got to work collecting samples like they had been doing for weeks. No one really knew anything about this tree. They just knew that they were supposed

to collect samples of plants at random. And this is the next one in sight. Interesting. I wonder what kind of tree that is. So the tree was called a Pacific yew. Have you ever heard of that? It's Y-E-W-E-W. I've heard the term yew before, not Pacific yew. And yew is a type of wood that has been used to make like natural fishing poles, if you want to call it that. That's so funny that you know that because that's totally true. There's a few different kinds of yew trees and shrubs and whatnot. And they're used to make like fishing rods and bow and arrows and all that kind of stuff. And this lawnmower is literally like right outside my house. I heard it that time.

I haven't heard it up until right now. This guy, I swear he's like, ooh, I bet there's a podcast being recorded in that house. I better take my leaf blower and hang out for 20 minutes. I'm never gonna leave. This particular tree is a type of yew. There's a few different types and it's called a Pacific yew. And basically as Arthur Barclay's team clipped samples of it. And then after a while, he moved on to the next plant. It must be so interesting to be a botanist.

I know. I would love to just spend time out in nature and look at plants. I don't think that's all they do. I guess that's what I think of when I think of a bot is just going out and hanging out with plants. So this is in 1962, right, where Arthur Barclay and his team are collecting these samples of the Pacific ewe. Now, fast forward through 31 years of research, testing, politics, which we know something about these days, and controversy. And the Pacific ewe was saving lives. Now, specifically, what I mean by that is molecules from the Pacific ewe tree bark

led to the creation of Taxel or Paclitaxel, which is actually a chemotherapy drug that has now been used to treat millions of patients with ovarian cancer, breast cancer, lung cancer, cervical cancer, pancreatic cancer, and others. But it all started with that simple plant sample collected in the middle of Washington in August of 1962. That's amazing. I often run across various people in general who always make the comment that there are so many yet undiscovered chemicals or molecules like this, especially in places like the Brazilian rainforest. Yeah. So this is super interesting. But imagine those places where human beings have not gone or cannot easily get to because of logistics and terrain.

Right. It makes you wonder what's out there that we could be using. And that's basically what this episode is about. I really had no idea how many of our modern day pharmaceuticals actually originated from plants. But there have been quite a few. Everything from metformin, which is used to treat type 2 diabetes, to morphine that basically helped me get some sleep during a painful 52 friggin hour labor when my son was born. Those two types of drugs and others have originated from chemicals pulled directly from plants. A lot of times it's just a matter of having access and getting a large enough population sample to determine what these substances can actually do for people.

I mean, since plants have often kicked off the drug discovery process for medicines, today the question is now being asked on whether or not there's a natural substance out there that could help us with, I mean, do you care to guess? Ebola. Or would it be COVID? It would be COVID. It would be COVID. I know. It's that one virus you haven't heard of. At all. Yeah. No idea what it is. Like never, right? And I figure since COVID doesn't seem to want to leave us alone,

we might as well use another episode of this podcast to try to figure it out. So today we're going to talk to an undercover superhero, as we say, who's had this question, can plants help us treat symptoms of coronavirus? And asking that question was this man. My name is Jerome Baudry. I am a professor at the University of Alabama in Huntsville. And Jerome specializes in computational biology with a particular focus on drug discovery, which he's been doing for 20 years, both in Europe and the United States. And when he isn't pushing the boundaries of scientific research, Jerome prefers to do nothing at all. What do you like sit on a bench and just sit? Pretty much. Pretty much.

And I must say I greatly enjoy that. I can't disagree with him at all. I often find great joy in doing absolutely nothing. Really? Given the pace of our actual careers. Yeah, I just I'm jealous of you being able to do nothing. I can't just sit there and do nothing very well. I mean, my brain goes crazy. And then I think of all the things I could be getting done that I'm

not doing. Yeah, I'm not saying I do it often. It's very rare. But the times when I get the opportunity to just relax and do nothing, they're treasured because nowadays i think everybody is just so busy right and i think humans have generally lost the art of doing nothing i mean he says he does like to meditate which is technically doing something um though he says traditional meditation with yoga or like controlled breathing with his eyes closed that all all drives him nuts. Instead, he likes to lose himself in contemporary repetitive music. Like, I don't know if you're familiar with Philip Glass. No, I actually didn't know Philip Glass super well, but I went to go listen to him. And since we don't have the rights to play actual Philip Glass music,

I scoured the online royalty free music world to find an imitation. So Jerome is a Philip Glass fan, and he's also a fan of Stanley Kubrick movies and Russian literature. Sometimes it feels like you're reading a telephone directory. It's full of names and very little action. But I kind of like it because it has this kind of slow pace, slow rhythm, which I find very meditative. So you're saying that you're a pretty uptight, high strung kind of personality is what I'm gathering. No, I'm a very mellow guy. I like to, at least I think I am, I like to just contemplate. I think contemplation of nature, of arts, of appreciation is what really fulfills me with joy.

