Unlocking the Promise of Protein Degraders: Molecular Glues, PROTACs, and the Path Forward

0:08
Good afternoon and welcome to today's thought leadership webinar, Unlocking the Promise of protein degraders, molecular glues, protax and the Path Forward.

0:16
My name is Rachel and I'm delighted to guide you through today's session.

0:20
We are honoured to be joined by our featured thought leader, Stefan Schieser, who is the Director of Medicinal Chemistry at AstraZeneca, as well as a wonderful panel of experts who we will introduce later on.

0:33
Stefan, thank you so much for joining us today.

0:36
We'll start with your short presentation and then we'll go to the panel discussion.

0:39
So Stefan, over to you.

0:42
Yeah, thanks a lot, Rachel, and thanks a lot for the the invite.

0:46
I will start sharing the screen.

1:02
Presentations coming through.

1:03
Yeah, great.

1:07
That's perfect.

1:11
Thank you actually for the introduction.

1:12
I'm very excited to be sharing the sessions about Protex and molecular gluten degraders, which is I think truly a very innovative and very important field for small molecule tract discovery.

1:23
So I would like to start with reflecting a little bit why is actually it is required that we have new and innovative phase in targeting diseases with small molecules.

1:33
And I am a strong believer that at the moment, the way we have discovered trucks in the last, let's say decades, that we have mainly worked with small molecules to either inhibit or sometimes or to activate our target proteins.

1:46
But this is not sufficient in the future anymore.

1:49
And I would like to show a couple of examples why I think this way.

1:52
So what I have plotted here on the left side is the projected sales for assets in 2025 across the pharma industry.

2:00
Where I would like to point your attention to is actually the modelatical and where you can see that under the top forecasted highest sales trucks on the market, actually only two of them are derived from some molecules.

2:13
There's a lot about antibodies and also peptides.

2:16
And this is surprising because FDA approves roughly at least 650 to 60% of some molecules every year.

2:22
So it's quite a bunch of some molecules which are approved.

2:25
But if you then look into this high pricing segment, actually it's a lot about antibodies, peptides and so on.

2:31
And also when you follow a little bit the pharma news, there's a lot of bass around T cell therapies.

2:36
T cell engages sometimes oligonucleotides.

2:40
So one could get a bit impression that some molecules are a little bit dusted if you want to say it in a drastic way.

2:45
So I think there's something we need to do in this molecule field to really get this one molecules up into the centre of the focus.

2:51
Again.

2:53
Another area which I believe is 7 impacting how we do in truck discover in pharma is the geopolitical situation at the moment.

2:59
So there's a lot of discussion around truck pricing.

3:04
And what I see a bit more is also discussion around first in class versus best in class that I see it's tipping more towards first in class targets.

3:12
So we also need to now think of how can we now engage novel targets with some molecules.

3:18
And it's actually, I believe a challenge because of the around 3000 proteins, which are associated with diseases, only around 700 of them are termed to be druggable.

3:28
So the vast majority of proteins we cannot address.

3:31
So far it's in the traditional way.

3:33
We have done it into the last decades.

3:36
Now I would like to spend a little bit of more time on this.

3:38
OK, why is actually a protein untrugable and why could a PROTAC or molecular flu degrader really help to unleash more targets in this space?

3:48
So there there are a couple of reasons why I believe proteins could be untrackable.

3:53
The most straightforward reason could be that there's not a binding pocket for us a molecule at the at the protein.

3:59
But I think it's not only a pocket which is required, but the pocket also needs to have certain features and what I call in a suitable pocket and what you can see on the left side.

4:07
So what I mean if a suitable pocket means is that the pocket really goes into the protein, that the small molecule can go in and make a couple of interactions, but it also needs to have balanced first Cam property.

4:18
So the pocket should not be too polar and it should not be too lipophilic that we can then design as a molecule which has a balanced first Cam property profile.

4:27
On the right hand side, you can see what I would deem a more challenging pocket.

4:30
So you can see that's not really a pocket, it's more on the surface of the protein and it's also quite polar region, which means also the small molecule building be quite polar, which could then give issues for example in absorption in the gut or cell permeability.

4:45
Another reason why why why a protein could be team termed undruggable is that it has a very nice pocket where we can devise a small molecule binder to it, but the pocket is actually not functionable.

4:55
So it's small molecule binds there, but nothing happens.

4:58
Or it can also be, for example, it is an intrinsic ligand in the cells which then has a very high affinity towards a very nice pocket that we have a very hard time to get the affinity of this small molecule high enough that we can actually displace this high affinity intrinsic ligand.

5:15
Other areas where I where I believe it could be tricky for us small molecules is that let's say there is a nice pocket, but this pocket is not only present in the target you would like to modulate, but it's also present in a target which you really don't want to hit.

5:29
That is very hard.

5:29
And for a small molecule is medicinal chemist to find selectivity against desired on target effect and undesired off target effects.

5:38
It can also be that it's a very nice protein, very nice truckable pocket, but it's just too essential for the cell that we would only like to hit it in deceased tissue or in in in diseased cells, but not in healthy cells.

5:51
But then as more molecule again has a hard time to re differentiate between healthy and diseased cells or it could be that it's not only about activation or inhibition of the protein of interest, but we have to do some other biology in order to treat the symptoms of the of the patients.

6:07
So you can see that quite a number of areas why a classical small molecule inhibitor approach could be challenging.

6:13
And now in the next couple of minutes, I would like to share a bit with you why I believe that the Protac could solve at least some of those challenges for small molecule drug discovery.

6:22
So what are actually Protacs?

6:24
So Protex leverage let's say the degradation machinery in our cells.

6:29
So when our cell decides that a certain protein which is shown here in blue is not needed anymore, it binds to the green protein which is the E3 ligase.

6:37
Then the whole complex of protein is put, proteins is put together and at the end there's a so-called E2 which then puts the ubiquitin on the protein and this mono ubiquitin is then chain is then growing so poorly ubiquitin chains.

6:51
And this is then a signal for degradation of the cells.

6:54
So the cell looks around for proteins which I have this poorly ubiquitin chain and then they go to the protease and they are degraded.

7:01
So what now protags are doing is they are bringing together the blue protein and the green E3 ligase even though they would under physiological conditions not bind to each other.

7:11
So they link them, which means the protag is consisting of three different parts.

7:15
It's one part which is binding in blue to the protein of interest or PUI.

7:22
Then you have an E free ligase ligand which binds to the green part to the E free ligase and you have a linker in between and then it forces the E free ligase to your protein of interest.

7:31
And if you do it in the right way, it triggers the ubiquitulation of support of interest and then the degradation.

7:38
What you can see on the left side, this is roughly how or how proteins, how Protex look.

7:43
So I said they have those three parts.

7:45
The green part is the POI ligand which binds for example, the androgen receptor or the BTK.

7:51
The orange part is the linker.

7:52
And what you can see in blue is 1 typically if you like it, which is a cerebrum based, if you like it, which many of the Protex in the clinic have.

