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Okay. Can you just start by telling me your name and your position here?

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My name is Fernanda Duarte, and I'm an associate professor at the university at the Department of Chemistry.

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Okay. And just tell me a little bit about your background,

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starting from how you first got interested in chemistry and what you've done between then and to where you are now.

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Where has been a long, a long journey? I am from Chile.

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So I first came to the UK in 2015 Assad postdoctoral researcher,

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and then I started to build my career first in Oxford, then in Edinburgh, and now back as an academic since 2018.

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And what got you interested in chemistry in the first place? I was mostly the the General Hospital when I was looking for a career in science.

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I wanted to do something that would have mathematics, chemistry, physics, a bit of everything.

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And I found that chemistry was combining quite a bit of that.

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And I'm from till I saw mining was also very important.

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So I thought that it would be a good combination. I never went into that area.

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I started to move into computational modelling, but that was a different operation.

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So tell me more about how you use computers in chemistry.

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What how does it complement the work that goes on in the laboratory?

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What we try to do is see what we cannot see in the laboratory.

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Sometimes we can use microscopes in biology, for example, to start to look at the fine details.

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But even with those one experimentally, we cannot do that.

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So computational give us the alternative to to use them as a big and maybe cheaper microscope to explore things that would be impossible to do.

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Experimental. You can it can you give me an example of something that you've worked on in the past?

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Oh, we have been working in a couple of enzymes. So enzymes are a very big, big molecule in our body that enable us to live.

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Many of them enable us to to build energy through the consumption of our food into energy or do all that type of transformation.

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And they contain thousands of atoms, which we cannot see very easily,

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not at our naked eyes and with computers were able to model them and we start to see them on time,

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how they move, how they interact with other molecules and so on.

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So really having a movie of those molecules that will not be able to see otherwise.

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And is this all done with mathematics or can you actually are you using visual representations of the molecules?

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When we start building the models, we use a first visual representations,

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but then when we start to see how they evolve in time, we actually use approaches that come from physics, classical physics.

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So we, we try to use Newton equations, actually very old equation just to see how those particles are propagated and evolving on time.

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So you're looking at forces and and forces on notice how they propagate on time.

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But in some cases, some are even more interesting because they can break and form bonds.

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And in those cases we have to use quantum mechanics. So a bit more complicated equations are the classical one because we can see how things move,

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but also we can see electrons, how electrons are affected.

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And those are the ones involved in balance, art form and broken out there.

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Mm hmm. And do computational chemists typically collaborate with chemists who are working in the

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laboratory so that you you've got a to and fro going on between what you're creating,

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which is presumably essentially it's a it's a as you say, it's a model, it's a theoretical approach.

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And you want to test that somehow. Yeah, I feel that we are kind of at the interface of the areas because there are theoreticians in our

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field that they are developing the theory behind very much focus on the fundamental aspects,

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not maybe on the applications. And actually we are using those techniques into it, making them applicable to to real system of interest.

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So we collaborate very closely with experimentalists in looking at applications,

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but also with theoreticians sometimes trying to learn the methodology and how we can push it not only to to leave that fundamental and small system,

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but also to push them to be use into a wider range of chemical reactions.

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Mm hmm. And what's the goal? What what are you hoping to find out ultimately from these studies?

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Fundamentally,

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sometimes the kind of the internal and the only motivation is really understand how in nature chemical reactions happen because they are so amazing,

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so fundamental to to what we are as humans, but then from they have an impact.

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So sometimes fundamentally understanding this is a motivation,

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the like solving the puzzle sometime but also they have an important a applications

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in developing new catalyst to generate a safer or maybe more ecological classic.

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Or in our case we have been focusing on enzymes where we. Interested in helping to develop new drugs.

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Because if you understand how the system work, then we can find ways to to block in cases,

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doses and work in the poor way or making that improvement to the the machinery that we know.

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And is there a particular area of medical importance that you're interested in, or is it a more broad based in our group,

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we have three branches or one of them is more fundamental looking to the methodologies that we use.

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The other one is a which is related to the COVID research we have done is looking at enzyme modelling.

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So we look at enzyme processes started in which the enzymes are involved, metal ions.

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That has been our interest because they are difficult to model.

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So our interest has been they are so important in, in biology for a, for blocking some signals, for example,

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related to cancer or to time my disease and so and people that try to avoid them because they are difficult to model.

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So this has been one way what makes them difficult to model because sometimes metals are a

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in the periodic tables metal occupies the special place that gives them some properties.

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Saw the way that the electron structure of the system is compounds means that they have many different configurations.

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Electron can be in many different places, and sometimes that make them difficult is difficult to model with classical approaches.

