 you can see. Perfect. Thank you. Thanks for the organizers. My name is Daniel. I'm from Tanzania created by the St. John's University of Tanzania in Dodom and the National Mandela African Institution of Science and Technology in the Arushia, Tanzania. And my talk that I'm going to share with you is on natural products that are serendipitous or of the SARS-CoV-2 and some insights from more recurrent simulations and meta-dynamics. So coronavirus too and the coronavirus one that occurred some couple of years ago, they share small similarities. And this offers two treatment options. Either to target on the coronavirus itself so we can design some drug or inhibitors that can inhibit the activity of the virus. Or we can inhibit to target on the human immune system and are preventing the viral entry to human serenity. And this is will be the focus of this talk. And so as we can see here that the virus has different structures. And so in order to enter into the human cell, it uses the spike receptor-branding domain which it attaches to the angiotangent converting enzyme to and the experiment, both experiment and theory have really confirmed that there is a strong interaction between the spike of the virus and the acid-2 enzyme in the human which enables the virus to strongly attack and have a strong affinity and hence to enter into the human body. So the motivation is that the case of Tanzania. So many, we are blessed to have a lot of natural products. And one of the plants that were suggested and they have been locally also used and have been claimed to be effective in managing the disease. And one of them is this one here that I showed the Tertradenia Preperia. But we really don't know how this compound works. Either by acting on the foie gras itself or by inhibiting the foie gras to enter into the cell. Daniel, sorry question. What percentage of Tanzanians use this plant? I cannot quantify how many, but a large number of people have been using this plant. In what context? Like in foods, in what? What has been used is what in Swahili we call it kujifukiza, I mean, in herring the vapor vet. Ah, okay, okay. I understand. Okay. Yes, yes, yes. Yeah. But for example, this planted contents is with a peony and essential oil and some flavonoids. But again, we don't know what it works. So initially, the natural. Can I just interrupt? I can ask questions. Yes, yes, yes. Is that plant used after the affection of the, or it is used before the just disease? So before someone get the coronavirus, use this plant or it is used for the treatment? So before it has been used for other diseases. But since the current of the coronavirus, now it has been widely used. So it is before the disease? Yeah, before the disease was also used for other diseases. But since the, yes. Okay. Okay. So it's not for the treatment? Yeah, it's used for treatment. Before it was used to treat other diseases. Okay, okay. Thank you. Yes, yes, yes. So before the natural product group or the invest of the Islam, I've isolated the number of natural products, including this one, I'm showing them to the left panel. And this have been tested the experimental and they've showed 75 low property, but not for the coronavirus. So this was our initial step to, to, to, to evaluate if they could have also coronavirus inhibition, whether targeting on the coronavirus itself or inhibiting the, the virus from entering the cell. So what we did, we, we, we did some molecular dynamics calculation on this and document calculation, of course. And then we did the repurposing. So we did the similarity stage based on the, the best performing, uh, molecules. So in this case, uh, ligand number 15, uh, worked better. And then when we did the similarity stage, we obtained three drugs from, uh, the drug bank. And this, uh, approved the drug for authentication. So interestingly, we were interested to note that this molecule, the diocemin, has been also reported by many computational groups that is, is, is a good content to target coronavirus. And our work initially, we found that these three drugs, they work by two distinct mechanism. One of them is especially the first one here. And this one, they work by, uh, acting on the virus itself and stopping the viral RNA replication. Again, the same, this one here, it works also and it was observed to bind strongly at the interface of the, of the virus, between the human assay and the, the, the, the spike of the virus. So, and this is the major focus now. So the apocrylene, this is the angiotesin convergent is aimed to for, from human. And this is the, the, the spike or the coronavirus and this label that the encaling residues that the, the, the, the, the, the virus uses to attach with the very high affinity. And when it attached, then it can get into the human cell. So we screened some, the natural product from the plant I showed before. There are so some natural product where they've been isolated. And so we did this cleaning, targeting, honoring at the interface and focusing on the interaction, uh, especially with this, uh, residues here at the interface. And this Fravenoid, like for the previous group, this Fravenoid showed the more, uh, low binding energy than the other cluster for the natural product. So this interested us to, to, to evaluate the stability of this Fravenoid and to see the dynamics of weight. So at first, we want to just to look at the, the, the ligand, uh, RMST and the distance RMST. So the distance RMST provided, uh, whether the ligand is remaining at the docking pose or is it changing? So we can see just after a few nanoseconds, it changed from what is a initial pose, then going to another pose and where