This episode provides a foundational understanding of structure-activity relationships (SAR) in medicinal chemistry. We will explore how systematic chemical changes inform potency and selectivity of drug candidates. The conversation will cover SAR data, reaction mechanisms, and how adjustments are made based on real experimental outcomes. Modern techniques like AI-driven SAR modeling will be introduced, along with the challenges of multiparameter optimization (efficacy, toxicity, solubility).

We'll also delve into real-world examples to illustrate how SAR principles are applied in practice. The episode will explore the use of VR applications like Nanome for SAR visualization, showcasing how technology is transforming drug discovery. Furthermore, we'll discuss the concept of "fail fast, fail cheap" and its importance in early-stage drug development. The episode will conclude with a look at preclinical drug development, highlighting the importance of considering metabolic soft spots and the ADME profile of a drug candidate.

2025-03-23 17 min Transcript

Available Results

Generated results are saved to the knowledge database for reuse and search.

No generated results are available for this episode yet.

Extract Knowledge

Pick what you want extracted first. Model, scope, and chapter options appear after a template is selected.

Generated results for public episodes are saved to the knowledge database so they can be reused and searched later.

Transcript

Welcome back, everybody. Today we're doing a
deep dive into something pretty cool, structure
activity relationships. You probably know it
as SAR though, right? Yep. SAR is super important
in medicinal chemistry. Yeah, it helps us understand
how changing even just a little bit of a drug
molecule can have huge effects on how well it
works. It really is fascinating. It's like every
atom matters. Each piece of the puzzle is crucial.
It's true. So we've got a bunch of research papers
here, some textbook excerpts too, and even some
stuff on AI and drug development, which is interesting.
Oh wow. Seems like we'll be covering both traditional
SAR studies and some of the more cutting edge
stuff too. Awesome. Yeah, it's definitely a field
that's constantly evolving. It is. But before
we get too far ahead of ourselves, we should
probably start with the basics. What exactly
I SAR? Totally. That's a great place to start.
I mean, in the simplest terms, SAR is all about
the relationship between a drug structure, how
its atoms are arranged, and its biological activity.
Exactly. So basically how it affects the body.
Exactly. You can almost think of it like a key
fitting into a lock. OK. The shape of the key
determines if it can unlock the door. Right.
Well, in the same way, the shape and chemical
properties of a drug molecule determine how it
interacts with its target, whether that's a protein
or an enzyme or whatever. Oh, I see. Yeah. And
just like a tiny change to a key could make it
completely useless. Oh, for sure. A small tweak
to a drug molecule can totally change its potency,
how strong its effect is, or even its selectivity.
you know, how specifically it targets one thing
and not others. Exactly. And that's why medicinal
chemists are constantly tweaking these molecules,
adding or removing atoms, messing with the chemical
bonds, and then seeing how those changes affect
the drug's behavior. Yeah, it's like fine -tuning
a recipe. Ooh, I like that. you know, swapping
out ingredients to see if it makes the dish taste
better or it changes the texture. Perfect analogy.
And just like a chef relies on taste tests, medicinal
chemists rely on experimental data to see what
works and what doesn't. Yeah, that makes sense.
Now, our sources talk about some pretty cool
real -world experiments that really show these
SAR principles in action. Oh, cool. Like what?
Well, one study focused on coedroxyl. Coedroxyl?
It's an antibiotic. OK. And they use this special
type of mice called PEP2 knockout mice. Have
you heard of those? I have, yeah. They don't
have the protein that normally helps safe hydroxyl
get reabsorbed in the kidneys. Right, exactly.
So by using these mice, researchers could basically
isolate the role of that specific protein in
how safe hydroxyl moves through the body. Gotcha.
So what did they find? Well, they found that
without that protein, the drug was eliminated
way faster. Interesting. Which is super valuable
for understanding how to, you know, manipulate
a drug's absorption, distribution, and elimination.
It is. It's like understanding the whole journey
of the drug through the body, right? Exactly.
Yeah. And this also highlights how important
it is to understand reaction mechanisms. You
know, like the step -by -step process of how
a drug interacts with its target at the molecular
level. Absolutely. We need to know not just that
a drug binds to a certain protein, but the exact
chemical dance that's happening during that binding.
I like that, the chemical dance. So we can refine
the structure for better efficacy and maybe even
