Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5262_Библиотеки_им_академика_М_И_Перельмана.pdf
3 General Terms and Concepts in Medicinal Chemistry48
Many pharmaceutical drugs function as enzyme inhibitors, targeting either
malfunctioning human enzymes or those vital for the survival of pathogens like
viruses, bacteria, or parasites. For instance, methotrexate is used in chemotherapy
and to manage rheumatoid arthritis, while protease inhibitors, such as darunavir,
are employed in the treatment of HIV/AIDS.
3.8 Activator
Activators are molecules that increase the activity of enzyme. While the majority
of drug discovery efforts are mainly focused on enzyme inhibition, small-molecule
activators of enzymes remain a relatively less explored area. From therapeutic
point of view, it is often beneficial to enhance the expression of certain enzymes
whose low expression is responsible for the observed ailment. Small molecules as
activators of several enzymes have great biological potential as antimicrobial and
anticancer agents, for the treatment of diabetes, obesity, metabolic disorders, and
for the treatment of neurological disorders including Alzheimer’s disease [22].
3.9 Drug Design
Drug design, also referred to as rational drug design or simply rational design, is
the innovative process of discovering new drugs by leveraging knowledge about
biological targets. Typically, the drug is a small organic molecule that either activates
or inhibits the function of biomolecules, such as proteins, to deliver therapeutic ben-
efits to patients. At its core, drug design involves creating molecules whose shape
and charge complement the biomolecular targets they interact with, enabling them
to bind effectively. While not always required, drug design frequently utilizes com-
puter modeling techniques, a practice known as computer-aided drug design.
When the process is guided by the three-dimensional structure of biomolecular
targets, it is termed as structure-based drug design. Beyond small molecules,
biopharmaceuticals—including peptides and, notably, therapeutic antibodies—have
emerged as a significant class of drugs. Computational methods have also been
developed to enhance the affinity, selectivity, and stability of these protein-based
therapeutics.
The process of identifying small molecules that interact with a specific target
typically starts with screening a library of potential drug compounds. This screen-
ing can be conducted using various assays. Furthermore, if the target’s structure is
N
N
N
N
N
N
H
O
Methotrexate
Darunavir, a protease inhibitor
S
N
O
O
H
N
HO
O
O
O
O
H
H
CO
2
H
CO
2
H
NH
2
H
2
N
NH
2
3.10 Ligand-based Drug Design 49
known, virtual screening of drug candidates can also be employed. Ideally, these
candidate compounds should exhibit “drug-like” properties, meaning they should
have characteristics that promote oral bioavailability, sufficient chemical and
metabolic stability, and low toxicity. Various methods are available to assess drug
likeness, including Lipinski’s rule of five and other scoring systems, such as
lipophilic efficiency [23]. Additionally, numerous approaches for predicting drug
metabolism have been proposed in scientific research [24].
Given that numerous drug properties need to be optimized simultaneously
during the design process, multi-objective optimization techniques are often uti-
lized. However, due to the constraints of current activity prediction methods, drug
design remains significantly reliant on serendipity and bounded rationality [25].
In an ideal scenario, computational methods would accurately predict the binding
affinity of a compound before it is synthesized, theoretically eliminating the need
for multiple iterations and significantly reducing both time and cost. However,
the reality is that current computational approaches are not flawless and, at best,
can only offer qualitatively reliable estimates of affinity. As a result, the drug dis-
covery process typically involves numerous cycles of design, synthesis, and testing
before the optimal compound is identified. Despite these limitations, computational
methods play a crucial role in accelerating discovery by minimizing the number of
required iterations and often suggesting novel molecular structures [26, 27]. Recent
advancements in this field have been comprehensively reviewed in two articles,
which highlight progress in drug design and its practical applications [28, 29].
Artificial intelligence (AI) is revolutionizing every stage of the drug discovery pro-
cess [30, 31, 32]. In drug design, AI is employed to predict protein 3D structures,
drug–protein interactions, and drug activity, enabling the creation of novel molecules
from scratch. In pharmacology, AI facilitates the design of targeted molecules and
multi-target drugs. Within chemical synthesis, AI aids in planning synthesis path-
ways, forecasting reaction yields, and deciphering reaction mechanisms. Additionally,
AI excels at repurposing existing drugs for new therapeutic applications. Undoubtedly,
AI plays an indispensable role in drug screening by predicting toxicity, biological
activity, absorption, distribution, metabolism, and excretion (ADME) properties, and
physicochemical characteristics, among other critical factors.