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So you have to go to quantum approaches, other means that they are more expensive and more difficult to implement.

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So sometimes people try to leave them at the side.

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So we have been interested in that from a just because they are so important and prevalent.

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So almost a third of enzymes would be M or proteins compared to having a metal.

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So that has been the motivation on those areas.

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But very many of them are involved in signal processes that will trigger cancer in some cases or some other diseases.

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And so you mentioned in passing that one of your areas of research was on COVID.

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Can you remember where you were when you first heard that there was something going on in

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Wuhan and that it looked as if it could be something that might affect the whole world?

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I remember I attended a conference in competition globally in Bristol.

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That was in March. I had heard before, like since February, we were receiving news about what was happening in China.

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We have students in our group who have family there, so we were well aware of the situation.

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But I remember the conference started on Sunday and and suddenly finish on Wednesday.

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One day pandemic was declared. So just from Sunday to Tuesday we realise how quickly the situation was evolving, how dangerous everything was.

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So we started on Sunday coming through. How difficult was travelling for those coming from abroad?

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And then on Wednesday everyone say, okay, we will finish now and early today.

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And everyone tried to go home as fast as possible. Okay.

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So that that and they're coming back on Wednesday they declared that they pandemica.

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And how did you you and your colleagues decide that this was something that was

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relevant to your research and that you could actually make a difference there?

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A bit earlier we started we have been interacting since I came to talks for in 2018.

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I have been interacting with a group of Professor Chris Schofield who has been doing

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experimental work for many decades in antibiotic resistance and other type of enzymes.

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An also with people in statistics some biochemistry.

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It just when they came I started to meet people and those working in protein

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modelling and some related areas because that is something that I was interested in.

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So was never related to the virus enzymes or anything was mostly the interest modelling and biomolecular modelling.

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And then when the COVID pandemic started it, we started discussions about a everyone was sent home very quickly,

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tried to do what you can at home, but then we started discussions about what we can do.

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We have so many good people, excellent researchers,

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and we felt that we were not doing much and that it was a tricky situation

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because we have to move projects and start work is something that is not funded,

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maybe not deliver in in other areas.

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And but it we felt that it was something that if you were not taking that risk out for, then who will be taking that that risk in the UK, for example?

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And what did you decide to focus on specifically?

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We focus on an enzyme called it's a main protease enzyme, one of the many enzymes involved in the replication of the virus.

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So this is an enzyme that the virus has within.

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I mean, it's making the protein. Yeah. Rather it's directing cells to make that protein.

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Yeah. So antibiotic comes into our body, taking over our machinery and then using that machinery to replicate.

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And the first things that are viruses doing is replicating. That's a long, very, very long time.

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It's like when you look at pasta, for example, a very long way, and then this enzyme is the very first one of that chain.

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And what he's doing is acting as a Caesar. So first would cut itself from that long chain and then start small making small pieces.

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So this very long chain that is not very functional,

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it starts to fall into small pieces and then form the proteins that are necessary for replication.

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So if we could block that first seesaw that is cutting everything else,

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we can block really there replication process and we say to target that enzyme because this is something that people have experienced before.

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It's related to other enzymes, not from virus, but the activity and the chemistry that is doing.

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And we felt that it was something that we knew from all other systems that we have been working before.

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Does it have a metal in it? No. But then, you know, then we we found that it was in that sense, always when we started working with systems,

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they feel easier than the ones that we have been working before.

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The chemistry is well known. It's chemistry that we teach our first year students.

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But but it was a and we did know quite a lot of of of the what will happen because the first

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a COVID it is a SARS-CoV-2 one that appears in many years before has some similarities.

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Right. So we realised that there was quite a lot of research, many papers that were not very well cited and they contain quite important information.

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So looking at those old papers out there was very important to get this started.

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Mm hmm. And so what what were you looking for?

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You were looking for molecules that would interact with this mpro the main protein?

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Yes, there were two branches. One very fundamental looking at how this enzyme is interacting with its substrate,

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because first has to cut itself and then interact with the different pieces of of these fronts.

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So it's recognised in a specific area so it doesn't cut randomly are then cut 12 different, 11 different sides.

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But it it was not cutting randomly, it was cutting this specific area.

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So we wanted to know how selective was for each of them.

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So we started to develop models. We didn't have this whole chain completely was very difficult to model.

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So we developed 11 different models of these eight enzymes that would they were sharp peptides,

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but they will mimic the the real sequence that they would be recognised.

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So the first question was how is this enzyme recognising those sequences and this recombination them in a more selective manner.

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So are they once more reactive may be is because it's recognising them better.

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And why? Because if you we can understand this recognition pattern, we can design new inhibitors that will mimic those interactions.