it expended some fluctuations and then, uh, came back to its original, uh, to the second pose that it changed. So this motivated us to investigate the distance between the natural product and with some, uh, residues, the anchoring residues to see whether it's really changing and all it is coming back. And of this, we, we performed it to a hundred nanoseconds. Uh, so you can see here that for example, tyrosine, this one, 505 and the ligand and another residue from the acid to enzyme, both, they showed that delays changes in, in, in, in the ligand from the initial pose. So the initial pose, as I showed before, is this one here, which is shown a, uh, lower binding energy, but after some time it is expended, it is changing and moving from the original pose. And after 50 nanoseconds, it has been changed and it is really having more. I think there are questions. Mariam, if you have questions, please ask. Hi, it was previously in your talk that you mentioned, uh, plant in Tanzania. I wanted to know, sorry, it's not related to this slide, but the previous, like the beginning of your slides, but I wanted to know if, uh, this plant has shown to be effective in other human populations, like the ones that are genetically distant from Tanzanians, like Europeans or us Middle Easterns. Uh, for other populations outside Tanzania, I don't have any data or information. Probably it has been also used, but I don't have more information about other population outside of Tanzania. You go for as well. Yeah. Thank you. And then we found that the strong affinity between the violas and the, and the, the, the acid to enzyme probably could be one of the reasons that it pushes this. Yes. Yes. So these are plain molecular dynamics simulation. Yes. Not enhance something, something. Okay. So, uh, what are the starting configuration of the molecule where you started in your simulation box, uh, the ligand? Yeah. So, so we, we, we obtained the, the, the, the initial from the docking pause, the one that showed the lower binding image. No, no, it means initially this, uh, ligand is already near the is part or it was in the uh, medium and then diffuse into, uh, so initially we, we just obtain the protein structure from the data bank without the ligand. Okay. So we have the ligand at the interface. Okay. So you put the, we, we, we did the, uh, uh, docking to bring the, the ligand to assess the affinity of the ligand at the interface. Okay. Okay. Thanks. Thank you. So then we, we, we wanted them to, to, to, to assess that if this ligand is binding at the interface, to what extent does it, to disrupt the recognition of this is hot spotless use. So we focus only on two, uh, on four hot spotless use between the, the, the virus and the, the humanity. So in this case, for example, the upper here, so we measure the distance of the virus and the, the humanity as the enzyme in particular now this distance here I'm highlighting. And this is the distance, which really shows that, you know, the, it's within a full angostrum. And again, we focus on other distance. Say that he stood in and the, the loss in this 453. And again, we see that there is a two maximas, but one populating here at the nearly three angostrum and the one, which is nearly 0.4 or 4.5 angostrum. But within the limitation of the sampling, so we, we, we wanted to ascertain to get more information from maybe some free energy calculation and from enhanced sampling, a calculation like metadynamics. So before we go to that one, then we did a end point free energy calculation. So in this case, we do the molecular mechanics poison, uh, Boltzmann surface here and the linear interaction in it. And from the molecular mechanics poison, Boltzmann surface area, we do the energy contribution because our interest is to understand to what extent does this say, let's use the contributed to the interaction and also, uh, to, to critically disrupting the recognition. So as we can see here, of course, this, uh, let's use the one, uh, he stayed in 34 and adult that are responsible for that recognition. And this, let's use the highly contributing to the inhibition. And these are from the, uh, the enzyme, human enzyme as two and from the receptor binding domain of the virus. Of course, this is tyrosine five zero five highly a contributing to the C inhibition, the bind to the regent and another decent. So to supplement this one, we did the, uh, really interaction in the energy of which of the binding in the energy cause we do to independent simulation for a ligand when it is bound and when it is a free in sort of fashion and the binding free energy was really similar to that obtained from the MMPBC a. So we then we're interested to, to understand the influence of water, the dynamic of water, uh, to the protein ligand and at the protein protein interface, how this water, which is present, he is really mediating the interaction and what the extent. So we initially, uh, started by just the quantifying the amount of water at different residues. So in this case, with this, he is stating that for rising three, five, three and terracing, uh, four, uh, 53. And then we, we, we present here the larger distribution function. And then we are calculating the, the, the, the, the, uh, the less than time for this water to see what, what is a little moving for, for very fast or mainly within this race used for a long time. So this calculation is still of course going on. And then now, yes, yes, yes. Okay. And then yes, yes. Okay. Can I go on? Yes, yes. I said only two minutes left. Thank you. I'm about to finish. Thank you. So then we want to get some insight from metadynamic simulation. So in this case, we select