3.10 Ligand-based Drug Design
Ligand-based drug design, also known as indirect drug design, utilizes
information about molecules that interact with a specific biological target. These
molecules serve as the foundation for developing pharmacophore models, which
outline the essential structural characteristics required for a molecule to bind
effectively to the target [33]. By analyzing the binding properties of these mole-
cules, a model of the biological target can be constructed, enabling the design of
new compounds that can interact with the target. Another approach involves the
use of QSARs, which establish correlations between the molecular properties of
compounds and their experimentally measured biological activities. These QSAR
models can then be applied to predict the biological activity of new, structurally
similar compounds [34].
3 General Terms and Concepts in Medicinal Chemistry50
3.11 Structure-based Drug Design
Structure-based drug design, also known as direct drug design, depends on
understanding the three-dimensional structure of a biological target, typically
determined through techniques like X-ray crystallography or nuclear magnetic res-
onance spectroscopy [35]. When the experimental structure of the target is unavail-
able, a homology model of the target can be constructed using the known structure
of a related protein. With the target’s structure in hand, medicinal chemists can
employ interactive visualization tools and their expertise to design potential drug
candidates that are expected to bind to the target with high affinity and selectivity.
Additionally, automated computational methods can be utilized to propose novel
drug candidates [36].
Current structure-based drug design methods can be broadly divided into three
main categories [37]. The first approach is to identify new ligands for a given receptor
by searching large databases of small-molecule 3D structures to find ligands that
fit into the receptor binding pocket using fast approximate docking programs. This
method is called virtual screening. The second category is the de novo design of new
ligands. In this method, ligand molecules are constructed within the constraints of
the binding pocket by stepwise assembly of small fragments. These fragments can
be single atoms or fragments of molecules. The main advantage of this approach
is that novel structures not included in any database can be proposed [38, 39, 40].
A third approach is to optimize known ligands by evaluating proposed analogs
within the binding cavity [37].
3.12 Lipinski’s Rule of Five
Lipinski’s Rule of Five, also known as Pfizer’s Rule of Five or simply the Rule
of Five (RO5), is a rule of thumb for evaluating druglikeness or determining
whether a compound with a certain pharmacological or biological activity has the
following chemical and physical properties: likely making it an orally active drug for
humans. This rule was developed by Christopher A. Lipinski in 1997 and is based on
the observation that most oral drugs are relatively small and moderately lipophilic
molecules [41, 42].
The rules describe the molecular properties important for the pharmacokinetics
(PK) of drugs in humans, including their ADME. However, this rule does not
predict whether a compound is pharmacologically active.
Lipinski’s rule states that, in general, an orally active drug has no more than one
violation of the following criteria [41]:
• No more than five hydrogen bond donors (the total number of nitrogen–
hydrogen and oxygen–hydrogen bonds)
• No more than 10 hydrogen bond acceptors (all nitrogen or oxygen atoms)
• A molecular mass less than 500 Daltons
• A calculated octanol–water partition coefficient (Clog P) that does not exceed 5
3.13 Lead Compound 51
In the drug discovery process, it is crucial to adhere to this rule when optimizing
pharmacologically active lead compounds in a stepwise manner. The goal is to
enhance both the activity and selectivity of these compounds while ensuring that
their physicochemical properties remain consistent with drug-like characteristics,
as outlined by Lipinski’s rule. Drug candidates that comply with the RO5 generally
exhibit lower attrition rates in clinical trials, increasing their likelihood of success-
fully reaching the market.
It is crucial to recognize that not all small-molecule drugs conform to this prin-
ciple. The RO5 operates under the assumption that passive diffusion is the primary
mechanism for cellular drug uptake, overlooking the significant role of transporters.
In reality, only approximately 50% of orally administered new chemical entities
adhere to this rule [43].