Just being around my family, you know, my spouse and children. That's what I like, even if it's to do nothing at all, actually. That's pretty amazing. I actually have to give Jerome props for that. Having the ability to kind of slow down and just enjoy things, I think, is great. I think many of us lack that. He thinks, interestingly enough, that his personality is a countermeasure to the fast-paced supercomputers to accelerate the discovery of new drugs, new pharmaceuticals against quite a lot of different diseases.

In my lab, we're particularly interested in mental health and inflammation diseases. But as you can imagine, something happened in the few last months, and that's this COVID-19 crisis. And we have been part we have been playing a big role I think the national international actually efforts to try to accelerate greatly the discovery of a potential pharmaceutical against this disease. Yeah and this is just part of a larger trend we've seen even through our own podcast series of scientists having to pivot away from things that they traditionally worked on and start looking at COVID through the lens of the type of work that they did before. Yeah, so no one was planning to study COVID-19 because it basically came out of nowhere,

which means that every working scientist who is now in the fight against COVID had to stop what they were working on, no matter what it was, and switch directions. Jerome actually found out that the coronavirus existed pretty early when a colleague by the name of Roy Magnusson started to suspect that the virus that had sprung up in China probably wasn't going to go away. Who kind of said, well, this one has all the fingerprints of the big one, kind of. The one that you would see in horror movies or disaster movies. And so it kind of raised the attention of everyone. So Jerome got to work, suddenly focused on this new virus. Everything went extremely quickly from there.

And not only did the virus take over his work, but it affected his family. In fact, Ernest, I know that someone in your own family was hit by the virus, if I remember right. What was that like? That's right. It was actually my sister, who is an RN and works in a hospital. She got it from an asymptomatic person who entered her ward during the initial surge of the pandemic. And she had fairly significant symptoms. Nothing that put her, you know, in the bed or in a hospital. She actually recovered at home. But it was still pretty scary because we were early on in this pandemic and we really didn't understand everything we understand now in terms of treatment and therapy and what's causing people to get infected or anything like that. So for us, it was very concerning.

That's some scary stuff, especially so early in this entire situation. I mean, talk about hitting close to home when your own sister gets it. And as I was talking to Jerome, actually, you and he have that in common. My sister in France got the disease quite early on, actually. Your sister had COVID? Yes, yes, she did. And she did well. It wasn't comfortable for her, but fortunately, she was part of this fraction of the population

for which it turns out to not be that big a deal. I think it's interesting that both you and Jerome has had a sister who has caught COVID. And as of my interview with Jerome, my family had somehow managed to avoid it. But I actually just found out a couple days ago that my own brother and his wife both have COVID right now. So they're at home and I shouldn't laugh, but it's kind of funny because for them, they are lucky to be asymptomatic. My brother completely asymptomatic, and then my sister-in-law just has a prolonged headache. They're both in their 20s and don't have any high-risk kind of conditions for it. And then they have a little baby that, thank goodness, COVID doesn't affect children too badly

for the most part. So lucky them, right? But it's interesting, they live 350 miles away. And we were actually in that town and I wanted to see him, but I was worried about COVID. So we ended up just seeing them for five minutes, but we were outside with masks on 15 feet apart. And then it was the next day that we found out that they were positive. And so I'm so glad that we were following these measures that we've been encouraged to take, because the last thing I want to do is catch COVID and then spread it to a higher risk family member. So all three of us, you, me, Jerome, we all have a sibling who has had COVID. And that just goes to show how personal this pandemic is.

Absolutely. And now that we're in the, I guess this would be the third surge, right? Because there was a spring surge, a summer surge, and now we're kind of in this hockey stick of the third surge. And, you know, I'm a student of history in many different aspects. And I immediately looked to the 1918 pandemic and started reading articles about it as soon as this one hit, just to kind of understand what happened last time. Yeah. And the bigger wave was in the fall, was exactly where we are right now.

Exactly. Like the first wave in the spring was actually really small, barely did anything. It was this time of year that most people died in 1918. And I can just express that I'm so grateful that we have the scientific knowledge that we do and the technology that we do and the speed of the technology that we do so that we can try to accelerate drug discoveries and whatnot to be able to fight this virus. And for Jerome, that's why when the opportunity came up to join this fight against COVID, he was totally on board. I've been working on this kind of research for a long time.

Before being in Alabama, in Huntsville, I spent about 10 years at Oak Ridge National Lab at the University of Tennessee, Knoxville. And to those of you who follow high-performance computing, you know that it's not just Oak Ridge National Lab at the University of Tennessee, Knoxville. And to those of you who follow high performance computing, you know that it's not just Oak Ridge National Lab. It's the Oak Ridge National Lab, which is home to some of the top supercomputers in the world, including a two and a half million core machine called Summit, which was the number one top supercomputer in the world before it was just dethroned a few months ago by the Fugaku supercomputer in Japan. So it was quite comfortable with using supercomputing for medical and pharmaceutical research. Jerome wasn't just familiar with doing this kind of research.

