Vol 4, Issue 2, 2022 (242-254)
http://journal.unpad.ac.id/idjp
*Corresponding author,
e-mail : karynelizabeth4621@gmail.com (K.Elizabeth)
https://doi.org/10.24198/idjp.v4i2.41005
2022 K.Elizabeth et al
Approaches for Drug Design and Discovery
Karyn Elizabeth1, Eri Amalia2
1Pharmacy Undergraduate Study Program, Faculty of Pharmacy, Universitas Padjadjaran ,
West Java, Indonesia
2 Department of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy,
Universitas Padjadjaran , West Java, Indonesia
Submitted : 30/07/2022, Revised : 02/08/2022, Accepted : 11/08/2022, Publis : 12/11/2022
Abstract
Drug discovery in general requires high costs and especially a very long time, which
is around 11-16 years. This is because drug development must go through a
complete series of research processes to obtain comprehensive data. However, in
line with the community's need for the availability of quality drugs, having good
efficacy and safety, the development of drug development technology using a
computing system is carried out. This is in line with the development of science and
collaboration between various disciplines. Approaches that can be used for
computational drug discovery include Structure-Based Drug Design and Ligand
Based Drug Design which are proven to accelerate and increase the possibility of
finding new drugs. This article aims to provide an overview of several approaches
to drug discovery development, especially the benefits of computational. The data
were collected from 28 primary published journals and 28 supporting literatures.
This article discusses the two computational methods, especially from the
application aspect which is expected to be useful in the field of drug discovery and
development to be more efficient in terms of time and cost. The traditional approach
to new drug development takes about 11-16 years but using computational methods
can shorten the drug discovery stage to 9-13 years.
Keywords: Drug Discovery, Ligand Based CADD, Structure-Based CADD
1. Introduction
The pharmaceutical industry and
educational institutions consistently find
and develop drugs for various diseases
according to the needs of the community in
improving their health. Drug discovery
efforts have been started since 450 M when
people have used plants and animals that
are thought to have certain compounds that
are efficacious in healing. At 2.5 M – 0.2M,
humans have discovered the medicinal
properties of natural products such as plants
and animals. 5000 years ago, medical
personnel were first recorded in Egyptian
papyrus scrolls using natural products for
treatment. In 1652, Nicholas Culpepper's
Herbs was published. Then in 1800,
synthetic organic chemical origins were
K.Elizabeth et al / Indo J Pharm 4 (2022) 242-254
243
identified such as quinine, aspirin, and
heroin. Furthermore, in 1900-1950, insulin,
penicillin, and streptomycin were
discovered. Continued in 1960-1970,
discovered hormone receptors and
recombinant DNA methods. In 1980, the
first targeted drug discovery and high-
throughput screening were carried out. The
discovery continued until 1990, there was a
human genome project and in the 21st
century, target-directed drug discovery is
still often the method of choice for drug
discovery [1]. This effort continues and
traditionally drug discovery will go through
a series of processes starting from the drug
discovery stage which takes between 3-5
years with research on extraction and
collection of compounds, target
identification, target validation,
development of compound assays, and
determination of potential compounds or
compounds. known as lead compounds.
The next stage is pre-clinical which takes 1-
2 years. At this stage the 250 selected
compounds will be further tested in terms
of in vitro and in vivo toxicity, the
determination of ADMET to determination
of pharmacokinetics/pharmacodynamics or
known as PK/PD. The next stage is the
clinical trial phase which consists of phase
I, phase II, and phase III clinical trials of 5
potential compounds which usually takes
about 6-7 years. In the final stage, when a
new drug compound has been determined,
product registration will be carried out to
obtain a distribution permit to be marketed.
After being marketed, monitoring and
evaluation of drugs are still carried out
which is known as pharmacovigilance
testing [2,3].
Efforts to find these drugs will
generally take 11-16 years or even more
than that. This is felt to be inefficient in
terms of cost and time, whereas currently
the medicines in question are very much
needed by the community. With the
development of science, a computational
system for drug discovery was developed
called SBDD and LBDD. This system
combines the results of research that has
been carried out on validated protein targets
and existing drugs, then attempts to use that
information to obtain compounds that are
suitable for specific disease protein targets.
These advances have reduced the time
required for the initial drug screening
period and hit to lead screening, so that time
and cost efficiencies in drug discovery can
be achieved [4].
