DrugDesignandDiscover

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Drug Design and Discovery
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Pre-PhD Students (Lecture 1)
Dr. Mohamed Kotb El-Sayed
Associate Professor of Pharmaceutical Biochemistry & Molecular Biology
1
Dr. Mohamed I. Kotb – Associate Professor of Pharmaceutical Biochemistry and Molecular Biology

Objectives:
2
By the end of this lecture, you should be familiar with:
 Drug Sources.
 Drug Targets.
 Drug Discovery Overview.
 Methods or Tools of Drug Design;
▪ CADD.
▪ Pharmacophore.
▪ Docking.
▪ Examples.
 Drug Delivery.
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Drug Sources:
3
▪ A drug is any chemical or biological substance,
synthetic or non-synthetic
▪ Animal: insulin (pig, cow) growth hormone
(man).
▪ Plant: digitalis (digitalis purpurea - foxglove)
morphine (papaver somniferum).
▪ Inorganic: arsenic mercury lithium.
▪ Synthetic: chemical (propranolol)
▪ Biological: (penicillin) biotechnology (human
insulin).
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Synthetic sources
Drugs
Natural sources Targets

Drug Targets:
4
1- Targets: Membrane Proteins:
▪ The selection of good drug targets depends on its contribution to a
biological pathway involved in the pathophysiology of a disease,
▪ The target is “druggable” if it is functionally and structurally known.
▪ Membrane proteins such as receptors, ion channels and transporters
are key regulators of cellular function.
▪ Membrane proteins account for up to two thirds of known drug
targets, demonstrating they are “druggable”.
2- Targets: DNA:
▪ DNA, mRNA, and rRNA are important molecular targets for cancer,
viral, and microbial chemotherapy.
▪ Drugs that bind to these targets inhibit DNA replication, the
transcription of mRNA, and its translation into proteins.
▪ How structure-based approaches have been applied to the rational
design of DNA groove binding agents that recognize specific nucleotide
sequences, and,
▪ How this provides the opportunity for the development of gene-specific
inhibitors of transcription.
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Drug Targets:
5
3- Targets: RNA:
▪ DNA-binding agents that specifically inhibit the transcription of
designated genes.
▪ The agents that selectively block mRNA to inhibit gene expression
at the level of translation.
▪ Example: The use of small inhibitory RNAs, known as siRNAs, in
post-transcriptional gene silencing.
4- Targets: Enzymes:
▪ Many cellular process involved in disease are mediated or
controlled by the specific action of enzymes.
▪ Several disease processes can therefore be reduced or eliminated
by manipulating the activity of specific enzymes.
▪ There are many examples of how several drugs exert their
therapeutic effects by interacting with these enzymes.
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Drug Targets:
6
DD &D

Discovering and Developing the ‘One Drug’:
7
 Time to
market: 10-12
years. Why?
(Biochemical,
animal, human
trials; scaleup;
approvals from
FDA).
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Pharmaceutical R & D (A Multi-Disciplinary Team):
8
Over 100 Different Disciplines Working Together:
 Administrative Support Analytical Chemistry Animal
Health Anti-infective Disease Bacteriology.
 Behavioral Sciences Biochemistry Biology Biometrics
Cardiology Cardiovascular Science Clinical Research.
 Communication Computer Science Cytogenetics
Developmental Planning DNA Sequencing Diabetology.
 Document Preparation Dosage Form Development Drug
Absorption Drug Degradation Drug Delivery.
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Drug Discovery & Development:
9
Identify disease
Isolate protein
involved in disease
(2-5 years)
Find a drug effective
against disease protein
(2-5 years)
Preclinical testing
(1-3 years)
Formulation
Human clinical trials
(2-10 years)
FDA approval
(2-3 years)
Drug Design
- Molecular Modeling
- Virtual Screening
Scale-up
DD &D
NDA = New Drug Application
IDA = Investigational New Drug.