His group at the Oak Ridge Center for Molecular Biophysics actually developed a lot of the supercomputing technology that would be necessary for this kind of COVID-19 study. So when HPE Cray offered Jerome direct access to one of their supercomputers to do some COVID research together, Jerome wasn't about to say no. So my history of developing supercomputing technology for drug discovery was kind of the catalyst that made me join this research. So if you listen to our previous episodes, we talked about several different studies that went around COVID. One of them had to do with fluid dynamics

and how particulate flows around different types of rooms, an elevator, a grocery store, a classroom, musical instruments we talked about. We also talked about what the molecules or the coding of the COVID virus look like. And I'm curious to see what the outcome of this particular study is going to be. And Jerome's study is from a completely different angle than the past studies that we've talked about. What we are trying to do is to find a drug, all drugs, that will be active against the virus.

And when he says drug, it's good to note here that the drugs work differently than vaccines. Like with a vaccine, you purposefully expose your body to the virus in a sort of controlled way so that your immune system can recognize it and destroy it and then create antibodies that will hopefully protect you from that same virus in the future. Well, hopefully. Right. And as we discussed in the last interview with Romy Amaro and her research, the coronavirus is quite adept at camouflaging itself once inside the human body. So it is necessary to have multiple different ways to attack this thing other than just vaccines. Long live marshmallow peeps and space fighters. And if you don't know what I'm talking about,

the last episode will help you or hurt you. If you're diabetic, it'll kill you. Yeah, for real. But okay, to back up just a bit, when a virus invades the body, it attaches itself to a living human cell in order to survive, like a little parasite. And then it forces that human cell to create everything that the virus needs to survive and multiply. They have not been invited and they've not been properly introduced to us, but yet they do.

What a rude thing to do. Oh, mean. So the virus uses the hijacked cell to multiply and expand throughout the body, wreaking havoc on the person infected. But if we could somehow figure out a pharmaceutical treatment, a pill or some kind of drug, that could prevent the virus from functioning, we might be able to prevent it from making an already infected person extremely sick. So we're trying to teach them a lesson by preventing them from doing that. And Jerome says that the way a drug like this could work is by having a drug send these sort of warrior molecules through the body of a person already infected with COVID-19, and then having those molecules basically track down the virus and either prevent it from entering a human cell, or if it's already entered one, trap it inside that cell and prevent it from being able to hijack the controls and multiply itself and spread.

It's kind of the grain of salt or the grain of sand that you would put in a clock and stop the clock from functioning. And if the virus is trapped within a cell with no way to multiply, then the infected person is probably going to feel a lot better than they would have otherwise. So what would it actually take to figure out that kind of pharmaceutical treatment? Well, that's just it. So through all of human history up until recently, medicine has pretty much been just trial and error. There's, in fact, this really interesting article by Evan Andrews of the History Channel

that I found online, and we'll link to it in the episode notes. And it talks about some of the medical techniques that have been practiced since ancient times. Like, for instance, I'm sure you've heard of bloodletting. I sure have. Yeah. So every time I see it in like a historical movie or read about it being practiced in a biography, I just want to reach through time and shake the so-called doctor by the shoulders and say, you're making things worse. What are you doing? But bloodletting was practiced for thousands of years.

And back then, I wouldn't have known any different. And for those who aren't familiar, it's basically when a doctor would cut a sick person's vein and drain their blood, thinking that it would help them get better. This reminds me of one of the Star Trek Next Generation episodes where Data is supposed to go looking for some radioactive material on this planet that has a very non-advanced civilization and something happens to him and he loses his memory so he has the container with the radioactive material with him and wanders into this town of people who again are not you know not modern and doesn't know who he is what his name is or what this container is well this i think it's a jeweler opens up the case and sees the radioactive metal and thinks that it would make good jewelry so he starts making

jewelry out of this and the entire town you know not everyone but the people start getting very sick and the funny part is there's a character a woman who is supposed to be like a doctor slash scientist and she does exactly this. She's making up all of this science as she goes that has nothing to do with the truth. And it takes a while for them to actually figure out what happened, right? And this is exactly what happened back then. People just made things up based on what they thought was happening. And in most cases, it probably made it worse. The thing I love about that example is that it illustrates perfectly exactly historical medicinal practices, just like bloodletting.