2. Method
The method used in this article
review is to search the internet through
Google Scholar and the NCBI website (the
selected category is PubMed) with the
keywords "drug discovery process" drug
discovery and structure-based discovery"
"ligand-based drug discovery". The sources
used as references are national and
international journals and articles that
discuss keywords. The exclusion criteria
are articles that are not in accordance with
the topic of discussion, published more than
20 years, and lack of detailed information
about drug discovery and development. The
data were collected from 28 primary
published journals and 28 supporting
literatures.
K.Elizabeth et al / Indo J Pharm 4 (2022) 242-254
244
Figure 1. Flow Chart or Selection of Articles
3. Discussion
3.1 Drug Discovery
Drug discovery is the process of identifying
a molecule as a potential drug candidate.
The aim of this is to obtain one or more
candidate molecules that have biological
activity on a target that is relevant to disease
and safe for use/testing on humans as drugs.
It takes more than one drug candidate
compound because not all compounds can
meet the test criteria which are usually due
to safety, kinetics, potency, and other
factors. Drug discovery differs from drug
development which is a drug development
process carried out with preclinical and
clinical testing stages to evaluate the
activity and safety of a compound in which
a compound molecule must have
pharmacokinetic properties that allow a
consistent relationship between the drug
dose given, exposure, and binding drug at
the desired therapeutic target. The purpose
of this drug development is to get FDA
approval so that the drug can be marketed
[5,6].
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245
Figure 2. Drug Discovery & Development Timeline
The drug discovery process is a
challenge for the pharmaceutical industry
due to the time-consuming and high-cost
process. In general, the research and
development process take about 3-5 years,
preclinical testing takes about 1-2 years,
clinical trials take about 6-7 years and the
review and approval process takes about 1-
2 years as shown in Figure 2.
Initial processes in the early stages
of drug discovery are target identification,
target validation, hit and lead identification,
and lead optimization.
a. Target Identification
The first step in drug discovery
is to identify potential drug targets and
their role in treating a disease. A target
is generally a single molecule, such as
a gene or protein involved in a
particular disease. Identification of the
target begins with isolating the
function of the possible therapeutic
target and characterizing the molecule.
K.Elizabeth et al / Indo J Pharm 4 (2022) 242-254
246
Targets that are considered ideal are
targets that are efficacious, safe, and
meet clinical and commercial
requirements. The methods used for
target identification can be based on
the principles of molecular biology,
biochemistry, genetics, biophysics, or
other disciplines [7,8,9]. Approaches
used to target identification include
phenotypic screening, genetic
approaches such as expression cloning
techniques, in silico or chemical
proteomic-based approaches, and
genetic association studies [10,11].
b. Target Validation
Once a drug target has been
identified, a rigorous evaluation needs
to be carried out to demonstrate that
the target will have the desired
therapeutic effect. In the drug
discovery process, the main obstacle is
at this stage [12]. In general, target
validation is carried out by genetic
manipulation of the target gene (in
vitro) which involves knocking down
genes (shRNA, siRNA, miRNA),
knocking out genes (CRISPR), and
knocking genes (transfection of
viruses from mutant genes) using
antibodies that will interact with the
target with high affinity and block
further interactions and using genomic
chemistry which is a chemical
approach to genome-coding proteins
[13].
c. Hit and Lead Identification
In drug discovery, the
identification of the 'hit' molecule is
the starting point for the hit-to-lead
process. The ‘hit-to-lead’ phase is
usually a follow-up to high-throughput
(HTS) screening. A 'hit' molecule can
be identified by one or more of several
technology-based approaches such as
high throughput biochemical and
cellular assays, natural product testing,
structure-based design, peptides and
peptidomimetics, chemogenomics,
virtual bycatch, and literature and
patent-based innovations [14]. The
'lead' compound requires structural
activity relationships as well as the
determination of synthetic feasibility
and preliminary evidence of in vivo
activity and target involvement. To
reduce the number of compounds that
fail in the drug development process,
drug performance assessments are
often carried out. This assessment is
important to do to convert 'lead'
compounds into drugs. For a
compound to be considered a drug, a
compound must have the potential to
bind to a specific target and have a
good pharmacokinetic profile [15].
d. Lead Optimization
Optimization of 'lead'
compounds is a process to improve the
chemical structure of a drug candidate
after the initial lead compound has
been identified to improve its
characteristics as a drug candidate.