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And on the other hand, our other side of the group was looking at molecules as small molecules that were already

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available and see if it was interaction with much the once that we would find it.

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So can we use what we have already are able to identify some a small a molecule.

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And was that the part that Henry was working on? So we've got Henry Chan here with us as well.

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Yeah. Yeah. So here, Henry, about that in a moment. Yeah, yeah, yeah.

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But so, so. And how successful were you at understanding better this interaction between the protease and the sites where it cuts?

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Yeah, we see as always, we feel that we have many more questions than we had initially.

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We did identify key interactions that are important for this recognition to take place.

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This is a very long chain. So we realised that one side of the enzyme is a has a very conserved interactions,

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while others will say maybe are more promiscuous, they are much more flexible and we're able to do a different type of a mutation,

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computationally testing, many different bases and in that way identify peptide sequences that will inhibit actually their reaction.

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And those were tested in the experimentally here in action as well.

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And so was very nice to see that we were able to understand part of the machinery and then

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also identify the key interactions that we could exploit to identify new inhibitors.

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And those have been tested experimentally and that's after that because initially the lab workers will have to go home, presumably.

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Yeah, was very, very limited. So here people was able to do some work, but still a progress was.

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This low, but we are very lucky that we're allowed to continue some experimental work.

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But because I'm bringing consumables from abroad and everything was lower than that than in normal times.

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Mm hmm. Yeah. And and where.

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Where are you now with this. With this research work? Is it continuing or did it meet you?

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Yeah. No, we're still working on maybe here we can comment more on that it later.

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But we have continue working this enzyme and probe what we want to understand a bit more the

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mechanism because people have a study and publish their mechanism for a small molecule.

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So some of the A it might have been published but not a real full sequence peptide.

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So we like to explore that in more detail and also are exploring another enzyme related to and which we that we feel we can start to target.

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Both of them identify using the same protocol, identify the interactions first and from that analysis, then develop new inhibitors.

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That is our focus now that this is another COVID enzyme. Yeah, that has been another sore arm since that.

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And this project has completely shifted our original idea to project police.

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It's now gone because we have many more questions in those two different enzymes and we would like to answer.

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And also because those virus enzymes are maybe important for COVID, but they, they may be relevant for for for other type of of viruses.

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In the long term, the machinery is not too different to other things that we have seen.

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Mm hmm. And I mean, your goal part of your goal is drug discovery is how far off is that?

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Have you had any commercial interactions with this work?

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No, I think that we are very new in this area because we we need to show to look at very fundamental questions in this area.

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And through the interaction with our colleagues, we will realise how important asking this fundamental question was to these drug

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discovery efforts so as to be very encouraging and motivating to learn about this area,

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also to realise that it's also very difficult to develop a drug so many people say will develop a drug,

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but something that is active in the laboratory and that it become active actually with a real drug involve a very, very long path.

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If we can contribute, especially in these early stages, is something that really motivates us.

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So I think that we we really want to explore farther this area, but also aim being aware that the path is is long and is complex.

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We're answering one part of the question and there are many experts that we have to work with a to to answer the other ones.

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Mm hmm. And you mentioned early on that funding was uncertain that you were going to have to switch from your existing projects to this one,

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that where you were able to get funding to to pursue the work that you do right now.

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For example, we were very lucky that through the university we were able to continue work here.

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So Experimentalist, who were the ones that needed the most,

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were able also to secure some funding to run calculations in the national computer facility.

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So there were some calls, priority calls for people working in particular in COVID research.

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So that was very helpful. And that was that UK or UK.

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Right. Yeah. And also through the funding, for example, that Henri is receiving, has, well,

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having the flexibility to still carry out research in different area, different to the one that we originally have.

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But it recognising that was also very important. So having that flexibility also coming from EPA in those areas, it was a very, very useful.

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Mm hmm. So so tell me a little bit about how shocking it was for you to to have to change the way you worked and coming back to it,

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coming to you personally, really how your response was to coping with with the virus.

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Yeah, but I mean, were you were afraid and we were afraid of actually becoming infected.

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Yeah, it was it was very difficult because people from a we work with computer, so many people say you can just go home and do your work safely.

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But there were some challenges because as a student, sometimes as a postdoc, I have been a puzzle because here too, you have different spaces.

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Sometimes sharing places with people and being able to work initially was very scary to be abroad, to be far from home.

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So if something happened, I would not be able to travel. So that was very scary.

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But at some point you realise that things have to keep going and you leave the group and you have to continue working with them.

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So paying attention to some hospital was very stressful because each person was expressing

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different a situation that sometimes at home was was not the best option for them.

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So they remember really, really sad not only for experimentalist but also for computational people.