But then number two, of course, you would mention a Star Trek reference. Of course. I think every time we record a podcast, you got to slide some Star Trek, some Lord of the Rings in there. It's amazing. I think our audience appreciates it. Oh, absolutely. Are you kidding me? We're all a bunch of nerds. And then there are other ineffective medical practices that existed as well, like drilling a hole in a person's skull to help treat an illness. Or this one's kind of like your Star Trek example,

rubbing mercury on your skin or even digesting it, which was actually thought to have killed Chinese Emperor Qin Shi Huang in 210 BC, which is kind of interesting because it appears he survived multiple assassination attempts over the course of his life, only to die from ingesting mercury pills, thinking that they would grant him eternal life. Yes. And I remember when I was younger, my dad commented how when he was in high school, the teachers would give them mercury. Oh, my gosh. Not ingest, but, you know, like as part of a science class and they would let them like roll it around in their hand. Oh,

yeah. Rub it in their fingers. You know, all these kind of things that now you would never allow a sane person to do. But they just didn't know back then. Yeah. And it wasn't that long ago. I mean, we're talking your parents. Right. Right. One generation back. And who knows how many of those people died from mercury poisoning without even knowing. Right. Because it wasn't until later that it was discovered that this was incredibly toxic to human beings. So, I mean, even though we don't have all the answers, I'm grateful that medicine has become more scientifically advanced. And as it has, drug discovery started to take place more in the laboratory instead of just these trial and error sessions on random people. Thank goodness. And that's when medical treatment really started to advance and save lives in great numbers. I mean, if you look at life expectancy charts, they changed completely in the 1950s because that's when medical technology and research really started to take off in a

scientific way. Normally, if you work in the pharmaceutical industry, you chop the virus into little pieces, into proteins, and you try to put all the proteins in test tubes and you screen tens of thousands of drug candidates. You put them in the test tube and you screen tens of thousands drug candidates, you put them in the test tube and you just see whether or not the drug candidates will stick to the proteins that are coming from the virus. So it's essentially still trial and error, but taking place in test tubes rather than on human subjects. Right. And this can take a lot of time and a lot of test tubes. They would pipette tens of thousands of recaninates in tens of thousands of test tubes in tens of thousands of little tiny fractions of a protein and see what sticks.

That sounds like an excruciatingly long process. And it is, apparently. And I mean, going back to the Pacific yew tree found in that Washington National Park, in that case, it took more than, get this, 30 years of test tubing and whatnot before that cancer treatment was actually available to the public. It's a totally amazing breakthrough, but can you imagine if it took 30 years for us to find and develop therapeutics for COVID-19? And today, thankfully, we can look into this stuff a lot more and a lot quicker with... Drumroll, please.

Supercomputers! That's right. Supercomputers allow us to do all kinds of things that were not possible 50 years ago, 100 years ago. And it is amazing what scientists like Jerome and many others are doing with these. Instead of using test tube, which takes a long time and costs a fortune, we're doing it with computers because we know how to calculate, how to predict if a drug candidate will stick to this part of the virus or that part of the virus. And they do this by computationally simulating how hundreds of thousands of chemicals collected from natural substances would interact with the coronavirus. Our simulations are based on models to calculate how much a given pharmaceutical will be happy or not to stick to a given protein from the virus.

So we reproduce a test tube screening that would take a long time and a lot of money. Calculate interaction between the atoms that are coming from the protein of the virus and the atoms that are making the substances we're interested in. So it's very much based on physics and physical chemistry. So instead of putting the chemicals

in a traditional test tube, they put them in a digital test tube and basically run the experiment digitally. That's exactly what they do. Where do they get the chemical profiles to run through the supercomputer? These chemical profiles are from substances that have pretty much been collected by scientists for years. So just like how Arthur Barclay harvested the Pacific ewe. Or Lara Croft. Or Lara Croft. Or Indiana Jones. They are found in plants. They are found in algae. A lot of them come from tropical regions, actually. It's just because the biodiversity of the tropical regions is known to be usually larger than the biodiversity at more temperate or colder regions.

So we have a lot of sea organisms that give interesting compounds as well. At the same time, they need to be close to the coast. Otherwise, no Indiana Jones will be diving at 10,000 feet to harvest, although some do. So it's a combination of opportunities to harvest them and chemical diversity. So we have a lot of compounds that come from these regions, but also some compounds that are not far from more traditional plants that we see at our latitudes. So the sources are diverse and include everything from plants to animals or animal-like and fungi. Basically, chemicals have been extracted from plants that are found wherever scientists

can put boots on the ground or even get a diver to reach in the water. If there's a plant out there, scientists are interested in learning more about its chemical composition and have already been collecting as many samples as possible for decades. And one reason scientists do this is because it's actually a lot easier and faster to find chemicals that can be used in therapeutics than trying to create a therapeutic completely from scratch. Evolution has already spent the last few million years fine-tuning very special chemicals to perform very special functions.

