The document discusses computer-aided drug design (CADD) and its role in drug discovery. CADD uses computer software and modeling to aid the drug design process and identify new drug candidates. It reduces the time and cost of drug discovery compared to traditional methods. Some of the earliest approved drugs discovered using CADD include Dorzolamide, Captopril, and drugs for HIV. CADD approaches include structure-based design using protein structure data and ligand-based design using information about known active/inactive ligands. Key steps involve target identification, obtaining protein structures, ligand docking simulations, and lead optimization.

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2. What is CADD
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• Drug design is the inventive process of finding
new medications based on the knowledge of a
biological target.
• If the same process was done by using
Computer/Software then it is referred as
CADD
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4. Why CADD…?
 Drug Discovery today are facing a serious challenge because
of the increased cost and enormous amount of time taken to
discover a new drug, and also because of rigorous
competition amongst different pharmaceutical companies.
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5. Some of the earliest examples of approved drugs that
owe their discovery in large part to the tools of CADD
include the following:
 Carbonic anhydrase inhibitor Dorzolamide used to
treat glaucoma (Vijayakrishnan 2009)
 The angiotensin-converting enzyme (ACE) inhibitor,
Captopril, an antihypertensive drug (Talele et al.,
2010)
 Three therapeutics for the treatment of human
immunodeficiency virus (HIV): Saquinavir, Ritonavir,
and Indinavir (Van Drie 2007)
 Tirofiban, a fibrinogen antagonist (Hartman et al.,
1992)
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6. Some of the earliest examples of approved drugs that owe their discovery in
large part to the tools of CADD
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7. Drug Discovery & Development
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)
Scale-up
FDA approval
(2-3 years)
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8. Technology is impacting this process
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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9. Target
Identification
CADDStructure-
based
Ligand-
based
3D structure
of the target
Information
on Ligands
Ligand
docking
Fragment-
based Design
Ligand-based
virtual
screening
QSAR
Pharmacophore
modelling
Lead
optimization
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CADD can be classified into two general categories

10. Structure-
based
Ligand-
based
Structure-based CADD relies on
the knowledge of the target
protein structure
to select compounds based on
their binding energies.
Ligand-based CADD exploits the
knowledge of known active and
inactive molecules through
 chemical similarity searches
 construction of predictive,
quantitative structure-activity
relation (QSAR) models.
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generally preferred
Where high-resolution
structural data of the target
protein are available, i.e., for
soluble proteins that can
readily be crystallized.
generally preferred
When no or little structural
information is available, as often
for membrane protein targets.

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• Obtaining 3D structure of protein
• Active site identification
• Ligand-receptor fit analysis(Docking)
• Design of new leads
Steps in Structure-Based Drug Design
The steps used in structure-based drug design for
designing new lead compounds are:
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13. Acetylcholine Esterase
• RCSB Protein Data
Bank (PDB)
• Human disease-
molecular biology
databases
– SWISS-PROT
– OMIM
– GenBank
– MEDLINE
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Combinatorial Libraries
• Thousands of variations to a fixed template
• Good libraries span large areas of chemical and
conformational space - molecular diversity
• Diversity in - steric, electrostatic, hydrophobic interactions...
• Desire to be as broad as “Merck” compounds from
random screening
• Computer aided library design is in its infancy

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E bind = E intra + E nonpolar + E polar
Docking Score

17. Various parameters used in QSAR studies are
1. Lipophilic parameters: partition coefficient, π-substitution
constant
2. Polarizability parameters: molar refractivity, parachor
3. Electronic parameters: Hammet constant, dipole moment.
4. Steric parameters: Taft’s constant.
5. Miscellaneous parameters: molecular weight, geometric
parameters.
Ligand Based Drug Design
QSAR PARAMETERS
The parameter is the measure of the potential contribution of
its group to a particular property of the parent drug
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18. Lipophilic parameters
Lipophilicity is partitioning of the compound between
an aqueous and non-aqueous phase.
Partition coefficient:
• P = [drug] in octanol / [drug] in water
Typically over a small range of log P, e.g. 1-4, a straight
line is obtained
e.g. log 1/C = 0.75 log P + 2.30
• If graph is extended to very high log P values, then
get a parabolic curve
log 1/C = - k1 (log P)2 + k2 log P + k3
• When P small, dominated by log P term
• When P large, log P squared dominates & so activity
decreases
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19. π-substituent constant or hydrophobic substituent
constants:
• The π-substituent constant defined by hansch and co-
workers by the following equation.
px = log Px - log PH
• Apositive πvalue indicates that the πsubstituent has a
higher
lipophilicity than hydrogen and the drug favours the organic
phase.
• A negative πvalue indicates that the πsubstituent has a lower
lipophilicity than hydrogen and the drug favours the aqueous
phase.
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Log P = logP(benzenz) + π Cl + πCONH2
= 2.13 + 0.17 + (-1.49)
= 1.35

21. Electronic parameters
The Hammett constant(σ)
σ x = log (Kx/Kbenzoicacid)
Electron Withdrawing Groups
• Equilibrium shifts Right & Kx > Kbenzoicacid
• Since sx = log Kx – log Kbenzoicacid, then s will be
positive .
• Hammett constant takes into account both
resonance and inductive effects; thus, the value
depends on whether the substituent is para or
meta substituted
-ortho not measured due to steric effects.
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22. Steric Substitution Constant
It is a measure of the bulkiness of the group it represents and it
effects on the closeness of contact between the drug and receptor
site.
much harder to quantitate
Examples are:
Taft’s steric factor (Es) an experimental value based on rate
constants
Molar refractivity (MR)--measure of the volume occupied by an
atom or group--equation includes the MW, density, and the index of
refraction
Verloop steric parameter--computer program uses bond angles,
van derWaals radii, bond lengths
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