8:02
So why is now this really a step forward compared with no molecule inhibition?

8:06
One of the big advantages is the protags, they actually don't need a functional pocket.

8:10
So the only thing what the protag needs to do is he needs to bring the protein of interest in close proximity to the if we ligase any pocket there, you can find us.

8:19
A molecule binder would do it in principle.

8:22
So it does need to be a functional pocket.

8:23
So we can also address now proteins which don't have a functional pocket.

8:28
I said that sometimes in biology it's not about inhibition, activation of the protein of interest.

8:33
So there are many proteins which also have, for example, a scaffolding function.

8:37
So there are some kinases out there that's described.

8:39
It's not only a kinase but also a scaffold where other proteins can bind.

8:43
So a protag then removes also the scaffold, scaffolding function, for example, of proteins.

8:47
So you can now address also proteins which also only have a scaffolding function or for example enzymes.

8:53
And you take both functions out of the game, enzymatic function and the scaffolding function, which has a promise to increase the efficacy.

9:02
And another area which I think is very exciting is it could be another layer of selectivity.

9:06
So a set of some molecules, it's sometimes very tricky to differentiate the on target desired and the undecided off target.

9:13
If the small molecule binding site is very similar as you have seen on the previous slide, degradation is much more complicated.

9:19
So this whole ternary complex needs to form and then you need to have a lysine at the right position where then the E2 can transfer the ubiquitin on.

9:27
So let's say if you have two proteins, which is a very, very similar binding site, but the Turner complex looks complex, looks different, and in one case you have a lysine and in the other case you don't have a lysine, you could still get selectivity that you degrade only one of those proteins and not the other.

9:43
So this can give another layer of selectivity if the two binding sites are very similar.

9:51
So I think around 10 years ago, there was really what some people explained like a gold rush in the Protex age.

9:57
So many pharma companies and also biotech companies, we looked into Protex and I did a quick calculation around more than 40 Protex are currently in clinical trials.

10:08
So the majority of them of course, in phase one because it's still a rather new field, but exciting to see that also a couple of them are already in phase three.

10:16
So that hopefully that in a couple of years times we have the first clinically approved Protex if everything goes smooth.

10:23
When you have a look in the indication space, I think there's not much surprise that many of the innovation actually always starts in oncology.

10:30
But you can see that also there are some assets now which go into autoimmunity or an indication which are beyond oncology showing that pro tax is not only limited to in college or college indications, but they also can move out in other indications.

10:43
When you have a look around what if we ligase is actually used?

10:47
So here I counted this is what if we ligases are the structures in in compound and products in the clinic where the structure's actually already disclosed.

10:57
So you can see for the majority of them the structure's not disclosed yet.

11:00
But for the products where it is closed, it's mainly bound and mainly based on Seroplon EV ligases a little bit also on on DHL and I think it's one of the topics that we'll discuss later.

11:11
So what is the next big EV ligase on the horizon?

11:15
And we now have a look around target classes.

11:17
You can see that it's actually a couple of target classes which are used.

11:21
So not surprisingly, many of those protects go after kinases.

11:26
There are also Nokia hormone receptors, which are, for example, heavily used, also some epigenetic targets and also some transcription factors.

11:33
And I mean, transcription factors are often target classes.

11:36
It's a target class, which is very tough to track with a small molecule, but it's exciting to see that there's quite a number of target classes around there, the protests actually explored.

11:48
So if you now go beyond Protex, what is on the horizon on targeted protein degradation?

11:54
So one of the problem what people experience early on in Protex is that the compounds got actually pretty big.

12:01
So normally you can get Protex easy to 900 or 1000 Dalton's even machine have some challenges that you are working in the beyond rule of five space.

12:10
And then people thought what about molecular clue degraders, which are molecule likely a little bit smaller, which means from a development point of view and also from an essay technology, sometimes they are deemed to be a little bit more well behaving than a PROTAC because they are more small molecule like.

12:27
But another exciting thing about molecular to the greatest actually that they bind and then they can change the surface of the of the protein of interest, which means that you then can make contacts with proteins which you normally could not make contacts without the small molecule clue binding to it.

12:44
But one of the challenges, and this is also a topic I would like to discuss later with the panel, is that the hit idea is more more challenging.

12:50
So how do we actually find those in a more rational fashion?

12:54
I said one of the big challenges, still a small molecule track discovery is that sometimes you want to target a protein which is essentially also in healthy cells.

13:07
And if you follow the last, let's say couple of years, there was a big buzz around antibody drug conjugates in pharma with the promise that you can deliver small molecules which you can't give systemically because they are too toxic, but you can deliver them quite selectively to your target cell.

13:22
And what people have now done is they have thought could we also put for example, Protex on an antibody, which are they're not called antibody drug conjugates, but degrade the antibody conjugates.

13:32
So Dacs, but the promise is for example that you can also as I said target proteins which are more essential As for healthy cells.

13:40
And people were also discussing because the protocol can have an catalytic effect.

13:44
So once it has initiated the degradation of the first protein of interest, it can diffuse away, trigger the degradation of the second one, the third one and so on.

13:54
And with antibody drug connucates, one of the big challenges is actually to get enough of this one molecule into the cell.

14:00
So a protocol could here in principle be beneficial because theory you might need less protech in the cell which then can trigger a catalytic effect and you get the desired pharmacology.

14:12
Another area which is I think interesting at the moment is protechs normally only work inside the cell because they are depending on the proteasomal degradation system which is inside the cell.

14:22
But many important proteins are actually extracellular and people have had a look now what can they actually do to also engage and degrade extracellular proteins.

14:32
So there are for example, some areas where for example latex are used, which then can track the extracellular protein inside the cell and then go into the lysosomal degradation path and degrade of extracellular proteins.

14:48
So when you read product publications, 1 area I would like to touch upon is around what are actually the challenges of product discovery because historically they are still seen as in in the small molecule bucket.

15:03
But what I I said at the beginning is that actually products have larger than small molecules.

15:07
And what we see more and more is let's say the SS we are using for some molecule truck discovery.

15:13
It is dangerous to just copy paste them and use them for product discovery.

15:18
So for example, essays like cargo permeability can be more more tricky products are more sticky towards, for example, the plastic of the virus that you sometimes need to develop specific essays to for, for Protex because they behave a little bit different.

15:34
Another question is around safety essays.

15:36
So can we just use our screening panels and screen them against Protex or do we actually need to have specific essays for certain for Protex compared to some molecules, which is for example, the area of proteomics.

15:50
Another thing which we discuss very often in in the team is can we use the same guidelines for small molecule truck discovery?

15:55
So over the years you have got a good understanding if you got certain signals in safety assets, for example, what does it mean?

16:02
How does it translate?

16:03
For example, in vivo situation, what is the threshold which of inhibition of a certain off target we can tolerate without seeing adverse effects.

16:12
So how can we now use those thresholds for protect discovery?

16:15
Can we use the same threshold or do we need to adjust the threshold for for protects to are the thresholds higher or lower?