some different set of corrective variables to help us, uh, understand what is happening. So we, we use a distance, uh, between the, the less used, uh, and also we use the, the, the contact and also we, we, we, we, we choose to understand the separation distance of the two protein in the presence of the, of the ligand. So as an example, uh, in this figure B here, we showed that when there is no ligand in between at the interface, the minimum, uh, free energy is about, uh, 0.5. And when there is a presence of a ligand and then the distance of this residue changes to, uh, to, to, to one, uh, uh, to one nanometer, which is given some insight that this ligand is able to, to, to beat changing the, the interaction and the recognition of, of, of this enzyme. And then we're interested in, in, in understanding the, the residence time of this drug because residence time has been reported to, to relate to in vivo bioactivity. So in this case, we have not calculated, but we're going to, to, to, to look and to get some insight of how, uh, time, what time does it spend at this site? But what we have observed in relation to the two figures here is that when the distance at one, this ligand is still having some affinity with the acid two ends, uh, uh, the ligand having this affinity with DC. And there are four disrupting DC interaction business use. And therefore this becomes more weak. And hence it does not bind stronger. And the NC changes, uh, I mean the binding of, the binding of the protein became, distance became large. So as an example here, we wanted to understand the first unbinding process of, of the ligand. So here I just truncate the, the, the, the, when the drug then is coming for the second to the original, to the native complex or to the binding state. And so from here then we are going to, to, to calculate the first residence time as, as normally we do, for example, for infrequent, the meta dynamic. And then DC, a snapshot here, we are trying to monitor the unbinding pathway. It seems that as we observed for the MMPBC, a free energy calculation, this ligand, it unbind toward the direction of DC, a, a rescue, which is from the virus. And because initially it was here at the interface. And after some time, which is in this region, then it's going through this way. And here it has completely moved from this position and it's going to DC position. So these are some inside that we are, we have obtained, but we're still going on and doing DC, DC kind of calculation. So I thank you, everybody. Thank you. Thank you very much, Daniel, for your talk. So we have time for questions. Daniel, thanks for, thanks for your talk. So I had a, maybe just to be a bit provocative. You know, if you were to use chloroquine instead of your, your natural product, would, would use, what do you expect to see? Do you think it'll be any different? Chloroquine has been noted to work on the virus itself. And so I have not seen a report about the binding at the interface and for serient inhibition. So maybe there could be something different. But the experiment and the, some theoretic calculation, I would say the tweak on the virus. I see. Okay. Thank you, Daniel. Can you go to slide nine? Yes, yes. Thank you. Okay. Yeah. Yes. I just wanted to know what kind of energy is this flat showing? Can you just explain a bit more about it? Yes. Yeah. This is the decomposition energy of individual residues to how much is, is it contributing to the interaction of between the protein and the natural product. So in order to obtain this first we calculate the, the, the, the, the MMPBCA. And then in order to get inside, further insight on what is happening to each residues, we can decompose and see how each residues is, is contributing to this one. Okay. Thank you very much. Thank you. Yeah. Thank you very much. Okay. Any more questions? Yeah. I have another question, actually. So, which is related to this. Could you go back to that slide, Daniel? So if I understand this last table, what you're saying is that let me see. So the sign, so if I was to compare the van der Waals versus electrostatic contributions, the electrostatic contribution is repulsive. No, no. The electrostatic is attractive and the van der Waals is repulsive. Yeah. That's correct. Is that correct? But, but there's a, there's a, there's a much bigger change in the, in the contribution of the van der Waals than the, than the electrostatics. Yeah. And I mean, I would, so I would tread with a bit of caution because of course these are all with the pairwise potentials and the van der Waals interaction is. Yeah. It's, it's the Leonard Jones potential, basically. Which, yeah. Okay. So it's, I would, you know, I would be cautious. I'll be just be careful about interpreting it. Good. Thank you. Okay. Thank you. Sorry, one question from Ali Hassanari. Why are you saying that the large number of van der Waals energy is something he has to be careful about? What's the reason for that? So, so the two, well, two reasons. One is this is a, it's a, it's a pair potential, this force field, this force field that is using. And, you know, so it, first it ignores any electronic, many body van der Waals contributions. Number one. Number two, the, the total interaction in a force field is, the physical quantity is the sum of the van der Waals and the electrostatics. So you can have a very bad van der Waals that interacts with the sum of the electrostatics to give you something physical. So you have to be very careful about what it, what did the individual contribution means in the van der Waals. Right. Thank you. Thank you. Any more question? No? Okay. Okay. Let's thank our last speaker and