reduce side effects. For sure. Now, all that
sounds pretty straightforward, but designing
drugs that actually work the way we want them
to is anything but simple. Oh, right. Well, the
material talks about something called multi -parameter
optimization. Oh, yeah. And it sounds like a
real challenge. It is. Basically, you see, it's
not enough for a drug to just be potent. It also
has to be safe, right? It needs to be soluble
so your body can absorb it. And ideally, it should
be easy to manufacture and administer too. So
it's like juggling a bunch of balls at the same
time. Yeah. You're trying to get efficacy up
there, how well it works, while also minimizing
any toxicity. Exactly. Not to mention things
like solubility, how easily it dissolves in the
body. Right. And stability, meaning how long
it stays active. Well, that sounds super complicated.
Oh, it is. Balancing all those things at once,
it's not easy. Which is probably why these new
technologies like AI -driven SAR modeling are
so exciting. Oh, yeah. That's some seriously
cool stuff. From what I've read, these AI systems
can analyze huge amounts of data super quickly
to find those promising modifications. Yeah.
Imagine being able to screen thousands or even
millions of potential modifications all on the
computer before ever setting foot in a lab. That's
incredible. It's really changing the game. One
platform that our sources mentioned is called
AtomNet. It was developed by a company called
Atomwise. Oh, AtomNet. Yeah, I've heard of that.
It's a great example of how deep learning is
transforming drug discovery. Okay. So how does
it actually work? Well, deep learning is all
about finding patterns, right? So AdamNet looks
at tons and tons of data on molecular structures
and their biological activities and learns from
all that research that's already been done. So
it's basically learning from the past to predict
the future. Exactly. So then it can predict how
effective a new molecule might be even before
it's even made in a lab. So it's like having
a super powered research assistant. Kind of,
yeah. It can sift through mountains of data and
point out the most promising candidates. Of course,
it's not going to replace human experts anytime
soon. I was going to say. But it's definitely
giving us a huge boost. That's incredible. And
speaking of exciting new tech, there's this VR
application called Nanome that's mentioned in
our sources. Nanome. Yeah. It helps scientists
visualize all this complex SAR data in a completely
new way. Oh, that's right. I've seen some demos
of that. It's pretty wild. So can you imagine
being able to like walk through a molecule? Yeah.
Seeing its 3D structure and actually manipulating
its atoms all in virtual reality? Yeah, it's
pretty mind blowing. It sounds like something
out of science fiction. So how does this visualization
actually help with SAR studies? Well, think about
it. Traditionally, SAR data is represented in
2D. Which isn't bad, but it's not the best when
you're trying to understand these really complicated
3d interactions between a drug and its target
So it's like the difference between looking at
a flat map of a city Yes, exactly versus actually
being able to walk through the streets in 3d
That's a great way to put it. By actually being
able to see those interactions in VR, researchers
can get a much deeper understanding of how changing
the molecule might affect how the drug behaves.
Yeah. It's not just about seeing the molecule.
It's about understanding how it works in that
3D space. Exactly. It's about the relationships,
the interactions, and all of that can lead to
faster and more effective drug design. It really
is amazing how much technology is changing the
way we do science, huh? For sure. Okay, so just
to quickly recap what we've talked about so far.
We started with the basics of SAR, which is all
about the relationship between a drug's structure
and its activity. And we saw how even tiny changes
can have a huge impact on a drug's potency and
selectivity. We also talked about how challenging
it can be to optimize a drug for all those different
parameters. Yes, so many things to consider.
Like efficacy, toxicity, solubility, all that.
Right. And we're seeing how technology like AI
and VR are really revolutionizing drug discovery.
They really are. It's a really exciting time
to be working in this field. Absolutely. Now
let's move on to another important aspect of
this whole process. the challenges and considerations
in preclinical drug development. Oh, yeah, that's
where things start to get real. Exactly. It's
that crucial step before we can even think about
testing a drug in humans. Absolutely. It's all
about making sure that a potential drug is safe
and effective before we start giving it to people.
Couldn't agree more. Now, the material delves
into all sorts of things about preclinical development.
But one thing that really caught my eye was this
idea of metabolic soft spots. Oh, right. We touched
on that briefly earlier. Yeah, we did. It seems
super important in the context of preclinical