16:21
And another big question is around, for example, those predictions and how can we actually predict from an in vitro system into an in vivo system and then into the clinic?

16:31
So I think that we also need to have more data to make those predictions make it.

16:36
And one the final thing I would like to touch upon is what I call the so far unfulfilled promises of Protux.

16:42
So when you read Protuk refuse, for example, people claim a couple of things which where Protux could be beneficial, but which I have not seen too much work in this area.

16:53
So what people forgot, for example, very excited is that there are on 600 EFI ligases in the cell.

16:58
And then people thought there could be a lot of opportunities of novel ligase which we can be recruited, I think the field and we can just discuss state in the panel also there are more and more ligases coming, but we are far away from engaging the majority of those ligases.

17:14
And one area which also was very exciting is people were discussing tissue or disease specific if you ligase.

17:21
So let's say you have a target which is in a lung cell and then you look, OK, what if you ligases are in a lung cell compared for example to a liver cell?

17:31
And then you find a certain EV ligase.

17:32
If you then would base your protocol on this EV ligase, you could get degradation in the lung cell where you'd like to have it if you go for respiratory indications.

17:41
But you can can for example, spare degradation of this target in other cells because EV ligase is just not present.

17:48
While sometimes people discuss the same around all the C states, it's certain ligase could be up or down regulated.

17:53
And this is how you can get certain selectivity.

17:56
But this is something which I always read in in refuse, but there have seen very limited examples this can actually be utilised.

18:04
That's why I call it the so far unfulfilled promise of products.

18:09
So with this, I would like to conclude, I hope this introduction gave a bit of an idea that I think there's innovation required in small molecule drug discovery and let's say using the classical approach going for some molecule inhibitors, it can still work in the future, but we need more tools in our toolbox to really expand the target space which we can, which we can modulate.

18:29
It's exciting to see that more than 40 products are currently in clinical investigation.

18:34
And I think when I thought about actually there is the product field, I think people are very excited about it.

18:39
But I think there's still in my opinion one where we keep he's missing and this is the first approved PROTAC, the first clinically approved PROTAC really moving the PROTAC field to a truck modality.

18:51
I'm quite confident that if we get there, but let's see what the future holds for the product discovery field.

18:57
And then in the final section, I'll discuss a bit more about the other targeted protein degradation mechanisms, for example, like molecular glute degraders or degrader antibody congregates.

19:08
And 1st, I would like to conclude and I would like to introduce the, the panel for the discussion.

19:16
So should we go ahead?

19:17
Martha, do you like to share a bit your, your background and give a bit of your CV?

19:23
Yeah, of course.

19:24
Hi, I'm Marta from Amphista.

19:26
So we are a molecular greed degrader company based in Cambridge.

19:32
We work on molecular greeds that do not engage VHL or Ceroplon.

19:38
So we've disclosed degraders that operate via DECAF 16 and F Box 22, primarily oncology programmes, but our molecules are quite small, so they can also access the CNS and we've got some earlier degraders in the CNS space.

19:55
Yeah, hand it over to Adam.

19:57
Frank, welcome to Dependent.

19:59
Thank you.

19:59
Adam, do you like to introduce yourself?

20:02
Yeah, sure.

20:03
So I'm Adam.

20:04
I work at Tannery Therapeutics.

20:05
So we're a tech by a company based in London and Stevenage that also works on molecular glues.

20:11
Similar to Marta, we're very much outside of the Cereblon and VHL space, but what we're looking at predominantly is both degrading and non degrading glues and also outside of oncology.

20:22
So expanding the therapeutic space and by using our computational platform to discover new glues.

20:28
Thank you, Beckham And Ben, do you like to share a few words about your background?

20:32
Yeah, thank you guys.

20:33
You can hear me, I forgot to test my MIC before joining.

20:38
So my name is Ben.

20:40
I'm the CTO of a company called Foremost.

20:42
So we have a Biver integrator interest and have done for many years.

20:46
I'm a biologist with a background in protein stasis.

20:49
I also have a second hat, which is founder and CEO of a new biotech in stealth mode that's focusing specifically on molecular glues.

20:57
So I hopefully can talk to both fields today.

20:59
OK, perfect.

21:00
Thanks a lot and looking forward to the discussion.

21:03
So before the before the session today, we have agreed on a couple of questions we would should we like to discuss.

21:09
And I think the first question I would like to discuss a few is around the hit identification, which for me is still one of the big bottlenecks.

21:16
Because when I when we discussed let's say hit identification for Protax, you can in theory do it in a bit more rational way.

21:24
So if you have a POI binder and you have your, if you like ACE binder, you have Radio 2 points and then you need to find the linker, you need to optimise the linker part.

21:33
So what is your thinking about hit ID for molecular glue degrade us especially is it phenotypic or can we do it also more target centric or what is your approach?

21:42
You have a target, you think you would like to go for molecular glue approach.

21:46
Does it work or not?

21:47
Or do you come, do you come more from a phenotypic point of view or sight?

21:52
Let's start the discussion off.

21:54
So first of all, Stefan, thanks a lot for the lovely introduction.

21:57
That was a very nice scene setting for everyone.

21:59
I think we've jumped straight into molecular glues.

22:01
I'm sure we'll come back to talk a bit more about Protax as well because I think there's lots to unpick there that you had started to address in your nice presentation.

22:09
But on this first question, molecular glues, I strongly suspect that Adam will want to give some indications of the ternary approach using computational based systems for PID.

22:19
So I won't touch on that.

22:21
I do like phenotypic based approaches.

22:22
Maybe one thing I wanted to discuss today and I'd love to hear the panel's opinion on this is maybe some of the things that aren't working in molecular glue discovery.

22:30
So just as the field of Protax has had some challenges associated with it in the transition moment from what I think are many tool molecules in the Protax space to molecules which actually look like drugs.

22:42
And then obviously, of course, beyond into drugs, which then give a clear patient benefit and have regulatory approval, glues maybe also are starting to feel like they haven't quite fulfilled their promise.

22:52
And I would level the criticism for this at what I think is a fundamental misunderstanding of how to discover molecular glues.

23:00
So from my perspective as an evangelist with an obvious bias because of it didn't work.

23:06
Thinking about it, is it the way this this this whole degradation field started to try and address his idea?

23:12
Molecular glues came from a very E3 centric perspective.

23:16
We had a moment at which clues became really relevant and interesting because we could see the degradation was exciting, but the Protacs weren't always going to be quite enough for all the reasons you introduced Steppen.

23:27
And we also had lots of enabling technologies which would give us an opportunity to discover, I guess, a fairly rich number of different E3 ligase ligands.

23:36
And they of course were pivoted in both directions towards Protacs and towards molecular glues.

23:40
These would be DNA library screening, virtual screening exercises, high even high throughput screening and it just mining people's libraries to see if we have molecules that can stick with any degree of specificity to each to an E3 ligase.

23:52
Now I do believe those two molecules have shown promise in developing Protax.

