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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5728_Библиотеки_им_академика_М_И_Перельмана
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cule. The atom-based method can produce a large number of novel molecules that
can act as potential drug molecules against the drug target. The only disadvantages of
the method are its complexity, time, and cost due to which these methods are seldom
used nowadays and are replaced by the fragment-based approach of de novo drug
designing. Earlier, programs such as LEGEND, GENSTAR, and GROWMOL were em-
ployed for the atom-based de novo drug designing.
b. Fragment-based metho d of de novo drug designing: This is the most common
and widely accepted method for the de novo designing of the drug molecules. In this
approach, small fragments are placed inside the interaction sites of the cavity and
then a novel molecule is designed based on these interaction points (Fig. 11.7).
Fragments are defined as small organic molecules with lower molecular weight,
high solubility, and high affinity toward the interaction sites of the cavity of the target
proteins. The fragments used in the molecule designing can either be in cyclic or ring
form, depending upon the requirement of the binding site. As Lipinski’s rule of five
was used for the drug-likeness of the larger drug molecules, Congreve et al. in 2003
proposed the rule of three for defining the properties of the small fragments. As per
the Congreve rule of three, smaller fragments should have the following properties:
– The molecular weight of the fragment should be equal to or less than 300 Da.
– The calculated c log P of the fragment should be equal to or less than 3.
– The number of hydrogen bond acceptors/donors should equal to or less than 3.
Along with these three rules, additional filters can also be applied to obtain more
drug-like fragments which include:
– The number of rotatable bonds in the fragment should be equal to or less than 3.
– The polar surface area of the fragment should be equal to or less than 60 Å square.
For constructing the fragments along the binding site of the target protein to obtain
potent novel drug molecules, different strategies are employed (Fig. 11.8). The main
approaches employed for this purpose are:
– Linking of the fragment: In this approach, fragments are first placed inside the
cavity as per their affinity with the interaction sites. They are then linked to-
gether with small linkers. Linkers generally consist of nonpolar organic alkyl
groups such as methyl, propyl, and isopropyl groups.
– Merging of the fragments: This is another approach for creating the novel drug
molecule from the small fragments. Contrary to the linking, in this approach,
merging is performed, rather than linking, for creating the novel drug molecule.
This can be best understood by considering one fragment having a carboxylic
acid (COOH) group and another amino (NH
2
) group is attached (Fig. 11.9). Instead
of using the linker, merging will be done by the removal of a water molecule. The
resultant molecule will have an amide group (CONH).
11.2 Classification of de novo drug designing 259
– Growing of the fragments: In this approach, initially, a single fragment is placed
at one interaction site of the cavity and then other fragments are grown along the
binding site.
c. Different strategies for finding the best fragments: Scree ning of the fragments
for the construction of a potent novel drug molecule is of utmost importance to get an
efficient drug candidate molecule. This selection of the best fragments for the particu-
lar target protein is done from a pool or database of the fragments. There are several
Fig. 11.8: Use of different approaches such as linking, merging, and growing of fragments to obtain a
novel active drug against a particular drug based on the active cavity of the receptor.
Fig. 11.9: The merging approach of the fragment-
based method of the de novo drug designing.
260 Chapter 11 De novo drug designing approaches
methods through which these fragment molecules are screened for their b inding to
the interaction sites of the cavity.
– Performing direct binding assays of the fragments with the target protein
This is the straightforward pathway for assessing the binding of the fragments
within the cavity of the target protein. The major limitation of this methodology is
that these fragments have low affinity to the target protein when assessed individu-
ally. To overcome this issue, the binding of these fragments is evaluated at a very
high concentration. Fragments that show the best binding at the interaction site of
the cavity are selected for the further generation of the novel drug molecule.
– Nuclear magnetic resonance (NMR)-based screening
In this approach
15
N-labeled protein molecule is used for screening purposes. A
groupoffragmentsisallowedtobindwiththis
15
N-labeled target protein and
their position of binding is assessed through NMR spectroscopy. Fragments that
bind inside the cavity of the target protein and are adjacent to each other are se-
lected for further novel molecule generation.
– Mass spectrometry-based screening
This is another approach for the selection of the best fragments for de novo design-
ing of the molecules. Electrospray ionization mass spectrometry (ESIMS) is the choice
of method for this type of screening of the fragments. With the ESIMS approach, frag-
ments that bind covalently and noncovalently are distinguished from the pool of the
fragments. The fragments showing the best binding in a noncovalent manner are se-
lected further for the designing of the potent novel drug molecule.
– X-ray crystallography-based screening
With the advancement in the technology of X-ray crystallography, it has become
highly capable of assessing the binding of the small fragments inside the cavity of
the target protein. These X-ray crystallographic methods have become so power-
ful that despite being small affinity of the fragments as compared to the lead mol-
ecules, they are still capable of finding the best bound fragments.