Technology is Impacting this Process:
10
Identify disease
Isolate protein
Find drug
Preclinical testing
GENOMICS, PROTEOMICS & BIOPHARM.
HIGH THROUGHPUT SCREENING
MOLECULAR MODELING
VIRTUAL SCREENING
COMBINATORIAL CHEMISTRY
IN VITRO & IN SILICO ADME MODELS
Potentially producing many more targets
and “personalized” targets
Screening up to 100,000 compounds a
day for activity against a target protein
Using a computer to
predict activity
Rapidly producing vast numbers
of compounds
Computer graphics & models help improve activity
Tissue and computer models begin to replace animal testing
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Drug Discovery overview:
11
1- Serendipity “Chance favors
the prepared mind”
• Occasional new drugs found by
accident (Serendipity).
• 1928 Fleming studied Staph, but
contamination of plates with
airborne mold.
• Noticed bacteria were lysed in the
area of mold. A mold product
inhibited the growth of bacteria:
the antibiotic penicillin.
Approaches to drug discovery:
•Serendipity (luck). . Chemical Modification.
. Random Screening. . Rational.
DD &D

12
 :
R-(CH2)n-N Homologs (n=2,3,4,5.....)
(A) Homolog Approach: Homologs of a lead prepared:
(B) Molecular Disconnection /Simplification:
O
N CH3
O
H
NCH2CH=C C
CH2OCONH2
CH2OCONH2
C
H3
C3H7
MORPHINE PENTAZOCINE MEPROBAMATE
(C) Molecular Addition:
O
N-CH2-CH=CH2
O
H
NALORPHINE
(D) Isosteric Replacements:
N
H2 COOH N
H2 SO2NH2
P.A.B.A. SULFANILAMIDE
2- Chemical Modifications:
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13
2- Chemical Modification….
Traditional method:
• An analog of a known, active compound is synthesized with
a minor modification, that will lead to improved Biological
Activity.
• Advantage and Limitation: End up with something very
similar to what you start with.
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• Lead is a chemical compound that has
pharmacological or biological activity
likely to be therapeutically useful,

14
3- Random Screening:
• Screen many synthetic chemical compounds or natural products
for desired effect.
• Although this approach for the development of new drugs has
been successful in the past, it is not ideal for several reasons.
• It is repetitious and time consuming.
• It is trial & error approach
• One does not need to know the structure of the drug nor
the structure of the target upon which the drug will act.
• One does not need to know about the underlying
mechanism of the disease process itself.
• Example: Prontosil is derived from a dye that exhibited
antibacterial properties.
DD &D

Drug Discovery Overview:
15
Depending on previous methods (1-3) is a time consuming with low
through output.
4- Rational Drug Design - Cimetidine (Tagamet):
• Starts with a validated biological target and ends up with a drug
that optimally interacts with the target and triggers the desired
biological action.
• Problem: histamine triggers release of stomach acid. Want a
histamine antagonist to prevent stomach acid release by histamine
= VALIDATED BIOLOGICAL TARGET.
• Histamine analogs were synthesized with systematically varied
structures (chemical modification) and SCREENED. N-guanyl-
histamine showed some antagonist properties = LEAD compound.
DD &D

Drug Discovery Overview:
16
4- Rational Drug Design - Cimetidine (Tagamet):
B. More potent and orally
active, but thiourea found to
be toxic in clinical trials
C. Replacement of the group
led to an effective and well-
tolerated product:
A. Chemical modifications
were made of the lead = LEAD
OPTIMIZATION:
D. Eventually replaced by
Zantac with an improved
safety profile
DD &D

Mechanism-Based Drug Design:
17
▪ Most rational approach employed today.
▪ Disease process is understood at molecular level & targets are
well defined.
▪ Drug can then be designed to effectively bind these targets &
disrupt the disease process.
▪ This process is very complex & intellectual approach &
therefore requires detailed knowledge & information retrieval.
▪ “Drug–Receptor Interaction is not merely a lock-key
interaction but a dynamic & energetically favorable one”
(CADD).
DD &D

Computer Aided Drug Design Techniques:
18
What's CADD:
 Computational Chemistry/CADD are computer programs that calculate the
properties of future drug molecules and thus helping in the process of
drug design and discovery.
 CADD methods are widely used today in academic and industrial
environments.
 It explains the basics on how the structures of molecules can be entered
into a computer and manipulated in silico (in computer simulation or in
virtual reality).
 This includes methods for geometry optimization, molecular dynamics
simulation, and conformational searching.
Why CADD?
 Drug Discovery today are facing a serious challenge because of the
increased cost & enormous amount of time taken to discover a new drug,
and because of rigorous competition amongst different pharmaceutical
companies.
DD &D