23:58
I believe they are fundamentally the wrong way to find molecular glues.

24:02
And why do I say that?

24:03
I say that because to be a molecular glue you necessarily require there to be a substantial degree of protein, protein interaction supporting the ternary complex between the protein of interest and the E3 ligase.

24:16
And the most, the best data that we've seen so far and I suspect the vast majority of E3 ligase ligands that have been discovered through high throughput screening, hundreds of them no doubt in various different biotechs and and pharma companies will bind of course to the most attractive and and bindable pocket on those E3 ligases, which will more than often be the same pocket that will access the best PPI route for future assembly of the ceramic complex.

24:46
So we are competing effectively for the sweet spot in the binding interaction between the three ligase.

24:50
Often it's the degrom binding pocket or something similar.

24:54
And by doing so you're effectively eliminating the opportunity to discover good molecules.

24:58
We can ultimately recruit a diverse range of potential E3 ligases.

25:02
That's an attractive idea.

25:04
And I can say I think we've been mis sold the idea by by the route of Protax and by the wrong lessons being learned from Ceroblon because Ceroblon on the surface looks like the perfect example of why why can't I just take a a ligand and diversify it and make molecular glues.

25:19
But of course what we know now is the native Dagron binding to the well, starting those down, the native Dagron binding to the Seroblon protein also competes for the image and it is a reconstituted binding site that represents the structural Dagron interaction with Seroblon, which is a completely different kind of phenomena.

25:35
So my soapbox is that we've done it, done it all wrong all along, and we're missing the golden opportunities to properly understand molecular glues, which are a completely different kind of molecule to Protax and for which do not require, in fact probably contrarily cannot be discovered by just diversifying a random bunch of E3 ligase ligands.

25:54
And I'd love somebody to tell me that's wrong, but that's how I feel at the moment.

26:01
Yeah, I mean, I can jump in.

26:02
I don't disagree with you.

26:03
I think I mean in the particular case of Seroblon, it's definitely been heavily studied.

26:07
And I think if that's what people are looking for, there are obviously like a massive number of CR OS now who are very happy to do things like direct to biology.

26:15
You know, they can screen hundreds if not millions of compounds diversified from this.

26:20
But I agree that it's a very fundamentally limited target space I guess in terms of what we're doing.

26:25
So we very much are a target centric companies.

26:28
So we're not kind of doing phenotivic screens and trying to work out what's going on, but instead trying to take targets that we're interested in.

26:35
And then really we've got 2 approaches computationally.

26:37
So we can either take kind of a pair of proteins that we know have got maybe some weak interaction that we want to try and enhance and we can then use kind of like virtual screening and various different techniques to try and find liggins that we're confident to bind to those.

26:50
But the other approach that we have taken that we have looked into is actually doing this from a more target centred approach, looking at different compounds.

26:57
And then when we find, when we find a compound that does the biology we're interested in, we then kind of have platforms to go back and look at what E3 ligase or what effect a protein might be doing that biology.

27:08
So kind of both ways around, we can look at that depending on which pieces we know of the puzzle.

27:13
And I mean, that's one of the fundamental challenges of this, I think is knowing the pieces of the puzzle.

27:18
If you know the exact 2 proteins that you want to bring together, you can set up beautiful assays to look for those ternary complexes, kind of incredibly weak binders you can find.

27:28
It's much harder when you're just saying, I want to take K rise and find something that glues it to something.

27:34
Yeah, that's the big comment.

27:36
Adam here.

27:37
Sorry.

27:37
Go ahead, Martin.

27:37
No, I was going to say I agree as well.

27:39
I think we're we're not forcing, I think our Amphistus technology where we take a target, again, similar to Adam, take a target that we're interested in, take APOI, derivatize it with our own library and then just look what it degrades.

27:52
And then we go looking what a three was responsible for that.

27:55
We're not forcing our target to interact with an E3.

27:58
And I think there's multiple complementary approaches of how people are doing it.

28:01
And I think this is going to be key to uncovering new degraders against targets and possibly new E threes.

28:08
Would you classify those approaches of theatrical screening or it's a slight deviation degradation?

28:16
Yeah, it is, yeah.

28:17
I think we always look at degradation.

28:18
We have never looked at self fitness, although that is a possibility.

28:23
It's just not something we've done.

28:25
But on your comments about the fact that the pockets, the most druggable pockets on the E threes are going to be picked up, I think we've got covalent compounds and I think what we've seen there is a bit different.

28:37
We find that the hits, at least in our earlier screens, they were very reactive warheads.

28:42
And so the cysteine that was almost hooked by the compound, we were able to identify sometimes very weak ternary complexes where the protein, protein interaction was actually very weak.

28:52
And it's only through optimizations I will touch upon later that we were able to dial down the reactivity of our actual warhead, but optimise the protein, protein interactions.

29:01
And I think that was key.

29:02
Yeah, I think covalent approaches don't necessarily sit slightly aside from traditional drugable approaches.

29:08
That's a that's a really important consideration.

29:12
So I would like to pick on Adam's comment that you said you often look for, let's say weak in the actions that you find the right binding part.

29:18
But sorry for your protein of interest you would like to degrade.

29:22
What do you think is the best approach there?

29:23
So do you have like computational tools where you can check how complementary the two proteins are?

29:30
Do you do a bit of that work before?

29:32
So what would you will be your approach if you have protein A now you would like to see can we actually degrade it with a molecular glue?

29:38
What would be your workflow?

29:40
Yes, I mean we are heavily computational.

29:42
So a lot of our early stage work is computational before we start looking at compounds.

29:46
So we look at things like surface complementarities.

29:48
So we look at whether or not proteins are predicted to have Global Services.

29:53
We've built our own models for that.

29:55
There are various publications that talk about kind of open source ways that you might go about doing this.

30:00
And then once we've identified targets that we do believe are global, we can then screen, gradually screen through libraries of other proteins to see which ones look like they come together.

30:10
So I mean, for example, if you just took BRD 4 and Seroblon, you could look at them and you could see if you thought that they had surfaces that made sense.

30:18
And we can do that kind of in a high throughput way.

30:19
So kind of machine learning, we can do that in much more computationally expensive ways with kind of long molecular dynamic simulations.

30:27
And so that that's how we do it.

30:28
And then we kind of go through looking for compounds.

30:30
And of course, just because two things have a complementary interaction just because you can lick in them it then there's like another layer of biology, which is does that ternary complex do something productive?

30:41
Can you actually force it to to then degrade, which I think is, yeah, a really interesting problem.

30:46
It's very specific to glues, I think is just because you're bringing things together in theory.

30:50
Can you actually then get them to do the biology you're expecting them to do?

30:54
Although there's obviously a rich field now emerging and maybe one of the most promising bivalent approaches and in some cases non evaluating is to drive just associations a bit like the Riptacs and have that have a consequence for sequestration of a protein in some other form or other.

31:08
But yeah, we, we, I just quickly speak on our approach.