Fragment-based de novo drug designing is the most widely used method for novel po-
tent drug molecule generation. The most common software used for performing this
task is LUDI, which was first introduced in the year 1992.
11.2.1.5 Assessing the binding strength of the designed molecules
In this step, the molecules that are obtained from the previous step of designing are
further evaluated for their binding in the active site of the target protein. The evalua-
tion of the binding of these newly designed molecules is done with the help of various
computational approaches such as molecular docking or molecular simulations. Out
of these two methods, molecular docking finds a special place due to its high popular-
ity and ease of performance along with being less time-consuming. The ranking of the
11.2 Classification of de novo drug designing 261
designed molecules is performed through the outcome of molecular docking results,
based on any of these scoring algorithms:
– Physics-based scoring
– Empirical-based scoring
– Knowledge-based scoring
– Machine learning-based scoring
The choice of the type of scoring function is totally dependent on the choice of the
individual researchers. Details of these scoring methodologies are already discussed
in Chapter 6 of this book.
11.2.1.6 Optimizing the probable hits for the absorption, distribution, metabolism,
excretion, and toxicology (ADMET) profile
Having high potency is not the sole requirement for any probable drug candidate. It
is the pharmacokinetic profile of the molecule that plays an equally important role in
a successful drug candidate. It is a fact that it is the concentration of the drug at the
site of action that decides its pharmacological action; hence, having an optimum ab-
sorption, distribution, metabolism, excretion, and toxicology (ADMET) profile is of ut-
most importance for any potent drug candidate. Therefore in the next step, the
ADMET profile of the novel molecules that have high affinity to the target receptor is
assessed. Based on the ADMET profile, these molecules are further optimized or dis-
carded from further study. The two m ost popular web servers for assessing the
ADMET profile of any molecule are SwissADME and ADMETlab 2.0.
11.2.1.7 Synthesis and in vitro analysis of the most promising candidates
This is the final step of the de novo drug designing process in which the first synthetic
route for the molecules that shows high affinity and good ADMET profile is investi-
gated. Once the optimum synthetic route is decided, the synthesis of these molecules
is performed. The synthesized molecules are then put under in vitro evaluation for
the validation of the in silico results. The novel candidates that show good activity in
the in vitro testing can be further evaluated for in vivo testing and clinical trials.
11.2.2 Ligand-based de novo drug designing approach
Ligand-based de novo drug designing is a strategic approach in drug dis covery that
focuses on developing new therapeutic compounds based on the characteristics and
properties of known ligands or molecules that interact with a specific target of inter-
est, typically a protein associated with a disease. Unlike structure-based methods that
rely on the knowledge of a target’s three-dimensional structure, ligand-based de novo
drug design starts with the identification of a reference ligand or set of ligands known
262 Chapter 11 De novo drug designing approaches
to bind to the target. The central concept behind this approach is to extract essential
structural and chem ical features from the reference ligands and use them as a tem-
plate for generating entirely new molecules with the potential to interact effectively
with the target. Computational tools, such as molecular modeling and chemoinfor-
matics, play a pivotal role in this process, allowing researchers to analyze and manip-
ulate molecular structures to design ligands that mimic the key interactions observed
in the reference compounds.
Ligand-based de novo drug design is particularly valuable when the 3-D structure
of the target protein is unknown or difficult to obtain. It leverages the wealth of exist-
ing ligand–target interaction data and can be a versatile strategy for optimizing drug
candidates to improve binding affinity, selectivity, and pharmacokinetic properties.
This approach significantly accelerates the drug discovery process by starting with
validated ligands and tailoring new molecules based on their proven biological activ-
ity [27–30].
The goal of this approach is also the same as that of the structure-based approach,
which is to develop a novel drug molecule. The only difference is that it is based on
designing the novel drug molecule from the information gathered from the already
active ligands against the particular drug target. The basic flow diagram of the ligand-
based de novo drug designing approach is given in Fig. 11.10. All the steps in the li-
gand-based de novo drug design are similar to the structure-based de novo design ex-
cept for the first two steps.
11.2.2.1 Searching for the active ligands
This is the very first step in the ligand-based de novo designing approach. The active li-
gands against the target disease are obtained from the literature. The active known com-
pounds are selected based on their biological activity value that is already reported.
11.2.2.2 Obtaining the pharmacophore from the active compounds
This is the most crucial step of the ligand-based de novo drug designing approach. A
pharmacophore is defined as an “ensemble of the essential features of the molecules
in 3-D to produce a desired pharmacological response.” There are several computa-
tional tools available for generating the pharmacophore from the active ligands. The
most popular software and web servers for obtaining the pharmacophore from the
ligands are PHASE, MOE, CATALYST, PHARMAGIST, PHARMER, and LIGANDSCOUT.