And so instead of manufacturing, synthesizing molecules totally out of the blue, let's take advantage of this millions of years of evolution that has done a great deal of chemical work for us and try to see if nature has already provided us a key for the door we are trying to open. Now, we still have to try all those keys, but we may not have to invent it from scratch, basically. And once a plant sample has been collected, scientists have to extract the chemicals from that plant, which is no small effort. I actually watched a few videos on how to do this,

and it's basically a lot of test tubes and lab coats mixing together and separating things very precisely over a few hours or a few days and then evaluating them on a computer. Until they can take a look at the chemical profiles. Yes. And thanks to advances in technology, scientists like Jerome can take those chemical profiles and then run them through a supercomputer to simulate how each chemical would interact specifically with the coronavirus. We must have screened 200,000 compounds. 200,000 is a large number. In what time frame are we talking here? They can screen all 200,000 compounds in a single day through a supercomputer. I think my iPhone can do the same thing. Oh, yeah. Your iPhone might be cool, but it ain't that cool. And care to guess how long it would probably have taken to do this number of simulations 25 years

ago? 750 years. That's actually a pretty good guess. Jerome says that if we would have even had the capability to run these exact simulations this way back then, it would have taken us 500 years to do what we can do in a day 25 years later. So you said 750. That's actually not too far off. Not when you're talking about the age of the Earth in billions of years. And that's why computational approaches are so important, because you can screen much faster and much cheaper than you would otherwise if you were just pipetting things in test tubes, you know, and we do it very, very quickly. And not just quickly, but cost effectively as well. It costs about, say, $20 to screen one chemical in one test tube. So say if you have 200,000 chemicals.

200,000 times 20 bucks equals? $4 million. And that's not including the work hours, which would have taken weeks to months to even years to go through that many chemical compounds manually. I suspect years. Yeah, absolutely. So it's clear that supercomputers are rapidly accelerating the process here. So have they found any results? Well, see, that's where it gets really interesting to me. So out of the 200,000 chemicals, I would have guessed with no scientific background, of course, that maybe 10% or so of those chemicals would be somewhat effective against COVID, but I would have been quite wrong. We found that a few of them, not that very many,

about 125 of them were predicted to be particularly interesting, potentially blocking some of the proteins of the virus to function. We found 100 needles in very large haystacks of chemicals from nature. Did he say 125? Yep. Out of 200,000. Yep. That's less than 1%. I would say that's quite typical, actually. Really? Yeah. Very few needles in this haystack. So what kind of chemical compounds are we talking about here? All different kinds, apparently. A lot of them have been used, sometimes forever almost, to treat some ailments. When I asked for names of them, Jerome didn't even know where to begin.

There's no thing like acetaminophen that everybody has been using forever and suddenly you find, oh, it could work. No, those are things a bit more obscure, but a lot of those compounds have been already described to be used in traditional medicines in the regions they are coming from for things that sometimes have to do with infectious diseases and sometimes have nothing to do with it. So just about anything goes. I guess if they have access to a chemical profile from a natural substance, my guess is they ran it through the machine. And it is worth noting here that from the harvesting to the chemical extraction to the analysis and pretty much everything in between, everything is very precise and scientific. You can't just like go eat the exotic weeds that you have in your backyard and then be cured of all ailments.

The compounds themselves are not dangerous. Like if you touch the plant, you're not going to die. That's good. However, it doesn't mean that you can just go and chew the plant and be COVID-19 free. As a matter of fact, if you put something in your mouth and eat it, if it's a plant, yeah, it can be very toxic. Even if the molecule itself is potent, potency means that it does something to ourselves, you know?

And there is a reason why we drink coffee or smoke cigarettes, which I would not advocate for. Although coffee, yes, I would. Or eat chocolate, you know, because it does something to ourselves. Oh, I'll advocate for the chocolate for sure. Yeah, the chocolate is a must, absolutely. But, you know, those things do go into our brains, into our livers, and they do their job, chemically speaking. And so be careful about what you get into your system.

The same molecules that can save you at a given dose can kill you at another dose. And something being called a natural product doesn't mean it's benevolent. There's a lot of work that needs to be done to make sure that you take it the right way. It can kill you, which is a way to solve your problems, I would say, but probably not the one you want to use. All I could think about throughout this statement is the people who are trying to push essential oils claiming they cure cancer. Normally that would be a joke, but not today.

We have people trying to ingest bleach. Austin emergency room doctors are urging people not to drink bleach. Coronavirus is a virus that is hard to treat and is causing people to resort to desperate measures. They call it high performance computing, but is it really living up to its name? I mean, how much has really changed in the last 15 years? Since the revolutionary jump to cluster computing, there have been new core types, new ways to queue jobs, but no real seismic shift. Until now.

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$2,500 instead of $4 million. And so those molecules, those 125 needles are very, very, very interesting, either because they will be working by themselves. We can take them and maybe they will work in blocking the virus entirely, preventing it from infecting cells. Or, and it is more likely, we will still need to modify them a little bit, but the modifications will be small and affordable and fast to perform, you know, because nature will have provided us the right mold. So we just have to fine tune, so to speak, the chemicals. So it sounds like often the chemical found in a plant turns out to be a starting point.