31:11
We have the same concept, but we start from a biology starting point.

31:14
So we can conduct cellular screening to address de Novo ternary complex formation, which reads out as degradation.

31:20
And that allows us to feed in from a much more confident starting point into computational systems.

31:25
But I really like Adam's point earlier around the molecules that can be discovered in this place.

31:30
I think fundamentally the challenge is, is on the asking the right questions and not some sort of magic property about the molecules.

31:37
I think that's also something that starts to become more and more apparent as we get better, you know, both in our case of the cellular data sets, but also in the computational systems we can apply to these systems.

31:46
The molecules are definitely there to be found.

31:48
They don't have to have traditional properties and qualities.

31:51
They're actually quite, I sometimes describe them as quite bad drugs.

31:54
You know, they don't have high affinity.

31:55
They don't have, they actually can have quite a high degree of structural diversity from the the pharmacology properties as well.

32:01
So that they are there to be discovered provided that we're asking the right questions.

32:04
We're starting from good confident positions about what we understand about the relevance of either a ternary complex or a piece of biology that we can programme into a ternary complex discovery mechanism.

32:13
So that I find to be a really exciting moment for the field that they were just starting.

32:20
I feel even just in the last year or so to understand that promise and potential and multiple groups are starting to say similar things about understanding PPI, integrating various different kinds of technologies and data sets to actually start to try and start from scratch on molecular glues.

32:34
Because like I said, I think the original approach of just I've got a ligand, maybe it's a glue.

32:38
Is, is fundamentally not the right way to go about this.

32:43
I'll use this.

32:44
I've I've a fault in that say predicting.

32:46
I mean, let's say if you want to check for complementarity of it, of your protein of interest and your, the, the, the effect of protein, so to say.

32:55
I mean, one thing is of course you look at crystal structures, but let's say there's no crystal structure.

32:59
Is the alpha folder useful thing wise?

33:03
It's pushing it too much that you have 1 prediction for the alpha fold and then one prediction for the interaction.

33:08
This is too much where it's the field already there to really use this and get kind of reliable results, which you then can base on your experiments on.

33:17
Yeah, I mean, I can maybe start with this.

33:19
We've looked at this quite a lot as a computational first company.

33:23
I think the alpha fault structures themselves are great and we have used them as inputs for various different accommodation experiments that we've looked at.

33:30
I think the one challenge with alpha fault is that it obviously looks at structured domains and proteins and from a traditional small molecule drug approach.

33:38
If you think about kinase inhibitors, we're only really interested in that structured domain.

33:41
We don't care about the spaghetti that goes around it.

33:44
And the challenge when you're looking at glues and if you look at kind of some glue structures, they often do have interactions that are part of unstructured region.

33:52
So yes, I think alpha voltage useful.

33:55
I think it can take a bit of preparation and a bit of thought to actually use those internary complex modelling.

34:00
In terms of taking that step further, our computational team did recently publish a paper looking at Co folding approaches.

34:05
So this is where you essentially try and do the entire ternary complex prediction in one go from sequences.

34:11
And we show that that's just very difficult.

34:13
I think there's just not enough training data out in the wild for a computational model to reliably be able to get essentially cold Co fold an entire ternary complex.

34:21
I mean, I think that's where you have to be a bit more careful using these kind of computational approaches.

34:27
Yeah, I think we've found that having good structural data of your ternary complex is very important.

34:33
We've invested quite heavily in health multiple.

34:36
I think it's up to like 8 or 10 ternary complex structures with different compounds to really understand the SAR.

34:42
And then then it's very helpful because it's very predictive of, you know, what SAR you're going to get.

34:47
It's enabling us to triage designs very quickly and quite accurately actually.

34:52
And for example, in the case of SMARCA 2 where you alluded to it and you talk and your introduction, Stefan, you know, you really want to degrade SMARCA 2, not SMARCA 4.

35:00
But the binding pocket is exactly the same.

35:02
And it is the ternary complex, which we were able to thanks to the structures, experimental structures and then modelling, we were able to then get selectivity there.

35:12
So you guys in combination with Crow EM, is that right?

35:15
Martin Core EM, Yeah, often the, I think the resolution on Crow EM is exactly the same as crystallography, but you can get quite big proteins on there.

35:26
I think we do it quite routinely now.

35:27
It's it's kind of become part of the cascade almost.

35:32
I think there is a lag at the moment where kind of obviously with small molecules there's a lot of data deposited.

35:36
But I guess because it's such a new feel, people are either very reluctant to or a lot of its proprietary data.

35:41
So I think in the next few years we will hopefully see a big bulk of chlorium data that's being published and deposited to that.

35:47
The whole community can learn from that.

35:48
I think there'll be some really interesting insights as that starts getting published.

35:53
Like to pick up on your point on a ternary complex formation and how it drives SAR design.

35:57
I mean, one thing when we discussed ternary complex, this is always OK.

36:01
You might not only let's say you get a structure of a ternary complex, but then the question is, is the productive ternary complex?

36:07
And this is where people can sometimes shy a little bit away from can we really use it for SAR?

36:13
So what is your experience about using ternary complex for design is some form of needs to be a little bit more careful.

36:18
This is something you think Martha used.

36:20
You said you use it quite routinely now for compound optimizations.

36:23
What is this theoretical fear?

36:25
This might not be the productive ternary complex.

36:27
Then you drive the SAR in the wrong direction.

36:29
What is, what is your take on this one?

36:31
I think we, we have to combine it with cellular data.

36:33
In our case we found relying just on and not just structural even binding, binding assays.

36:39
We really need to combine it with what happens in a cell to your degradation, the kinetics, the depth, the potency, everything.

36:45
In some cases, we've used ubiquitinomics exactly to answer the questions that you were you alluded to Stefan, which is are we getting selective ubiquitination and where is it?

36:54
And so can we place that in this case it was a loop which is published biocompetitor that is ubiquitinated in Smarter 2, not Smarter 4.

37:03
And that was key.

37:04
But we you do need cellular data.

37:06
Otherwise you, you just can't detangle the, the, the structural data thing.

37:10
And you need both, right?

37:11
Because in circumstances where you only have cellular data and you're not structurally enabled, then you're in a real pickle for all sorts of unexpected MOA switches that can happen in this wild and exciting degradation field that we all work in.

37:24
And there are more and more examples of that being published and disclosed, which is a whole fascinating conversation to have on another day, I'm sure.

37:36
On this point, we discussed a little bit screening strategies and cascades.

37:39
So what do you think apart from, let's say a cellular degradation screen and a ternary complex model?

37:44
What do what other essays, let's say, do you think or technologies?

37:48
Do you think a must have technologies to be successful in the glue degrader or product space?

37:56
Marty, that sounds like what for you.

37:57
I don't know if you've exhausted your list.

38:03
No, I think so.

38:06
It's important to understand, you know, what target are you going after, what are you going to achieve when you degrade your target?

38:12
And I think does it offer an advantage compared to inhibition?