Figure 11.11 depicts a pharmacophore developed from the three known com-
pounds (physostigmine, neostigmine, and rivastigmine) against acetylcholinesterase
enzyme. The pharmacophore is developed from the online web server of Pharmagist
and the visualization is done from the ZINCpharmer web server. The green ring in
the pharmacophore represents the hydrophobic regions of the pharmacophore, the
orange ring represents the hydrogen-bond acceptor area, and the purple ring repre-
sents the aromatic ring, essential for acting on the acetylcholinesterase enzyme.
11.2 Classification of de novo drug designing 263
Fig. 11.10: The overview of the basic steps involved in the process of the ligand-based de novo drug designing approach.
264 Chapter 11 De novo drug designing approaches
The remaining steps in the ligand-based de novo drug designing from the designing of
the novel molecules to the synthesis of these molecules are similar to that of the struc-
ture-based de novo drug designing already discussed above. The only difference in
this approac h is that ins tead of interacti on sites of the cavity of the target protein,
pharmacophore constrain are employed for the designing of the novel molecules.
11.3 Advantages of de novo drug designing approaches
De novo drug design approaches in CADD offer numerous advantages, contributing to
the efficiency and effectiveness of the drug discovery process. Here are 10 major ad-
vantages of de novo drug design in CADD:
– Novelty: De novo design allows for the creation of entirely new drug candidates,
avoiding reliance on existing compounds, which can be particularly beneficial
when targeting novel or challenging diseases.
– Target flexibility: It can be applied even when the three-dimensional structure
of the target biomolecule is unknown or challenging to obtain, as it relies on li-
gand-based or fragment-based approaches.
– Cost-efficiency: By reducing the need for high-throughput screening of large
compound libraries, de novo design can save signif icant time and resources in
the drug discovery process.
– Customization: Researchers can tailor drug candidates to specific targets, opti-
mizing binding affinity, selectivity, and other pharmacological properties.
– Rapid iteration: De novo design allows for quick iterations and modi fications
of drug candidates in response to experimental results or changing project
requirements.
Fig. 11.11: An illustration of the pharmacophore developed through the ligand-based de novo drug
designing approach.
11.3 Advantages of de novo drug designing approaches 265
– Exploration of chemical space: It enables the exploration o f a broader range
of chemical space, leading to the discovery of diverse and innovative drug
candidates.
– Minimization of off-target effects: De novo design can focus on designing mole-
cules that interact specifically with the target of interest, reducing the risk of off-
target effects.
– Reduced side effects: By optimizing molecular properties, such as bioavailability
and toxicity, de novo-designed drugs can potentially have fewer side effects.
– Access to undruggable targets: It opens up opportunities to target previously
considered “undruggable” proteins or biomolecules by custom-designing ligands
with the desired properties.
– Intellectual property: De novo-designed compounds are often entirely novel,
which can lead to stronger intellectual property positions for pharmaceutical
companies.
These advantages make de novo drug design approaches a valuable tool in the arsenal
of CADD techniques, accelerating drug discovery, and enabling the development of
innovative and effective pharmaceuticals.
11.4 Limitations of de novo drug designing approaches
De novo drug design approaches in CADD have made significant strides but still face
several limitations:
– Limited understanding of complex biology: De novo methods heavily depend
on our knowledge of target proteins and their interactions, which may be incom-
plete or inaccurate, especially for novel or poorly characterized targets.
– Computational resources: Performing extensive molecular simulations, virtual
screening, and designing large chemical libraries can b e computationally inten-
sive, requiring high-performance computing infrastructure.
– Accuracy of predictive models: The accuracy of computational models used in
de novo design is contingent on the quality and quantity of available data, leading
to potential inaccuracies in predictions.
– Chemical space exploration: The vastness of chemical space makes it impossible
to exhaustively search for all potential drug candidates, potentially missing prom-
ising molecules.
– Protein flexibility: Protein structures can undergo conformational changes,
making it challenging to predict how they will interact with designed ligands
under various conditions.
– Lack of experimental validation: Predicted drug candidates from de novo de-
sign must be synthesized and exp erimentally validated, which can be time-
consuming and costly.
266 Chapter 11 De novo drug designing approaches
– Toxicity and side effects: De novo-designed compounds may have unforeseen
toxicities or side effects due to challenges in predicting their interactions with off-
target proteins.
– Bioavailability and pharmacokinetics: Predicting a molecule’s behavior within
a biological system, including absorption, distribution, metabolism, and excretion,
remains a complex task.
– Chemical synthesis challenges: The synthesis of novel compounds designed
through de novo methods can be intricate and may involve the development of
new chemical routes, adding complexity and cost.
– Regulatory hurdles: Meeting regulatory requirements for drug approval can be
challenging for de novo-designed drugs, as they often lack a historical safety and
efficacy profile.
Despite these limitations, de novo drug design remains a promising approach in
CADD, with ongoing advancements in computational techniques and an increasing
understanding of molecular biology. Researchers continue to address these challenges
to improve the efficiency and effectiveness of de novo drug design strategies.
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