This process involves a series of
iterative syntheses and
characterizations of potential drugs to
build a representation of how chemical
structure and activity relate in terms of
interactions with targets and their
metabolism. Lead compounds were
evaluated by various aspects, including
selectivity and binding mechanism
during the optimization of lead
compounds. The purpose of this
optimization is to maintain the
beneficial properties while at the same
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247
time correcting deficiencies in the
structure of the 'lead' compound. In
addition, it is necessary to evaluate the
pharmacokinetic parameters,
pharmacodynamics, and toxicological
properties [16].
3.2 Preclinical Test
Preclinical testing is a drug
development process that evaluates the
safety and efficacy of drugs in animal
species to conclude prospective results in
humans. To carry out this test, approval
from the relevant regulatory authority is
required. Where regulatory authorities must
ensure that trials are carried out safely and
ethically and are only carried out for drugs
that are confirmed to be safe and effective.
Preclinical testing can be done in two ways,
namely general pharmacology and
toxicology. Pharmacology is concerned
with the pharmacokinetic and
pharmacodynamic parameters of drugs.
Toxicological studies of drugs can be
carried out by in-vitro and in-vivo assays
[17,18].
3.3 Clinical Trials
Clinical trials are tests on human
volunteers to answer questions about the
safety and efficacy of a new drug or
method. Clinical trials follow a specific
study protocol designed by the researcher
or manufacturer. During clinical trials,
researchers need to select patients with
predetermined characteristics, determine
the number of participants who take part in
the study, duration of testing, administer
treatment (dose and dosage form
administration), make parameter
assessments, and collect patient health data
for some time specific for later analysis.
The clinical trial consisted of 3 testing
phases where phase 1 was carried out on 20-
80 volunteers to evaluate safety and dosage,
phase 2 was carried out on 100-300
volunteers to evaluate efficacy and side
effects, and phase 3 was conducted on 300-
3000 volunteers to the monitoring of
efficacy and adverse drug reactions [9,19].
3.4 Product Registration to Get
Marketing Permit from the Food
and Drug Supervisory Agency
The New Drug Application (NDA)
aims to verify that a drug is safe and
effective for use in the person being
studied. It is necessary to include
everything about the drug from preclinical
data to phase 3 clinical trial data in the
NDA. In addition, it is necessary to include
labeling, security updates, patent
information, and instructions for use. Once
complete data is obtained for an NDA, it
will take the FDA approximately 6-10
months to decide to approve an NDA. If the
FDA has declared that a drug is safe and
effective for use, then the developer needs
to increase the information about the drug
by labeling it. Proper labeling determines
the basis for approval and direction for drug
use. Developers can choose to continue
further development or not and if the
developer objected to the FDA's decision,
an appeal could be made [20,21].
3.5 Approach Method with Computing
The computational approach method is
a computer-aided drug design technique
and is usually used for drug discovery such
as Structure-Based Drug Design and
Ligand Based Drug Design. Where
structure-based drug design consists of
structure-based virtual screening,
molecular docking, de novo drug design,
molecular dynamics, and pharmacophore
modeling. Meanwhile, ligand-based drug
design consists of QSAR, pharmacophore
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248
modeling, and ligand-based virtual
screening.
3.5.1 Structure-Based Drug Design
Structure-Based Drug Design
(SBDD) is a more specific, efficient, and
fast approach to leading compound
discovery and optimization. SBDD refers to
the systematic use of structured data such as
target macromolecules (receptors) which
are usually obtained experimentally or
through computational modeling. The aim
is to understand and design ligands in such
a way that they have high receptor binding
affinity. Drug targets are generally key
molecules involved in the metabolism or
cell signaling pathways of certain cells that
are known to have activity in certain
diseases [14]. Current SBDD methods
allow the design of ligands containing the
features required for efficient modulation of
target receptors [22,23]. Selective
modulation of drug targets validated by
high-affinity ligands interferes with certain
cellular processes which in turn leads to the
desired pharmacological and therapeutic
effects [24].
SBDD uses the geometric shape/3D
structure of the target protein sourced from
the Protein Data Bank (GDP) and
understands disease at the molecular level
[25]. SBDD begins with knowing the
structure of the target, then an in silico
study is conducted to identify potential
ligands followed by an evaluation of
biological properties, such as potency,
affinity, efficacy, and ADMET properties
of a compound [26,27]. Molecular docking,
structure-based virtual screening, and
molecular dynamics are one of the most
frequently used SBDD strategies due to
their wide application in the analysis of a
molecule such as binding energy, molecular
interactions, and evaluation of
conformational changes that occur during
the docking process [28].