Furthermore, research has shown that certain natural products, such as macro-
lides and peptides [44, 45, 46], defy the chemical criteria established by Lipinski’s
filters.
3.13 Lead Compound
In drug discovery, a lead compound is a chemical substance that exhibits phar-
macological or biological activity with potential therapeutic value. However, its
structure may not be optimal, necessitating modifications to better align with the
target. A lead compound serves as a foundation for further development and pro-
vides a basis for creating backup candidates for future drug launches. The chemical
structure of a lead compound acts as a starting point for structural optimization to
enhance properties such as potency, selectivity, or pharmacokinetic performance.
Moreover, newly discovered pharmacologically active compounds may lack
sufficient drug-like characteristics, requiring chemical adjustments to make them
suitable for biological or clinical evaluation. Prior to identifying lead compounds, it is
essential to select appropriate targets for rational drug design, based on biological rel-
evance. Alternatively, targets can be identified by screening potential lead compounds
against a range of biological targets to determine their efficacy and specificity [47].
Drug libraries are frequently evaluated using HTS methods, where compounds
are tested for their capacity to either inhibit (as antagonists) or activate (as agonists)
a specific receptor. Compounds that demonstrate activity are identified as “hits,”
and their selectivity is further assessed during this process.
A lead compound can originate from multiple sources. These compounds are typ-
ically discovered through the characterization of natural products, the use of combi-
natorial chemistry, or molecular modeling techniques such as rational drug design.
Additionally, chemicals identified as hits during HTS may also serve as potential
lead compounds. Once a lead compound is identified, it undergoes lead optimi-
zation (LO) to enhance its “drug-like” properties. During this process, Lipinski’s
RO5 is often applied to evaluate its suitability. Other considerations, such as the
feasibility of scaling up the chemical’s production, are also critical factors in the
optimization process.
3 General Terms and Concepts in Medicinal Chemistry52
3.14 Hit-to-Lead
A compound that exhibits the desired magnitude of effects in a HTS is referred to as
a hit. The procedure of identifying these hits is known as hit selection. Following
this, the hit-to-lead (H2L) stage, also termed lead generation, is a critical phase
in early drug discovery. During this stage, small-molecule hits identified from HTS
are assessed and undergo preliminary optimization to pinpoint promising lead
compounds. These lead compounds are then subjected to more comprehensive
refinement in the subsequent phase, known as LO. The drug discovery pipeline typ-
ically follows a sequential pathway that includes the H2L stage as a key step.
The process typically follows these stages: Target Validation (TV) → Assay
Development → HTS → H2L → LO → Preclinical Development → Clinical
Development.
The H2L stage begins with the confirmation and evaluation of initial screening
hits, followed by the synthesis of analog compounds (hit expansion). Typically, the
initial hits exhibit binding affinities for their biological target in the micromolar
range (10
−6
M). Through focused H2L optimization, the binding affinities of these
hits are often enhanced by several orders of magnitude, reaching the nanomolar
range (10
−9
M). Additionally, the hits undergo targeted optimization to improve
metabolic stability, enabling testing in animal disease models, and to enhance selec-
tivity against other biological targets. This selectivity optimization helps minimize
potential off-target interactions that could lead to undesirable side effects.
On average, just one out of every 5000 compounds that progress from drug dis-
covery to preclinical development ultimately gains approval as a marketed drug.
3.15 High-Throughput Screening
HTS is a method for scientific discovery especially used in drug discovery and rele-
vant to the fields of biology and chemistry [48, 49]. Using robotics, data processing/
control software, liquid handling devices, and sensitive detectors, HTS allows a
researcher to quickly conduct millions of chemical, genetic, or pharmacological
tests. Through this process, one can quickly recognize active compounds, anti-
bodies, or genes that modulate a particular biomolecular pathway. The results of
these experiments provide starting points for drug design and for understanding the
noninteraction or role of a particular location.