19
1- Physicochemical Properties Calculations:
 Partition Coefficient (LogP), Dissociation Constant (pKa) … etc.
2- Drug Design (Molecular Modeling):
 Ligand based drug design (LBDD) “INDIRECT DESIGN” ▪ Followed when
the structure of the target is unknown.
 QSARs.
 Pharmacophore Perception.
 Structure based drug design (SBDD) “DIRECT DESIGN” ▪ Followed when
the spatial structure of the target is known.
 Docking.
 de-novo drug design.
3- Pharmacokinetic Modeling:
 Absorption, Metabolism, Distribution and Toxicity … etc.
4- Cheminformatics:
 Database Management.
 Similarity / Diversity Searches.
 All techniques joins together to form VIRTUAL SCREENING
protocols.
DD &D

20
1- Ligand-Based Drug Design:
 To improve the properties of a potential drug, structure activity
relationships are established to identify structural moieties that
contribute to the binding and activity of a compound.
 It can be used to model and predict these properties, and to screen
databases for new leads.
 These methods include quantitative structure-activity relationship
(QSAR) and pharmacophore determination. A pharmacophore defines the
structural features and geometry of a drug that impart biological activity.
2- Structure-Based Drug Design:
 Where the detailed three-dimensional structure of the protein target is
available, so-called structure-based computer-aided drug design methods
can be utilized to identify and modify lead compounds.
 If the protein structure is not available, then computer models, based on
structures of similar proteins, can be prepared and are suitable for
structure-based drug.
 This introduce structure-based drug design and protein modelling methods.
DD &D

21
Ex: Receptor-Based Drug Design:
▪ A fundamental requirement of rational drug design
is knowledge of the 3-dimensional structure of the
receptor, generally a protein, sometimes a nucleic
acid.
▪ There are many experimental methods available for
determining these structures, focusing on X-ray
crystallography, NMR spectroscopy, and mass
spectrometry.
▪ Examine the 3D structure of the biological target.
▪ Hopefully one where the target is complexed with a
small molecule ligand (Co-crystallized).
▪ Look for specific chemical groups that could be
part of an attractive interaction between the
target protein and the ligand.
▪ Design a new ligands that will have sites of
complementary interactions with the biological
target.
▪ Advantage: Visualization allows direct design of
molecules.
DD &D

Quantitative Structure Activity Relationships (QSAR):
22
 QSARs are the mathematical relationships linking chemical
structures with biological activity using physicochemical or any
other derived property as an interface.
 Mathematical Methods used in QSAR includes various regression
and pattern recognition techniques.
 Physicochemical or any other property used for generating QSARs
is termed as Descriptors and treated as independent variable.
Biological property is treated as dependent variable.
Biological Activity = f (Physico-chemical properties)
Compounds + Biological activity
QSA
R
New compounds with improved
biological activity
DD &D

Pharmacophore-Based Drug Design:
23
Pharmacophore:
• It is the spatial orientation of various functional groups or
features in 3D necessary to show biological activity.
• Examine features of inactive small molecules (ligands) and the
features of active small molecules.
• Generate a hypothesis about what chemical groups on the
ligand are necessary for biological function; what chemical
groups suppress biological function.
• Generate new ligands which have the same necessary chemical
groups in the same 3D locations. (“Mimic” the active groups)
Advantage: Don’t need to know the biological target structure
DD &D

Docking Process:
24
 An Automated software for Predicting Optimal
Protein-Ligand Interaction or Prediction of
the optimal physical configuration and energy
between two molecules
 Put a compound in the approximate area where
binding occurs.
 Docking algorithm encodes orientation of
compound and conformations.
 The docking optimizes;
 The binding between two molecules such that
their orientation maximizes the interaction.
 Evaluate the total energy of interaction such
that for the best binding configuration with
minimum energy.
 Hydrogen bonding.
 Hydrophobic interactions.
 The resultant structural changes brought
about by the interaction.
DD &D

Docking Importance:
25
 Interaction between biomolecules lie at the core of all metabolic
processes and life activities.
 The number of solved protein structures available in the databases is
expanding exponentially.
 To understand their functions, it is essential to elucidate the
interaction mechanisms between the different molecules.
 Primary importance lies in rational drug design.
 Depending upon the success of the docked molecules the docking ligand
may be redesigned, or its structure further refined.
 Also important in the area of immunology to study antigen-antibody
interaction.
Inhibitor bound to active site of HIVPR
DD &D

Categories of Docking:
26
1. Protein-Protein Docking:
▪ Both molecules are
rigid.
▪ Interaction produces
no change in
conformation.
▪ Like lock-and key
model
2. Protein-Ligand Docking:
▪ Ligand is flexible but
the receptor protein is
rigid.
▪ Interaction produces
conformational changes
in ligand.
Optimized
2. Protein-Ligand Docking
1. Protein-Protein Docking
DD &D