testing, though. You're right. It is. So a metabolic
soft spot is basically a part of a drug molecule
that's really vulnerable to being broken down
by enzymes in the body. OK. So if a drug gets
metabolized too quickly, it might not be able
to reach its target. Exactly. It might not be
able to stick around long enough to actually
do its job. That makes perfect sense. So I guess
that's where the modifications come in again.
You got it. Scientists can tweak the molecule
to make it more stable. So they might add something
bulky to protect that vulnerable area. Yeah.
Or adjust the chemical bonds to make it harder
for enzymes to break it down. I see. It's like
reinforcing those weak points so the drug can
survive the journey through the body. Exactly.
It's amazing how much goes into these preclinical
studies. It's like a whole detective investigation
before you can even move on to the next stage.
I love that analogy. It's so true. It really
highlights how important this stage is in drug
development. All right. Let's pause here for
a second. We'll be right back. Welcome back,
everyone. So before we move on to clinical trials,
I think we should dig a little deeper into these
preclinical studies. You know, they're really
crucial in figuring out if a drug candidate is
ready for the next stage. Totally. And you were
talking about metabolic soft spots earlier, which
seems to be a big focus in these preclinical
evaluations. It kind of sounds like researchers
are in this constant battle with the body's metabolic
processes, right? Yeah, that's a great way to
put it. Our bodies are incredibly efficient at
breaking down anything they see as foreign, including
drugs. Right. So a big challenge in drug design
is creating molecules that can survive those
metabolic attacks, at least long enough to reach
their targets and do what they're supposed to
do. So basically identifying and fixing those
soft spots is like... essential for a drug to
actually be effective. Exactly. Imagine you build
this powerful engine, but it's made of a material
that just falls apart under stress. Oh, okay.
You wouldn't want to put that engine in a car,
right? No, definitely not. It's the same with
drugs. If it gets metabolized too quickly, it
might not even have a chance to work. That makes
sense. So I'm guessing that's where those modifications
come in again, right? Like tweaking the molecule
structure so it's tougher. Exactly. We can try
to reinforce those soft spots by adding, say,
a bulky group that kind of shields the vulnerable
area. OK. Or maybe adjust the chemical bonds
a bit to make it harder for those enzymes to
break it down. So it's all about making the drug
more stable and increasing its chances of success,
basically. Right. It's like giving it armor.
Now, these preclinical studies involve a whole
bunch of different tests and analyses. And aside
from metabolism, we're also super interested
in something called the ADME profile. ADME. It
stands for absorption, distribution, metabolism,
and excretion. OK. And all of these factors determine
how a drug moves through the body, how it gets
to its target, and how it's eventually eliminated.
So it's basically mapping the drug's journey
through the body from start to finish. precisely,
and each step in that journey can impact how
effective and safe a drug is. Like if a drug
isn't absorbed well, it might not reach a high
enough concentration in the blood to do anything.
Right. Or if it's distributed too widely, it
could start messing with other tissues and causing
side effects. That makes sense. So it's a real
balancing act to get all these things just right.
Oh, yeah. It's super complex. And that's why
these preclinical studies are so important. They
give us tons of info that helps us refine the
drug's formulation, figure out the best dose,
and ultimately decide if it's even worth it.
moving on to clinical trials. Right, those trials
are the next big step. That's where we actually
see how the drug works in people, in the real
world. Exactly. But before we jump ahead, there's
one more challenge that often pops up during
preclinical development, especially when we're
dealing with drugs for brain disorders. Oh, are
you talking about the blood -brain barrier? Bingo!
That's the one. It's an amazing protective mechanism.
It keeps all sorts of harmful substances out
of our brains. But it also makes it really hard
to get drugs into the brain. It's like a fortress
around the brain keeping the bad stuff out. Yeah.
But also making it tough for the good stuff to
get in. Perfect analogy. The blood brain barrier
is super picky about what it lets through. So
designing drugs that can actually cross this
barrier and hit their targets in the brain is
a huge challenge. So how do scientists even begin
to tackle that? Well, one approach is to make
drugs that are small and lipophilic. That means
they like to dissolve in fats. And that helps
them slip through those fatty membranes that
make up the blood -brain barrier. So it's kind
of like designing a key that fits both the lock
on the gate and the lock on the trachea chest