3.16 Pharmacophore
In the fields of medicinal chemistry and molecular biology, a pharmacophore rep-
resents an abstract framework of the essential molecular characteristics required for
the recognition of a ligand by a biological macromolecule. According to IUPAC, a
pharmacophore is defined as “an ensemble of spatial and electronic features that are
crucial for achieving optimal supramolecular interactions with a specific biological
target, thereby eliciting (or inhibiting) its biological response [50].” Pharmacophore
3.17 Affinity, Efficacy, and Potency 53
models provide insights into how structurally varied ligands can interact with a
shared receptor site. Furthermore, these models are valuable tools for discovering
new ligands that can bind to the same receptor, through either de novo design or
virtual screening approaches.
Historically, the modern notion of a pharmacophore gained prominence through
the work of Lemont Kier, who introduced the concept in 1967 [51] and later for-
mally used the term in a book published in 1971 [52].
3.17 Affinity, Efficacy, and Potency
Affinity is the tendency of one molecule to bind to another molecule. The affinity of
a drug refers to its ability to bind to its biological target (receptor, enzyme, transport
system, etc.). For pharmacological receptors, it can be thought of as the frequency at
which the drug will reside at the minimum free energy position within that recep-
tor’s force field when the drug enters the vicinity of the receptor by diffusion.
Efficacy is a measure of the maximum biological effect that a drug can produce
as a result of receptor binding. A compound with high affinity does not necessarily
mean high efficacy.
The potency of a drug refers to the amount of drug required to achieve a specific
biological effect—the smaller the dose needed, the more potent the drug. Potency
is a comparative rather than an absolute expression of drug activity. Drug potency
depends on affinity and efficacy. Thus, two agonists could be equipotent but have
different intrinsic efficacies with compensating differences in affinity.
An enzyme (E)-catalyzed biological reaction is the conversion of a substrate (S)
to a product (P).
When enzyme inhibitor drug (I) is added, it will compete with the substrate for
the enzyme’s active binding site. For an agonist (or for an antagonist), the numerical
representation of affinity is the reciprocal of the equilibrium dissociation constant
(k
d
) of the ligand–receptor complex denoted k
i
, calculated as the rate constant for
offset (k
off
) divided by the rate constant for onset (k
on
). k
i
is also referred as inhibi-
tion constant.
k
i
= k
off
/k
on
The smaller the k
i
value for I, the more potent the inhibitor. Another common
measure of inhibition is IC
50
, which is the concentration of inhibitor that produces
50% enzyme inhibition in the presence of substrate.
The half-maximal effective concentration (EC
50
) is a measure of the concentration
of a drug, antibody, or toxicant that induces a biological response between baseline
and maximum after a specified exposure time. More simply, EC
50
can be defined as
E
+
S
E S E P E
+
P
E + I
E I
k
on
k
off
3 General Terms and Concepts in Medicinal Chemistry54
the concentration required to obtain 50% effect. EC
50
is often used as a measure of
drug potency.
3.18 Structure–Activity Relationship
The SAR is the relationship between the chemical structure of a molecule and its
biological activity. The idea was first proposed at least as early as 1868 by A. C.
Brown and T. R. Fraser [53, 54].
SAR analysis enables the identification of chemical groups responsible for caus-
ing a target biological effect in an organism. This allows the effect or potency of
a bioactive compound (usually a drug) to be altered by changing its chemical
structure. Medicinal chemists use chemical synthesis techniques to insert new
chemical groups into biomedical compounds and test the biological effects of the
modifications.
This method has been modified to establish a mathematical relationship between
chemical structure and biological activity, called a QSAR [55].
In medicinal chemistry practice, once a pharmacophore is identified, the SAR is
usually performed by synthesizing several series of analogs of the lead compound.
3.19 Partition Coefficient and Log P/Clog P
The partition coefficient, abbreviated P, is defined as a particular ratio of the con-
centrations of a solute between the two solvents (a biphase of liquid phases), spe-
cifically for un-ionized solutes, and the logarithm of the ratio is thus log P. When
one of the solvents is water and the other is a nonpolar solvent, then the log P value
is a measure of lipophilicity or hydrophobicity. The defined precedent is for the
lipophilic and hydrophilic phase types to always be in the numerator and denomi-
nator, respectively; for example, in a biphasic system of n-octanol (hereafter simply
“octanol”) and water:
log P
oct/water
= log
10
([solute]
oct
/[solute]
water
)
The distribution coefficient of a drug plays a critical role in determining its ability
to reach the intended target within the body, the potency of its effect upon reaching
the target, and the duration it remains in its active form. As a result, the log P value
of a molecule is a key parameter considered by medicinal chemists during preclin-
ical drug discovery, particularly when evaluating the druglikeness of potential drug
candidates.