38:17
Because I think otherwise you're just doing a very complicated method to just do what your inhibitor could have done.

38:24
I think it sounds obvious, but checking that your inhibitor actually doesn't degrade your target because the, the degradation field is relatively new, I think there are lots of inhibitors actually did stabilise, destabilise the target.

38:38
Not necessarily some were like those grooves, but some just destabilise them.

38:40
For some reason the cell just got rid of it.

38:43
So that's something we do routinely.

38:46
But then other than scaffolding functions, you know, which you you alluded to, there are other things such as is the pharmacology, does a degrader offer better pharmacology?

38:55
For example, can you, if you take out the target for a very long time, is that going to offer you deeper, a better therapeutic index?

39:05
So I think it's very important before you start investing into the greater programme is understanding your target and why you're going after it.

39:12
What kind of profile are you looking for?

39:14
What kind of degradation are you looking for?

39:17
Sometimes, sometimes it's deep, probably in the oncology space.

39:20
But for things like CNS, sometimes just getting rid of 50% of your target is probably going to be sufficient.

39:28
Does your rationale also extend?

39:30
I think Stephanie mentioned this in your introduction as well around selectivity, tissue selectivity, which is sort of a bit of a, a white elephant these days in degraded discussions.

39:40
Because I don't think anyone's realised the promise that was there maybe three years ago when it was very in vogue to talk about that.

39:49
I mean, it still has some interesting things to probably be uncovered about various different ligases, but I don't think anyone has shown selective degradation that is based on a rationale that we previously no.

40:01
So I would agree, we don't specifically look at it because we don't think you might, you're not just going to stumble upon that or we might, but we want to ensure that we're active in the line of sight cell or tissue.

40:14
So I think that's something very important.

40:16
We really ensure that we degrade in all different types.

40:19
You know, if it's a specific patient population, you want to go across the genotype, across different tissues and really.

40:25
Check that you degrade there.

40:27
In terms of tissue cell activity, we think that the degrader antibody conjugates actually probably offer more of an advantage or more accessible way forwards rather than looking for E3 sparing and that that could be due to the way we do our screens.

40:41
We are not counter screening in a cell line which we don't want to degrade in.

40:50
So if you stick with, let's say the, the greater antibody conjugates, I think that is also topic for you.

40:55
How do you see this field?

40:56
This is like a hype because AD CS is hyped and then the Protac molecular glue field jumped on it.

41:02
Or do you think this is something which can really make a, make a difference in the future?

41:06
No, I, I, I do think there is promise there.

41:09
I think it's very early stage, but I do think it can offer a level of precision.

41:13
You know, AD CS offer precision due to their antigen.

41:16
You know, the antibody to which the the antigen to which the antibody binds to gives you the cell and tissue selectivity with degraders.

41:23
You can achieve that by whether the targets expressed or not the three legs is expressed or not.

41:27
But as we talked about, there's very few examples of that.

41:30
But when you put both together, then you get a multi layer selectivity and I think you can really get improved safety there, but also can unlock new targets.

41:39
Sometimes we just when the, when the toxicity is on target you, you probably unless you can get an E3 sparing degrader, you're the DAX will enable that.

41:53
I think we, there's some nice talks at the TPD meeting a couple of weeks ago from Nurix and prolied on how they're doing that with their Cerebron Dax.

42:01
But I do think they alluded both talked about the challenges of developed in the Cerebron DAX because of the Cerebron chemistry itself.

42:10
It is not always easy to get it onto the antibody and then this has to be stable for a long period of time to to bind to the antigen and get into the cell.

42:19
I think with Mfesta we've got different chemistry and so we believe that we can get our degraders, our payloads onto the antibodies using typical conjugation methods and this would be stable in humans plasma.

42:33
So I do think they offer quite a lot of opportunities.

42:35
It's just the field is very early.

42:37
It requires understanding of what the problems are, what are not the problems and things like you alluded to, right?

42:42
What kind of can we get away with weak degraders or can we not?

42:46
Because I think that is a debate to be had, but I think it's just an early field.

42:54
Thanks.

42:55
I think 11 point.

42:56
I want to touch upon what I think is, I mean, often people say molecular glues and molecular glue degraders often are used synonymously, which I don't think is true because molecular glue degraders are with degraders, molecular glues can do much, much more.

43:09
And I think someone already independent alluded on this.

43:11
So what beyond molecular clue degraders, what do you think is let's say the next hot field of molecular clues, is it riptax or what is what is on the horizon there?

43:22
I think it's riptax good in it.

43:27
I think it's, yeah, there's, there's increasing evidence that that is a strategy, whether or not it's because it's more achievable because you're sampling a massive diversity of potential mechanisms or whether or not it's actually because it's the better way to use induced proximity therapeutics, I'm not sure.

43:43
But the, the, the, the well, obviously this clinical data is very nice and how they're leading the way, but there's actually some nice academic studies as well.

43:50
There's a really nice one came out last week on P53.

43:53
And I think you can even do this in a target centric way as well.

43:55
So there I think there is a big array of potential in that space.

43:59
You can use macro cycles, you can use, there's a place where you probably can, you know, really focus on the the POI ligand as well and just address directly, you know, typically in that case.

44:08
And I suspect the majority of mechanisms that will be revealed or be RIPTAC, like I think there has been lots of really cool other things, you know, both for Protex and for glues.

44:19
And the KRL story, especially in the macro Cycle World is quite incredible.

44:24
Love to see that repeated in different places.

44:27
But that might be a little bit niche and might not be as kind of generalizable as I think the riptax field is showing potential to be.

44:36
Yeah, I mean, my answer to this may be a bit biassed, but we've been looking at activation as opposed to degradation.

44:40
So actually switching back on biology.

44:42
So one of our kind of lead projects is be activating by glueing 2 projects back together, kind of where disease biology has kind of gain of function versus loss of function, which is something that we're really excited about at the moment.

44:59
How do you discover those active?

45:00
I'm interested in those activating things because I think this is a nice approach.

45:03
And often, I mean, we also take for example antibodies.

45:07
I mean they're often blocking.

45:08
And I think this it's for molecules who can activate stuff.

45:10
I think there's an exciting field because there are not many other modalities who can who can do it.

45:15
So we've got to share a little bit more of the approach there.

45:17
And how would you actually discover activating the activating clues, if you can share more?

45:26
Yeah, I mean, I think we did a lot of kind of data mining, literature mining, just looking at diseases.

45:31
And I can't remember the statistic off the top of my head, but I think a very small proportion of diseases are caused by gain of function.

45:38
So the kind of things that you'll be able to inhibit represents a very small proportion of all possible diseases.

45:44
And so we kind of started from that position looking for diseases where reactivation would be useful.

45:51
That kind of gave us target lists and then you can kind of work backwards from there with a computational approach.

45:55
I think the nice thing about the way we've built our platform is that it doesn't really matter what the PPI is like fundamentally we're looking at PP is coming together and ligening those Ppis.

46:05
Sorry, we're not going to limit it to just saying we're looking at degradation in that sense.