inside. I love that. But yeah, it's tricky. We
also need to make sure the drug still retains
those chemical properties that actually make
it effective against its target. That sounds
incredibly difficult. It is, but researchers
are always coming up with new strategies like
using nanoparticles as carriers or even designing
molecules that can kind of trick the barrier
into letting them through. Wow, it's amazing
what scientists can do. It really is. It shows
just how dedicated they are to finding treatments
for these really complex brain disorders. Okay,
let's take a quick break here. When we get back,
we'll finally dive into those much anticipated
clinical trials. All right, we're back and ready
to tackle the final stage of drug development.
clinical trials. This is where we move from the
lab to real people, right? It's where we really
see if a drug can live up to its potential. You
got it. It's where the rubber meets the road.
All that research, all those preclinical studies,
it all comes down to this. Can this drug actually
help patients? So clinical trials are usually
broken down into different phases, each with
its own goals. Can you walk us through those?
Of course. Clinical trials are very carefully
designed. We want to be sure we're evaluating
a drug's safety and how well it works while keeping
the participants safe. It all starts with phase
one, which is really all about safety. OK. We
start with a small group of healthy volunteers
just to figure out the safe dosage range and
see if there are any side effects. So it's like
we're easing into it, right? Making sure it's
OK before we go any further. Yeah, exactly. We
just want to see how the drug is handled by the
body. Watch out for any bad reactions. Once we're
comfortable with the safety profile, we move
on to phase two. And is that when we start testing
on people who actually have the condition the
drug is supposed to treat? Right. In phase two,
we include folks who have the specific disease
we're targeting. And the goal here is to get
an early look at how effective the drug is. Does
it actually seem to work? We're also still keeping
a close eye on safety, of course, and fine tuning
the dosage. So it's kind of like a pilot study,
right? A smaller test run before the big one.
Exactly. If things look good in phase two, you
know, if the drug seems safe and effective, then
we can move on to phase three. And this is the
big leagues, right? Big trials with lots of people,
the whole nine yards, the real test. Exactly.
Phase three trials are the most rigorous and
extensive. We often have thousands of participants
at different sites. And the goal is to confirm
that the drug really... does work, check for
any rare side effects that might have been missed
before, and see how it compares to other treatments
or a placebo. Oh, right, the placebo. That's
the sugar pill, right? That's the one. It's an
inactive substance. We use it as a control just
to be extra sure that any positive effects we're
seeing are truly due to the drug and not just,
you know, in people's heads. Makes sense. You
got to be thorough. So all this data from phase
three, that's what the FDA looks at, right? Right.
The FDA wants to make sure that any drug that
goes out to the public is both safe and effective.
They'll review all the data from the trials really
carefully before deciding whether to approve
it. It sounds like such a long and demanding
process. Oh, it definitely is. But it's essential.
It's all about protecting public health. We want
to be sure that any therapies that are available
have been thoroughly tested and are as safe as
possible. Totally agree. And so even after a
drug is approved, the monitoring doesn't stop
there, does it? Nope. It's an ongoing process.
Even once a drug is on the market, it's continuously
monitored for any long term or delayed side effects
that maybe didn't show up during trials. So it's
really this constant cycle of evaluation and
improvement. all with the goal of creating safer
and better treatments. Exactly. It's all about
pushing forward, always learning, always looking
for ways to do better. Well, this has been an
amazing journey. We started at the molecular
level talking about how even small changes can
have a huge impact on a drug's behavior. Right.
Those SARS are where it all begins. Exactly.
And then we moved all the way up to these large
-scale clinical trials, where we see a drug's
true potential. It's been a fascinating look
at how far drug development has come, from traditional
SAR studies to those incredible new tools like
AI and VR. It really makes you appreciate the
sheer amount of work and dedication that goes
into bringing new treatments to people who need
them. Absolutely. It's a truly amazing collaborative
effort, all driven by that desire to improve
human health. Couldn't have said it better myself.
A big thank you to our expert for walking us
through all of this. And to our listeners, we
hope you enjoyed this deep dive into medicinal
chemistry. Until next time, stay curious.

Chapters

No chapters available.