Measuring the log P of a compound requires its physical synthesis, which makes
it impossible to determine this property beforehand. To address this, computational
tools such as ClogP® v4.0 (BioByte Corp., 1999) and ACD/logPdb® v7.0 (Advanced
Chemistry Development Inc., Toronto, Ontario, Canada, 2003) have been developed
to predict the log P of compounds. The log P value estimated by these programs is
referred to as Clog P. According to Lipinski’s RO5, one of the criteria for an orally
active drug is that its Clog P should not exceed 5.
3.21 Preclinical Studies 55
3.20 Drug Candidate
A drug candidate is a compound that has shown potential to become a therapeutic
agent for the treatment of a specific disease or medical condition, whether because
it has sufficient target selectivity, drug-like properties, or sufficient potency. Once a
potential drug candidate is identified, rigorous preclinical studies are conducted to
evaluate its safety (toxicity), efficacy, PK, and pharmacodynamics (PD). This pre-
clinical stage involves testing drug candidates in labs and animal models to col-
lect data on their effects and potential risks. If a drug candidate successfully passes
preclinical testing, clinical trials may be conducted, which involve testing the drug
in human subjects to further evaluate its safety and effectiveness. Ultimately, if it
shows sufficient safety and efficacy in clinical trials, it may gain regulatory approval
to be marketed and used as a therapeutic drug.
Drug candidates are critical to healthcare because they represent entirely new
treatments or the potential to improve existing treatments. They can address unmet
needs and bring hope to diseases or conditions for which there are currently no
effective treatment options. New drugs can also address limitations of existing
drugs, such as reducing side effects, improving efficacy, or targeting specific patient
groups. However, only a small percentage of drug candidates make it through the
rigorous testing and approval process to become commercialized drugs. While the
journey from drug candidate to approved drug is challenging, their potential to
improve patient outcomes and advance medical knowledge makes them an impor-
tant part of healthcare progress.
3.21 Preclinical Studies
In the process of drug development, preclinical or nonclinical studies represent
a crucial phase of research conducted prior to clinical trials (which involve testing
in humans). During this stage, essential data on feasibility, iterative testing, and
drug safety are gathered, typically through experiments conducted on laboratory
animals.
Drugs may undergo PD (what the drug does to the body), PK (what the body
does to the drug), ADME, and toxicology testing. These data allow researchers to
allometrically estimate safe starting doses of drugs for use in human clinical trials.
Most preclinical studies must adhere to Good Laboratory Practices (GLP) in the
International Council for Harmonization of Technical Requirements for
Pharmaceuticals for Human Use guidelines before they can be submitted to
regulatory agencies such as the U.S. FDA.
Typically, both in vitro and in vivo testing will be performed. Drug toxicity
studies include which organs the drug targets and whether there are any long-term
carcinogenic or disease-causing toxic effects.
The information collected from these studies is vital so that safe human test-
ing can begin. Typically, in drug development studies, animal testing involves two
species. The most commonly used models are murine and canine, although primate
and porcine are also used.
3 General Terms and Concepts in Medicinal Chemistry56
3.22 Toxicity
One of the initial steps in evaluating a new drug candidate is assessing its potential
toxicity. This process usually starts with in vitro testing using genetically engineered
cell cultures and/or in vivo testing on genetically modified mice to study its impact on
cell reproduction and identify possible carcinogenic effects. Additionally, the drug is
tested for acute toxicity by administering a dose large enough to induce toxic effects or
death within a short timeframe. These studies often involve multiple animal species,
and the animals are later dissected to determine if specific organs were affected.
Following this, further acute toxicity studies are conducted over several months,
during which the drug is given to experimental animals at doses designed to cause
toxicity without being lethal. Throughout this period, blood and urine samples are
collected and analyzed. At the end of the study, the animals are euthanized, and
pathologists examine their tissues for signs of cellular damage or cancer.