The software needed in SBDD includes
AutoDock Vina to combine protein
structure data obtained from PDB with
ligand data. However, if the protein in
question is not available, it can be made
using the homology modeling method using
the MODELLER or SWISS-MODEL
program. Other software that is also needed
is Discovery Studio, OpenEye,
Schrödinger, and MOE.
a. Structure-Based Virtual Screening
The SBVS method relies on the
structure of the target protein's active
site which in the SBVS database the
compound will be anchored to the
target binding site [29, 25]. Along with
the prediction of the binding mode,
SBVS provides a rating of the tethered
molecule which will be used as the sole
criterion for selecting a potential
molecule or can be combined with
other evaluation methods. The selected
compounds were then experimentally
evaluated to determine their biological
activity on the molecular targets under
investigation [30].
Broadly speaking, the steps for SBVS
are preparation of molecular targets,
selection of compound database,
molecular anchoring, and post-
docking analysis [31]. The
conformational change resulting from
the interaction with the ligand is an
important matter that requires
consideration in selecting the
appropriate structure. The selected
structure needs to be prepared to carry
out the docking procedure properly by
adding hydrogen atoms, removing
water molecules, determining the
correct protonation and
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tautomerization status of the binding
site residues, and calculating partial
charges [32]. Next, the prepared
database is installed at the target
binding site. A potential ligand is when
the energy of each molecule has a high
score. Post docking analysis is usually
carried out to decide which compound
will be the lead compound [33].
b. Molecular Docking
Docking is a molecular interaction
simulation technique. Molecular
docking predicts conformational and
ligand binding in the target active site
with high accuracy and is the most
frequently used technique in SBDD
[34,35]. This method is applied to
study molecular phenomena such as
ligand binding and intermolecular
interactions for the stability of a
complex [36]. In addition, the docking
algorithm predicts the binding energy
and the ranking of the ligands through
various assessments. There are two
types of molecular docking, namely
flexible-ligand search docking and
flexible-protein docking [37].
c. Structure-Based Pharmacophore
The pharmacophore model of the target
binding site encapsulates the steric and
electronic requirements for optimal
ligand-target interactions. The most
common properties used to define a
pharmacophore are hydrogen bond
acceptor, hydrogen bond donor, basic
group, acid group, partial charge,
aliphatic hydrophobic group, and
aromatic hydrophobic group. Besides
being able to be used for virtual
compound screening, pharmacophore
models can be used by de novo design
algorithms to guide the design of new
compounds. Structure-based
pharmacophore methods were
developed based on the analysis of
target binding sites or based on the
structure of the target ligand complex
[38,39].
d. Molecular Dynamics
The flexibility of the target binding site
is an important aspect that is often
overlooked in the consideration of
molecular docking. Enzymes and
receptors can undergo conformational
changes during the molecule
recognition process. In some cases
these structural rearrangements are
minor and the ligands fit at the binding
site with little mobility or significant
conformational changes in some
proteins that may involve secondary
and tertiary structural elements. This
flexibility-related problem can be
addressed using molecular dynamics
techniques [40,41]. MD simulations
can generate alternative
conformational states corresponding to
the ligand-induced structure. In the
absence of a suitable crystallographic
structure for the molecular target, MD
can be applied to produce a good set of
structures for docking [42]. MD can
also be used to estimate the stability of
the ligand-receptor complex proposed
by molecular docking [43]. MD has the
drawbacks of high computational costs
for simulating large systems usually
consisting of thousands of atoms when
the ligand-receptor complex is being
studied and the conformational
changes that the receptor undergoes
during molecular recognition exceed
the available computational timescale
capacities [44]. However, MD makes
an important contribution to SBDD,
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especially when combined with other
methods such as molecular docking.
e. De Novo Design
De novo drug design is a method of
forming new chemical compounds
starting from molecular units. The
essence of this approach is to develop
a chemical structure of a small
molecule that binds to a target with
good affinity [45]. Two methods can
be used, namely ligand-based de novo
and receptor-based de novo. The
quality of the target protein structure
and knowledge of the binding site are
important to know if you want to use a
receptor-based design because suitable
small molecules are designed to
incorporate fragments into the binding
of the receptor. This can be done by
crystallizing the ligand with the
receptor [46]. The greatest challenge in
the design of this de novo drug cannot
be separated from its greatest
advantages. By defining compounds
that have never been seen before, it is
necessary to attempt synthesis for
acquisition before testing. This
affected the de novo protocol where it
was necessary to incorporate synthesis
capability metrics into the assessment.