That's exactly right. In fact, going back to Arthur Barclay from the beginning, discovering that Pacific yew tree in Washington. Once they discovered and developed the drug Taxyl, originally the thought was to keep creating the drug using those natural chemicals that were directly extracted from the plant. In fact, in the early 1980s, during Taxyl's phase two human trials, which is 10 years before the drug actually hit the market,

Taxyl was shown to shrink 30 to 60% of ovarian cancers, which had never been seen before from a drug at the time. That was like a huge deal. But then after doing the math, the National Cancer Institute realized that in order to provide taxol to every ovarian cancer patient, they would need to create 240 pounds of the drug, which meant chopping down 360,000 Pacific yew trees. And that's just to treat ovarian cancer patients. Taxol could also benefit many patients with other cancer types, which would mean

chopping even more trees down. So I think I see where this story is going, but my guess is there weren't enough of those trees to spare. Exactly. So since Pacific yew trees are really only found on the northern west coast of the United States and a little bit on the same coast in Canada, and they only grow an average of eight inches per year, it means that they're likely a few hundred years old. So you couldn't just plant and grow new Pacific ewes for medicinal use, and harvesting them in great numbers could lead to, frankly, their extinction. So they have this dilemma.

Do we keep chopping down trees to save cancer patients until there were no more trees to chop? Or only develop a small amount of the drug and somehow pick and choose who received the treatment. My guess is that those weren't their only two options, but neither one of those is good. Yeah, Ernest, I know you're like way too smart to be like the respondee. I swear, because you're like, I wonder where this is going. Well, when you tell an engineer there are only two options, they're going to come back and say, no, there are many more than that.

And there was. Thankfully, there was this third option. And that was to study the original molecules and then try to create the same drug through a process called semisynthesis. Interesting. So I guess they're trying to bridge that gap and move from pulling these as natural substances to generating a synthetic equivalent. That's exactly what my understanding is, is that semi-synthesis, like you're explaining, is that process where chemists use chemical compounds from the natural source, like the Pacific yew tree, and they use it as a starting point to create a drug. So the result is a drug that can be created synthetically, patterned after the one that is already naturally made. That makes a lot of sense. They literally find something that works in nature and figure out how to create it without nature.

And that's mainly because once they understand the chemical composition, then it's just a matter of recreating that synthetically. And when it came to taxol back in the 80s, that actually turned out to be an incredibly complicated process for this particular chemical compound. And it took 10 years to get from human trials of the taxol created from the natural tree to being able to market semi-synthetic versions of the drug in the early 1990s. So by finding a way to create taxol semi-synthetically, they may have not only saved the lives of cancer patients, but also the Pacific yew trees from extinction. Yep. So in the case of Jerome and the 125 substances with potential, some of those could eventually end up as a semi-synthetic drug or as a natural drug.

The key is that the discovery for both of these drug types originally came from a natural substance like a tree or an animal. Right. And actually, some of the things he mentioned in addition to trees and animals like fungi or algae are things that can be grown quickly and harvested quickly as opposed to a tree or an animal where you start getting into ethical concerns. Yeah. And then, of course, there's the synthetic drug discovery process, which basically means that the lead is discovered in a lab instead of in a natural substance. So pretty much from beginning and end, those kind of drugs are created in a lab. But that can be really hard to do, right? So it's not what Jerome's team is aiming for with this particular research. They have these 125 needles out of a 200,000 chemical compound haystack. And Jerome is now sending those to a lab in Memphis

to do some testing and validation. We have been doing the discovery. We think we found the needles. And now this lab is going to test those needles to verify which ones are real needles and which ones are not. We do not expect all of them to be true positives, to really work. But we would hope that we are going to find maybe 10 or 20% of them. That would be fantastic.

Even one, as a matter of fact. Even two. But if we are statistically very right, maybe 5 to 10% of these 100. So maybe 5 to 10 molecules will actually turn out to be at some level of potency against the virus. So he's hoping that five or ten of these chemicals will work out. Yeah, and it narrows down even more from there. There is a big difference between a substance doing its job in the test tube and the same substance being efficient and potent in the human body.

As a matter of fact, this is one of the reasons why drugs are so complicated and so expensive. It's because most of the things that work really well in the lab, and that's still where we are right now in the lab, most of the pharmaceuticals that are doing really well in the lab will fail. They will be found to not only torpedo the virus proteins, but torpedo pretty much everything they can put their hands on, including our own cells, which is not a good idea either. As a matter of fact, you know, 95% of the molecules that do really well in the lab fail in clinical trials. So most of what you're very excited about in the lab will fail for this very reason, because they are promiscuous

protein, that's their name, because they will not be specific enough against the virus, and they will happily go and bind to a lot of things that you don't want them to touch in your body. So just so I follow, Jerome started out with 200,000 chemicals, which through supercomputing were narrowed down to 125, and out of that five, only five or ten are expected to show real promise. But if ninety five and ninety eight percent of drugs that succeed in the lab fail in the human body, then we're talking about maybe one of these chemicals realistically helping to fight COVID.