Finally, long-term toxicology trials are carried out over several years at lower dose
levels to evaluate the drug for chronic toxic effects, carcinogenicity, specific tox-
icological impacts, mutagenicity, and reproductive abnormalities. These compre-
hensive studies are critical to ensuring the safety and efficacy of the drug before it
progresses to human trials.
There are two types of data used to measure drug toxicity. One is the LD
50
value,
which is the lethal dose required to kill 50% of a group of animals. The other is the
ED
50
, which is the dose required to produce the desired effect in 50% of the animals
tested. The ratio of LD
50
to ED
50
is called the therapeutic ratio or therapeutic index.
3.23 Pharmacokinetics and Pharmacodynamics
PK is a field within pharmacology focused on understanding how the body processes
a drug following its administration. It involves the study of chemical metabolism
and traces the journey of a drug from the moment it enters the body until it is fully
eliminated. PK relies heavily on mathematical models, with a particular focus on
the relationship between the concentration of a drug in the bloodstream and the
time that has passed since the drug was administered.
PD examines the effects of a drug on the body and how these effects are produced.
Together with PK, PD plays a crucial role in determining drug dosing, therapeutic
benefits, and potential adverse effects, as illustrated in PK/PD models.
3.24 Absorption, Distribution, Metabolism,
and Excretion
ADME is primarily used in the fields of PK and pharmacology. These four terms
represent key processes that describe how a drug interacts with the body over time.
Absorption/administration describes how a drug enters the body. Absorption
relates to the movement of a drug from the administration site to the bloodstream.
There are four main routes of administration:
3.25 Bioavailability 57
• Ingestion through the digestive tract;
• Inhalation via the respiratory system;
• Dermal application to the skin or eye;
• Injection through direct administration into the bloodstream.
Only injected compounds enter the systemic circulation directly. For drugs to be
administered by ingestion, inhalation, or skin contact, the chemical must cross a
membrane before entering the bloodstream.
Distribution: Once a drug is absorbed, it moves from the site of absorption to
surrounding tissues in the body. This distribution from one part of the body to
another is usually accomplished through the bloodstream, but can also occur from
cell to cell. Researchers examine where chemicals travel, how quickly they reach
certain locations, and how widely they are distributed to help determine efficacy.
Some compounds move easily, while others do not. Factors such as blood flow, lipo-
philicity, tissue binding, and molecular size influence distribution.
Drug metabolism refers to the process in which drugs are biotransformed
through organs or tissues (mainly liver, kidney, skin, or digestive tract) so that drugs
are excreted from the body. To facilitate elimination through feces or urine, drug
compounds are altered to be more soluble in water. Chemical metabolism can lead
to toxicity, such as the production of damaging by-products or toxic metabolites.
Scientists map out specific metabolic pathways of candidate drugs, called adverse
outcome pathways (AOPs). AOPs provide the data needed to determine the poten-
tial safety or toxicity of a drug.
Excretion is the process of elimination of the metabolized drug compounds
from the body. The researchers wanted to know how quickly the drug was excreted
and how it was excreted from the body. Most drugs are excreted in feces or urine.
Other excretion methods include excretion of sweat molecules through the lungs or
through the skin and affects the cargo excretion pathway. Not all drug compounds
are completely excreted. Adverse effects may occur when chemical or metabolic
by-products bioaccumulate. Lipid-soluble compounds are more likely to bioaccu-
mulate than soluble compounds.
DMPK is the abbreviation of drug metabolism and pharmacokinetics studies.
3.25 Bioavailability
Bioavailability is a specific aspect of absorption, representing the percentage (%)
of an administered drug that successfully enters the systemic circulation. By defini-
tion, when a drug is administered intravenously, its bioavailability is 100%. However,
when drugs are delivered through other routes (e.g., oral, intramuscular, etc.), their
bioavailability is reduced due to factors such as absorption through the intestinal
epithelium and first-pass metabolism. Mathematically, bioavailability is calculated
as the ratio of the area under the plasma drug concentration–time curve (AUC)
for an extravascular formulation compared to the AUC for an intravascular (intrave-
nous) formulation. AUC is used as a measure because it is directly proportional to
the amount of drug that reaches the systemic circulation.