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Coming to the lab in a safe environment was important. So we started to open early on with the rest.

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Implementing the university, sometimes people sitting very far away in an office,

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but having this space that was different to maybe a crowded home sometimes or or maybe giving you some freedom to stop,

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think about what is happening back home and maybe try to focus on some of what I saw was a distraction.

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And I felt that that was very useful to have the support from from the apartment that initially thought, okay, you don't have any problem,

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you don't need to come back at all to realise and that sometimes mental health is

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also related to to feel that you're doing work that you feel accomplished and doing,

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I guess. Yeah, that's something I was going to ask him.

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Did the fact that you were able to to do important work on the virus itself helped to support your own well-being, do you think?

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Yeah, and I think that was mostly the interaction with with the colleagues so many times.

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We'll spend the first 510 minutes just discussing how things happened this week and sometimes a bit long if someone was ill.

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So you feel this personal connection with people that was discussing science.

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We were meeting every Wednesday online to discuss science,

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but also was to a topic or we used to meet at five or 6 p.m., so because was easier for everyone to coordinate.

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But it was not something that I follow a half hour late meeting, not at all was a bit of a distraction also to interact with colleagues in a much

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more friendly environment and also do some science that we were very moderate.

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Mm hmm. And. Yes.

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Oh, yes. Do you think you worked longer hours than normal?

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I initially when I was working at home, I didn't feel I felt that there was a lot of flexibility.

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I could take breaks in between and go to the park. But later I did feel quite higher.

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So for that, when I came back and things were starting to go back to normal.

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I did realise what happened during that period and I did feel tired instead of

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like maybe not only physically but instead of ideas or how things will be going.

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So it was a realisation maybe after.

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And then you start to think actually yes, I was working more hours but initially didn't feel was quite flexible, but then three months was okay.

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But then when we went to six months and maybe the worst case for us as a group was also when things were getting better.

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And then we went back to to lockdown in December, very close to Christmas.

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That was a very deep point for everyone, fully realising all the time that we have been working long hours,

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maybe that you were just there, that you wanted to go home.

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I think that that was a very difficult period for everyone. And I mean,

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you mentioned earlier on that your work has always been somewhat collaborative because it's very

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multidisciplinary and you need to interact with with people who are doing practical chemistry.

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But do you think this particular project was more collaborative than what you've been used to, and how did you feel?

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Oh yeah, yeah, definitely. Some of the meetings that we have were just for someone presenting the methodology that they were using,

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because sometimes we would just not understanding the language. It was so different.

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Some people would come, even some of the politicians, but not able to understand each other or the experiment that people are doing.

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So we're able to us very, very basic questions. And many of the meetings were based on that.

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Someone will come in today and present the methodology and explain the details.

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And that is something that was very new to me. So I have never worked.

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We were. Yeah. And more than 25 people working in this project and just learning the language to where all can be specific, what can be surfaces is.

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So we followed our yeah, we knew the language very well but it still was a learning process before starting to do some work.

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Do you think there's a lesson from that, that normally your you'd be slightly afraid to admit that you need to have a bit more of an explanation of

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something and maybe everyone should think more in the future about having that kind of open discussion.

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Yeah, definitely. And I think there was more knowledge about other things that you can do,

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how you can complement your research and how you can push it that a bit further

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maybe what doing a fundamental analysis and then what person would say,

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actually, I know someone that we we can really test this on how we can test or sometimes we're

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having problems with our computer someone else will offer help also for with that.

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So was the aspect of improving the science that we were doing but also feeling motivated that you were part of a team group.

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So we are still interacting now. We meet every other week or again every week, but we're still aiming to continue work together.

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Oh, that's interesting. So you're taking it forward. I mean, still working on COVID or on other problems as well?

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That has been COVID.

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And hopefully we can find funding to continue in some of the water we're interested in doing in general in biomolecular modelling.

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But the bridging data aspect of the fundamental modelling and drug discovery.

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Mm hmm. Mm hmm. So just looking forward,

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has do you think the experience of working on this problem and working in this collaborative way has changed your attitude to your work?

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And how would you like to see it moving forward in the future?

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Seems like our has it from from the side in the aspect has been a being very useful to realise how complex a process that you work at on our bodies.

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It's okay to go and ask questions to other people. So sometimes I feel like I am not an expert on that.

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But yeah, well we can find someone that is an expert and we work together.

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So I think that gave me the motivation and maybe the confidence to just go and ask someone if that is the case and more from the personal aspect,

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maybe leading a group, realising how important are they the human interaction to the science.

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Because if you those were affected, we saw that in the science of how people was developing.

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So we take from granted to many of those interactions that we had before and now hopefully trying to appreciate those those more.

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Great.