Yeah. Isn't that insane? From two hundred thousand to one. That's insane. But that's what needs to happen COVID. Yeah. Isn't that insane? From 200,000 to one. That's insane. But that's what needs to happen here, right? We have to narrow these down as best as we can before we ever get to the human trials, because that's where the real risk happens. Right. And it really does feel like finding this needle in a haystack, especially when you look at it with these kind of numbers. And apparently it's totally normal. Going back to the story of discovering the drug in the Pacific yew tree,

it's interesting to note that from 1960 to 1981, the NCI USDA program that the taxol came from had screened more than 14,000 plant extracts and more than 16,000 extracts from animals. And then in the more than 20 years that they were working on this, out of these 30,000 natural extractions, only Taxol was on the path to actually becoming a drug. Now, a few other natural substance candidates eventually followed, but the process was clearly very slow going. But only in recent years, advances in technology have accelerated the drug discovery process in a major way.

Well, they just hadn't discovered essential oils yet. This approach has been around for a couple of decades, even more in the pharmaceutical industry. What is happening now is that because of the power of supercomputing, we can use it to screen very large databases of chemicals, the kind of scale I was mentioning here, very, very fast times. So what supercomputer did they use? HPE Cray gave Jerome access to the supercomputer called Sentinel, which has about 4,000 cores and computational power of 200 trillion calculations per second or 200 teraflops. It's about if the entire population of Earth was performing 20,000 calculations at the same time. That's pretty amazing to think that this machine can do that many calculations per second. And Jerome says that this kind of compute power is necessary. It takes a lot of computational power to describe all the atoms that would essentially be meeting each other in the

actual test tube in the wet lab, you know, how they may interact with each other, the geometries, how the torpedo is going on the boat, so to speak, and all the forces that act between all these atoms. It's based on a lot of things. And you do have a lot of atoms in the test tube. And so we do need this computational power to perform at this scale. Jerome says he started out screening about 10,000 compounds per day, but eventually got to the point where he can run

a million compounds in a single day by using Sentinel as a delocalized machine by way of Microsoft Azure's cloud. And just to give you an idea, beyond that, the Oak Ridge Summit computer that we mentioned earlier, that is number two on the top 500 list, that computer would have the power to run a billion compounds per day. So compute speed is really not an obstacle these days for research like Jerome's. Now, part of the reason is that everyone is putting resources into it, obviously. When half of the resources of the planet are put on the project, it's like the moon chart. I mean, we are going fast, basically. But it shows a potential

to accelerate by an order of magnitude the drug discovery process. And accelerate it has. Jerome said that not only does supercomputing make science go faster, but it changes the traditional approach to research. Instead of analyzing and explaining what happens in the laboratory, which is already quite difficult and valuable, we are able to predict what will happen in the laboratory. And that has totally changed the way we do research. Yeah, it's been interesting to see how, even in the development of technology, what used to be more of a trial and error process is being driven more by predictive analysis models, where we know much more about where to start. And the way it changes the psyche of the young scientists, you know, I belong to a generation when we had a problem, we had to derive an analytical solution to it. And then we would run the numerical recipes to solve this well-defined analytical solution.

But now instead... Run 100 tests and find the 10 that works, basically, and stop wondering about why it works, but just make it work. And that mindset is one thing that those in high-performance computing and those in the pharmaceutical industry have in common. Fail early, fail cheap. And that's what HP allows us to do, you know, to fail early and to fail cheap and to

fail massively, which doesn't sound great, but it actually is extremely valuable. But Jerome didn't always think that way. The pharmaceutical industry has taught me to accept failure as a PhD and postdoc from quite prestigious places, if I may say so myself. Failure was a personal, horrible thing. And it's my mentor in the pharmaceutical industry. I will remember that forever. Dr. Riyad Sawafda told me, just give it a try. And the liberating aspect of this notion was totally new to me. And indeed has allowed me to succeed.

On the other hand, I understand I'm in Huntsville. That's where the U.S. space exploration program started. You know, NASA started here. Von Braun came here from Germany after World War II. We cannot just send 100 Saturn V on the moon and see which one succeeds and which ones fail. You know, so the nature of the problem has also lent itself to this trial and error acceptance. And it's because we are virtualizing reality. We can, in virtual worlds, afford to fail.