46:15
Thank you.

46:16
I guess when the assays do get a little harder when you're looking for activation, there's both you a nice way is to look for generic activation in the same way as you could with a hybrid cell history.

46:24
And the downside of that from a kind of biology perspective.

46:28
Yeah.

46:28
So the screen is more tricky.

46:29
Yeah.

46:30
Green.

46:31
Do you look at things like post translation and modifications?

46:34
Is that also, you know, I guess, I guess it can it's, it's a whole panel of things that you can look at activation, right.

46:38
So I get, yeah, your your screens must be quite difficult because you don't want to miss things.

46:45
So you have to look at I guess levels post translation, modifications, localization possibly, Yep, also like mutations as well.

46:52
So like situations, those mutations.

46:55
Yeah.

46:55
So we've got one project in that space at the moment.

46:57
I won't say too much else, give away too much.

47:02
Exciting to see what is ahead of us.

47:04
So if you come back to the molecular glue degraders, I mean one question I was always wondering, I mean you have those two options now we have the protocol option and you have the molecular clue degrade option.

47:13
And I mean the companies you are all working on are heavily clue focused.

47:18
So what does actually your what do you take into account?

47:21
So let's say if you approach of interest identified and then the question is, would you go for clue or would you go for PROTAC.

47:27
So what are the key things one should take in mind to decide either for the PROTAC or for the molecular clue approach, how much money and time you've got?

47:37
OK, so clue some.

47:39
Thank you.

47:41
No, the other way I think, I think you need to go down the prototype route.

47:44
You need to accommodate a much, much more complex than medicinal chemistry and translational route.

47:49
I think you need to have really deep pockets, extreme tolerance being being brutal about it.

47:54
I think it may become the luxury of the Pharmaceutical industry and it's not a place where biotech has a liberty to play.

48:00
I think the funding environment is challenging to justify that particular endeavour at the moment.

48:06
Glues, on the other hand, you know, we're only just starting to properly understand what they are.

48:10
Obviously we need innovative new technology and I think there's some really, really exciting things going on.

48:15
And I think those next kind of couple of years as we start to properly untap and get better examples and start to understand the rules, not necessarily at the level of the chemistry, but actually under under the kind of properties and paradigms in which clues can be discovered and how to routinely discover them.

48:32
I think they'll become eminently more discoverable more routinely and ultimately have traditional predictable translational paths.

48:40
And so I think, yeah, contrary to your the time of money, I think it's hard to spend on broke tax on the money at the moment.

48:51
Yeah, I think I would have said the opposite to what you said.

48:53
That's always fun.

48:58
No, in terms of money and not which one would be in terms of which one would cost more money and time because the, the project is quite modular, but I guess you can only take it to a certain extent.

49:07
Yeah, yeah.

49:08
The tool, the tool discovery 100% degree is much more accessible.

49:11
The systematic part I, I'm absolutely.

49:13
And I think there are.

49:14
And actually I think that, you know, I think Stephanie mentioned around the, the, you know, how many ligases have been really enabled.

49:19
Actually there are loads, there are many, many good examples of degraders against all sorts of different ligases.

49:24
I'm sure we're into the 20s by now that have shown tool compounds that are recruiting those ligase is with good enough data packages to show that they can be hijackable with the protech.

49:34
It's the part after that is where the valley of death starts actually in getting it into a drug or a candidate starting point.

49:44
Yeah, but you're also sitting on a rich place that's got a technology that can identify, please.

49:49
So I think it'll be nice once other people have access to this, like you say.

49:53
And, you know, in a decade or so, this will be more routine.

49:56
But yeah, yeah, well, we're happy to partner.

49:58
You know, that's never a problem.

50:01
I was also coming more, I mean, from the product space because, I mean, I think, as I said, discovery is a little bit more straightforward because it's, we have a bit of more of a modular assembling it together.

50:11
I mean, then you still need to get a linker, right?

50:12
But let's say you get starting points perhaps a little bit quicker, but I think then you might pay more at the end when it get more gets more more complicated because I agree.

50:21
I mean, small molecule molecular clue is a bit easier to to develop because it's still more small molecule like more or less.

50:28
Yeah.

50:29
So I would like to touch on your point about the EV ligases.

50:32
And I see you you said something around 20 of them are already out there.

50:36
Meanwhile, I sometimes see the problem is that people find binders to it.

50:39
But if you then look at with a truck like glasses on those binders, sometimes they, you can see that they might be very challenging to get them into a truck.

50:48
So of those 20, if you like, as you have mentioned, then how many do you think can really not be applicable, but really truck up that you get the properties in the right space.

50:57
What is your how many?

50:59
I mean, despite my previous sentiments, I, I am optimistic that in time, you know, Protax that are diverse away from the the ones that have shown promise in the clinical data set so far, which I think we all know will be yeah, especially setup on of course, VHL and some of the decafs.

51:15
But I actually do think that I don't see any particular reason why it isn't eventually solvable.

51:19
There's some, you know, phenomenal Tour de force examples of Med chem that has made molecules which didn't ever look like they were going to be drugs into drugs and into candidates.

51:27
And I think that's really, really important work to be done.

51:31
And I think that's going to be, and it is being done, I'm sure.

51:33
But I think that's a time consuming and costly and unpredictable endeavour.

51:39
So, but in principle, I don't think there's a, a cap on it.

51:42
I, I suspect that because of the principles associated with protects and the, you know, the ability to circumvent to a certain extent, some of the properties that are required by molecular glues about complementarities and things like that, protects actually might offer long term a better solution.

51:57
But when I say long time, I, I might be thinking about decades here, whereas I think good drug candidates with molecular glues are going to come very, very quickly in the next few years.

52:06
So I don't, I don't have any, you know, starting position on certain ligases being completely incompatible.

52:11
There are certain ligases which have a high proclivity to discovery and I don't think we understand that yet.

52:17
But there's some fascinating biology around that yet to be unpicked and all the stuff that Martha mentioned earlier around systematic screening with counter screening, with proper biochem enabling, you know, with good readouts and structural data wherever possible.

52:30
I think we know broadly speaking, how we can enable the best routes forward to maximise the likelihood of discovering a proper proto that's actually via the mechanism we intended in the original part.

52:39
So yeah, I like the Protox.

52:41
I just think they're harder and slower.

52:42
But yeah, as Master says, that's the opposite opinion too other people, so that's fine too.

52:50
I do think it's fascinating though, that, you know, especially sitting from I'm Fista, I have spent a long time thinking about it.

52:56
Why are Decaf 16 and F Box 22 coming up for quite a lot?

52:59
And, you know, there was a nice review by Cravat that was quite nicely timed.

53:03
As you can imagine, we all spent a lot of time reading it, thinking about it, and I still don't have an answer to this day.

53:07
Why is Decaf 16?

53:08
Oh, I hope.

53:09
I was hoping you're going to tell us the answer then.

53:10
Marty, you've got that.