This will increase the effort required
such as costs, results, time, and also the
required expertise. Thus, synthesizing
capability becomes increasingly
important when designing large
numbers of compounds [47].
3.5.2 Ligand-Based Based Drug Design
Ligand Based Drug Design (LBDD)
is an approach if in some cases data
relating to the 3D structure of a target
protein are not available, then drug design
can be based on a process that uses known
ligands of the target protein as a starting
point. QSAR and pharmacophore
modeling are methods that are often used
in the drug design process using the LBDD
approach [48]. Using fingerprints of
known ligand molecules, databases can be
screened for similar molecular fingerprints
[49]. The general structural features of the
ligands can be found by pharmacophore
modeling which can then be used for
molecular screening [50]. To predict the
activity of new molecules, models can be
built with QSAR. While pharmacophore
modeling only shows the activity of the
active ligand, the relationship between the
chemical/physical properties of the ligand
and biological activity can be explored
more fully using the QSAR model [51].
The software needed for LBDD includes
AutoDock Vina, Schrödinger, LiSiCA,
BioSolveIT, and many others. Consisting
of 5 methods that can be done are QSAR,
Ligand-Based Pharmacophore, 2D
Similarity-Based Search, ADMET
Prediction, and Scaffold Hopping.
However, 3 of them that are commonly
used are QSAR, Ligand-Based
Pharmacophore, and 2D Similarity-Based
Search.
a. Ligand-Based Pharmacophore
Among the ligand-based virtual
screening techniques, the
pharmacophore modeling approach is
one of the best. This approach requires
the introduction of a 3D pharmacophore
preparation using a list of known active
substances that should bind to the same
active site or from the 3D coordinates of
the protein active site. The advantage of
using a pharmacophore is that it can be
computationally visualized,
superimposed onto a list of molecules,
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and thus assist medicinal chemists in
synthesizing new molecules [52,53].
b. QSAR
QSAR describes the mathematical
relationship between structural
attributes and target response. The flow
of drug discovery based on QSAR is
started by collecting a group of active
and inactive ligands, then creating a
mathematical descriptor that describes
the physicochemical and structural
properties of a compound. A model was
created to identify the relationship
between descriptors and experimental
activity and maximize predictive
power. Finally, a model was applied to
predict the activity of the test compound
encoded with the same descriptor. The
success of QSAR depends not only on
the initial quality of the compound but
also on the choice of the descriptor and
the ability to generate suitable
mathematical relationships. One of the
important considerations regarding this
method is the fact that all the resulting
models will depend on the sampling
space of compounds with known
activity [54].
c. 2D Similarity-Based Search
Goldman and Wipke presented a new
approach to shape-based molecular
similarity search [55]. This method is
capable of locating different molecules
by using a geometrically invariant
molecular surface descriptor. This
method uses a superimposition
algorithm that uses this geometric
invariance to recognize similar regions
of the surface shape that exist in two
molecules [56]. The calculation of the
shape descriptor continues by
considering initially all the
conformations of the molecule to define
the shape descriptor space; the chemical
features in each feature lattice shape
and location are then co-coded into a bit
binary string descriptor. Identification
of the most important bits for the
activity leads to a model that can judge
the library on the number of bits the
ensemble matches.
4. Conclusion
Several approaches including the
traditional drug discovery process and
modern computational approach are useful
in finding novel drugs. Nevertheless,
Structure-Based Drug Design and Ligand-
Based Drug Design approaches that are
computationally based are currently known
as preferable alternatives in drug discovery
because they are more efficient in terms of
time and cost. This is considered very
important since alternative drugs with
several beneficial effects or alternatives to
existing drugs are urgently required for the
enhancement of human health. The
traditional approach to new drug
development takes about 11-16 years but
using computational methods can shorten
the drug discovery stage to 9-13 years.
Acknowledgements
The authors would like to thank the
Pharmacy Study Program at the University
of Padjadjaran which has provided
assistance and support in writing this article
review.
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