That's absolutely right. And there definitely has been a paradigm shift. When I was coming up in college and undergrad and graduate in the computer science program, you were obviously failing repeatedly as you were learning all this stuff. But once you got into the, let's call it the real world, you often were taking your designs to extreme lengths, trying to deal with corner cases. And that probably wasn't the most efficient way to attack the problem. And now the tech sector has kind of shifted to this fail fast mentality, which is much better, you know, lean operation. Right. And this fail fast mentality is now enabling both science and tech to move very quickly and de-risk what would have been incredibly risky having to do this in labs, on humans, etc. And that's interesting that you say that because I come from the entertainment industry, right? And I've been in the tech industry for about a

year now. And when I first entered the tech industry, the executive who brought me on board looked me in the eye and said, I need people who can fail fast. And that always stuck out in my mind because I had never been in a role where that was the mindset. Yeah, absolutely. You know, so it's so interesting that the way computing has had this ripple effect. I mean, not only changing the speed and the power behind research or even changing the outcome, which obviously it has, but the very way we approach research in general. And Jerome sees more changes for good on the horizon. What we can do now is look at gazillions of different test tubes in a day. What we will be able to do in 5 to 10 years, I think,

instead of looking at test tubes, we'll be looking at organisms who will be able to simulate the answer of you or the answer of me if we are given a drug. As a matter of fact, we treat every cell as the same right now. We know that's not exactly what happens in reality. You may be reacting very well to a pharmaceutical, while that very same pharmaceutical may make me sick or allergic and whatnot. It's the second reason why pharmaceuticals fail in clinical trials is because some of us will live, will benefit, but 5% or 10% of us may have some heart conditions that will prevent us from benefiting from it. So usually so much liability involved that usually the program is canned entirely. And when we can address that, we will be able to not only discover molecules that could do well,

but also red flags, the ones that will very likely totally fail. And then we will solve the 15 years and $2 billion problem of the cost and time it takes to discover a drug. But we're not there yet. Right now, we're very happy at the teraflop and petaflop. We're going to go exascale and zetascale, I would say, and then we can start. But what we can't addressing every individual instead of just addressing every test tube, you know. Right. And Jerome brings up a good point that predictive analysis, AI, a lot of these things are going to be brought to bear in addition to

supercomputing, not just the raw computing power and number crunching, but things like predictive analysis. And it's important to keep funding research like this because it's not just one area that this works on. The more money that's put into just supercomputing in general and AI and predictive analysis, deep neural nets, these impact so many areas of human life. And not only that, it creates a feedback loop where the more money you put into supercomputing, the faster you're able to advance material science, which generates the materials that go into building the next generation of supercomputers. I couldn't agree more. If you needed even an egoistical reason to found this kind of research is because by doing so,

you found yourself. You are investing in your own future. You are investing, as a matter of fact, in building your own reality. We're all in this together. And if this terrible crisis of COVID-19 has taught us something, is that we're all in the same boat. And that seems to be an ongoing theme with all of these interviews that we've been doing about COVID-19. This thing affects all of us. So we have to work together to fight back and win. So yeah, I'd say we've come a long way since bloodletting. We sure have. And Jerome is absolutely right. And specifically with a pandemic, we have to work together because if we don't ensure that a vaccine gets to every human on the planet, this pandemic or this virus will still reside in hotspots and will just re-trigger another pandemic over and over when people travel through these areas. Right?

So we kind of don't have a choice. I don't even know what to say to that. Yeah, it's pretty bad. But hopefully everything will be okay. Yeah, it's like the musicians on the deck of the Titanic. That's so sad. Playing, what was it, a closer walk? I don't know what they were playing.

No, nearer my God to thee. There you go. As it went down. I like to think there's enough lifeboats for everybody. Yeah, unfortunately with 7 billion people, there's not. There are. We're building the lifeboats. Ernest, we're building them with supercomputers! Well, let's hope so. We are all in the same boat, we're all in this together, we find solutions together or we

don't find solutions at all. So if you're wondering what will happen with the 125 compounds from Jerome's study, they're still being studied in the lab as we speak. But you can keep tabs on their progress by going to the episode notes page on bigcompute.org. And there we'll be sure to provide you with all kinds of links and information so that you can keep track of what's going on. And if you want to help us get the word out about the Big Compute podcast, please leave us a five-star review and follow us on any of our social media channels. Yes, tell a friend. Oh, we found out that we are in the top 10% of podcasts globally, which was a nice surprise. But, you know, as a type A personality, now I want to get in the top 5%. Or the top 1%.

Yeah, why limit ourselves, right? This is the era of high performance podcasting. So dumb. And, of course, special thanks to undercover superhero Jerome. I like how you just transition like. Yeah. We're leaving that one to lie on the dirt. And of course, special thanks to our undercover superhero, Jerome Baudry, not just for speaking with us, but for the amazing work he's doing in the fight against COVID-19.

Yes. Who knows? I mean, maybe someday someone we love will be treated with a therapeutic discovered through Jerome's research. It's possible. See you next time. Bye!