53:12
Well, I've come down to something that I should, I mean it, it could be something to the biology right there.

53:17
The if you look at the literature or companies doing it, we're all buying, buying into.

53:22
I think there's at least three systems in the literature that have been liganded.

53:25
They sit on different phases of decaf 16.

53:27
There's non covalent binders that have done it.

53:29
So I don't know if it's something about the plasticity and adaptability of the C3 ligase.

53:33
This is just really happy to stick to other surfaces and just fold.

53:37
You know, we don't there's no decaf 6 April decaf 16 in the literature.

53:41
So we don't know what it looks like in its native state.

53:44
And so is it just changing quite a lot, but it could it be something about how we're just decompositing our E threes.

53:51
It may not be a redundant.

53:52
So decaf 16 and FX-22 and the other decaf and the in the review was Decaf 11.

53:59
They're not redundant.

54:00
They don't seem to have redundant functions.

54:02
And say when we do target the convolution, you often do single gene knockout.

54:05
And so anything that has a redundant mechanism, you're just going to throw it away.

54:08
You're going to say that's doing something funny to myself, but actually it, it could be the next E3.

54:13
We're just complete discarding it because you need two of them.

54:16
But so yeah, I don't have an answer that's my fault at the moment.

54:18
It's fascinating.

54:19
I totally agree and I wish we could one day.

54:21
Well, I'm sure we will one day cracking, but it's so now it's serious.

54:30
Rachel's come back on to that maybe run out of time.

54:32
I've already got time for one more point.

54:35
You have one more point.

54:37
I think I've wanted one more concluding point from our session.

54:42
So what do you think are the limitations of molecular clues?

54:44
Are there certain areas where you would not go with a with a clue certain, I don't know indications, target classes.

54:51
What's your experience or clues very, very openly similar to products.

54:55
You can use it quite broad.

54:57
You are.

54:57
There are certain areas where you would say I would not touch a clue if it needs to go into this space.

55:05
I have not found an occasion.

55:07
Yeah.

55:08
Yeah.

55:08
Once you get beyond Cereblon, I think the space is wide open.

55:12
Yeah.

55:12
But then again, we are people with hammers to every every problem is a clue.

55:18
Good.

55:22
OK.

55:22
Perfect.

55:22
But then I think, Rachel, we can take some of the audience questions.

55:27
Yeah, we have two.

55:29
The first one is what are the strategies and pitfalls of BRO 5 oral protects development was like who would like to take this one?

55:42
I mean, I guess we've done some in vivo work, so I can perhaps start with that.

55:46
But we are working with glues and we have found that.

55:49
So not quite answering the question because we haven't done protects, but I think there are there is evidence that you can go beyond the rule of five and you can still get oral viability and get all the properties to make a drug.

56:01
And I am not a chemist again.

56:03
So perhaps I find you a better place to answer the best.

56:05
But you know, there are other considerations such as the folding of the Protax.

56:09
What what 3D confirmation will this take?

56:11
And can it be uptaken by a cell or penetrate a tissue?

56:15
Because we have seen protests that get into the blood bone barrier and they're well beyond the rule of five.

56:20
So I think there is space.

56:22
It's just understanding it and optimising for it.

56:27
I agree with Mark.

56:28
I think this confirmation is expect aspect can be really important that in the end you always saw them like linear, but I mean, they can fault in each other, shield certain, for example, hydrogen bonds, donors or acceptors that they are not so accessible anymore.

56:42
And then actually if you look on paper, you would count the hydrogen bonds, donors and acceptors and you are beyond rule of five.

56:47
But if you then actually look how much of them can actually make water into actions either because they are too buried and some from lipophilic where water doesn't want to get there or they are already satisfied with intramedicular hydrogen bonds.

57:00
They can actually then be as you say brain permeable or even high, high or bio variability.

57:06
So I think this was one of the fears of this fiscal property space.

57:09
Do we actually get the products have good oral bio variability and good permeability?

57:14
But I think we are understanding it more and more how to design those products to get them into the right space.

57:22
So I think this is in optimization still one thing we'll need to take into account, but I think is we have a couple of tools there how to fix the the properties in this beyond rule of five space.

57:33
Yeah.

57:34
OK, interesting.

57:35
Anyone else have any insights on that?

57:37
Yeah, I was going to say, I think there's been some really interesting work recently of people showing that protects kind of have different transporters and things that get them into the brain.

57:44
So I think just fundamentally from like a chemistry point of view, we always think about PGP in the brain.

57:48
But actually it may just be that things we're screening against just don't want the things that are particularly relevant in the case of those big drugs.

57:57
Yeah, it'd be definitely interesting to see where it where it goes.

58:01
The second question is quite a big question, so we'll just get some short staffing answers.

58:08
Given the current momentum in targeted protein degradation, degradation, how do you see the competitive landscape evolving over the next five years?

58:16
More partnerships, consolidation or diversification?

58:22
I guess for us, I think partnerships are key, right?

58:26
You often need a technology which, you know, we've heard all three of us have different aspects of how we're going to offer that.

58:33
But then you also need the, in our case, we need ligands, for example, against targets other people may need.

58:39
We need ternary complex structures, we need data, we need target selection, we need.

58:45
So I think they're key to getting the best of both worlds and combining 2 people and really advancing the field forward.

58:53
For sure, for sure.

58:54
I think if you just look at the deals that big pharma companies have done, it kind of just speaks to how much they're looking for partnerships to save, having to kind of reinvent the wheel like so many multi, multi £1,000,000 deals from Pfizer.

59:08
It's an awful all in this space.

59:11
Yeah, yeah, it's, yeah, it's good because you need innovation.

59:15
But it is also fundamentally from a scientific perspective, it is both molecularly and corporately cooperative.

59:21
So I'm sure there'll be more partnerships to be done, no pun intended.

59:28
I agree.

59:28
I mean, I think it's I think track discovery gets more and more complicated.

59:32
I mean it back in the days yet from molecule inhibitors with our screening technologies, our high fruit protects, then we could do it.

59:38
But I think now more more it gets more more tricky.

59:40
I mean, how do you do Protax?

59:41
How do you do clues ADCSDACSI mean we touched up on a couple of them.

59:46
So I think as one company it's very challenging to be expert in all of those fields.

59:50
And then the partnerships really come in that you have the specific expertise.

59:54
How do you know discover a clue or product how to develop it?

59:58
And I think your partnerships are really, really key to accelerate and not invent a wheel on yourself all the time.

1:00:07
Yeah, 100%.

1:00:09
But I think that's all we've got time for today.

1:00:12
So I'd like to exam my my thanks to all of you, Stefan, Ben, Marta and Adam for a very insightful discussion.

1:00:21
Definitely left us with some.

1:00:23
Food, it's food for thought there and seven sort of different perspectives and it'd be interesting to see where where we are in a few years time.

1:00:33
And of course, thank you to our audience for joining us.

1:00:36
We hope this session has provided valuable perspectives and sparked some new ideas for your own work.

1:00:41
So thank you so much.