Docking Applications:
27
• Discovery of Indinavir, the HIV protease inhibitor.
• Identification of Haloperidol as a lead compound in a
structure-based design for non-peptide inhibitor of HIV.
• Carbonic Anhydrase (treatment of glaucoma).
• Renin (treatment of hypertension).
• Dyhrofolate reductase (antibacterial).
• Neuraminidase (antiviral).
• HIV-1 aspartic proteinase (anti-acquired immune deficiency.
• Collagenase (Rheumatoid and Osteoarthritis).
• PhospholipaseA2(anti-inflammatory).
• Glycogen phosphorylase (treatment of diabetes mellitus).
DD &D

Drug Delivery:
28
DD &D

Drug Delivery:
29
1- Bioavailability:
▪ Pharmacokinetics is the study of what the body does to a drug once it is
within the body.
▪ A clinically important outcome of the body’s treatment of a drug is how
much drug is finally available in the body to bind to its intended
therapeutic target (bioavailability).
▪ Means that how ADME processes (Absorption, Distribution, Metabolism
and Excretion) impact on a drug’s bioavailability.
2- Pro-drugs and Drug Delivery:
▪ An inactive derivative of a known active drug may be called a prodrug and
requires transformation within the body in order to release the active
drug.
▪ Prodrugs can provide improved physiochemical properties such as
solubility and enhanced delivery characteristics and/or therapeutic
effect.
▪ Then we must know the barriers to drug action, pro-drugs as drug delivery
systems, and the application of pharmacokinetics and pharmacodynamics
in drug delivery.
DD &D

Preclinical and clinical testing:
30
1- Pre-clinical Toxicology: In Vitro;
• This discuss the role of in vitro toxicity tests in establishing the
safety of new drugs.
• In vitro toxicity tests required by the world’s regulatory bodies;
tests for genotoxicity, cytotoxicity and others as required by
chemical class - the theory and methodology underlying various in
vitro toxicology tests.
2- Pre-clinical Toxicology: In Vivo;
• To understand: - the role of in vivo toxicity tests in establishing the
safety of new drugs
• In vivo toxicity tests required by the world’s regulatory bodies;
genotoxicity, acute and short-term toxicity tests, tests for
carcinogenic potential, Q-T prolongation and others as required by
chemical class. - the theory and methodology underlying various in
vivo toxicology tests
• The ethics of in vivo toxicity testing and the potential for
replacement by in vitro models .
DD &D

Preclinical and clinical testing:
31
Clinical Trials:
▪ The regulation of therapeutic products and the phases (I-IV) of
clinical trial that a drug must pass through before registration.
▪ Clinical Trial Design: The components of clinical trial design to be
discussed will be aims, design, controls and placebo, blinds,
randomization procedures, sample size, statistics, endpoints and
ethics (ethics will be covered later in the course).
Ethics of Human and Animal:
▪ Experimentation Testing of drugs in animals and humans is under
strict regulation to limit any harm and distress to the research
subjects.
▪ The ethical conduct of biomedical research, including the policies
governing biomedical and animal research in Egypt.
▪ The role of institutional human ethic committees and what
constitutes informed consent.
▪ The general principles for the care and use of animals for scientific
purposes and the replacement, reduction and refinement will be
covered and the role of institutional animal ethics committees.
DD &D

Reference
32 Dr. Mohamed I. Kotb – Associate Professor of Pharmaceutical Biochemistry and Molecular Biology
mohamed.kotb71524@gmail.com
WhatsApp: 00201140400767
www.researchgate.net/profile/Mohamed-kotb-Kotb-El-Sayed
• Drug Discovery and Development; Technology in Transition. HP Rang. Elsevier Ltd 1st
edition 2006.
• Pharmacology in Drug Discovery. T. P. Kenakin. Elsevier, 1st Edition 2012.
• An introduction to medicinal chemistry. G. L. Patrick. 5th Edition Oxford UK, Oxford
University Press, 2013.
• Textbook of Drug Design. Krogsgaard-Larsen, Liljefors and Madsen (Editors), Taylor and
Francis, London UK, 2002.
• Drug Discovery Handbook S.C. Gad (Editor) Wiley-Interscience Hoboken USA, 2005.
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