The document discusses the quantitative structure-activity relationship (QSAR) approach in drug design, highlighting the importance of identifying and quantifying the physicochemical properties' effects on drug biological activity. It explores the use of linear regression analysis to predict drug interactions and the role of electronic and steric factors in determining compound activity. Additionally, the document introduces 3D-QSAR methods that analyze molecular properties without relying on experimental data, enhancing predictive capabilities for drug design.

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3. The number of compounds required for synthesis
in order to place 10 different groups in 4 positions
of benzene ring is 104
Solution: synthesize a small number of
compounds and from their data derive rules to
predict the biological activity of other compounds.
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4. QSAR what actually do?
IDENTIFY AND QUANTIFY the Physico-chemical properties effect on
Drug’s Biological activity
Such relationships holds – Equations can be drawn up- some
confidence
to which should be Fit to the target
PHARMACOKIINETICS
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5. QSAR and Drug Design
Compounds + biological activity
New compounds with
improved biological activity
QSAR
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6. Instead of trial and error , use computer to help
Now desired structure can be designed computationally
PROCEDURE
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7. HOW it is
LOOK LIKE7

8. PHYSICO-CHEMICAL PROPERTIES - log 10P (X axis)
BIOLOGICAL ACITIVITY - log1/C (Y axis)
“Linear regression analysis by the least Squares method”
Draw a line through the data points
most of the points will be scattered
on the either side of the line is best
Best line through the
points will be the line
where this total sum of
squares is minimum
y=mx+c
M,C are variaents determaines the
line each time for every n number of
compounds using relevant softwares8

9. 2.Correlation graph analyse
To see if the relationship is meaningful.
figures statistical evidence obtained to support QSAR equation and Quantifies the goodness to fit
Regression coefficient (r) is the measure of How well the eqn explains the varience in activity
observed
Sscalc – measure of how much the experimental activity of the compound varies from
calculated
Ssmean –how much experimental activities varies from mean of all experimental activities
R=1 perfect
fit
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11. Drug and Target interactions
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12. ConceptsOF DESCRIPTORS
•Aims
To relate the biological activity of a series of compounds to their
physicochemical parameters in a quantitative fashion using a mathematical
formula
•Requirements
Quantitative measurements for biological and physicochemical properties
•Physicochemical Properties
•Hydrophobicity of the molecule
•Hydrophobicity of substituents
•Electronic properties of substituents
•Steric properties of substituents
Most common
properties studied
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13. Hydrophobicity of the Molecule
Partition Coefficient P = [Drug in octanol]
[Drug in water]
High P High hydrophobicity
•Activity of drugs is often related to P
e.g. binding of drugs to serum albumin
(straight line - limited range of log P)
Log (1/C)
Log P
. .
.
.. .
. ..
0.78 3.82
Log 1
C



= 0.75 logP + 2.30
•Binding increases as log P increases
•Binding is greater for hydrophobic drugs
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14. Example 2 General anaesthetic activity of ethers
(parabolic curve - larger range of log P values)
Optimum value of log P for anaesthetic activity = log Po
Log
1
C



= -0.22(logP)2 + 1.04 logP + 2.16
Log P
o
Log P
Log (1/C)
Hydrophobicity of Substituents
Benzene
(Log P = 2.13)
Chlorobenzene
(Log P = 2.84)
Benzamide
(Log P = 0.64)
cll CONH2
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15. QSAR equations are only applicable to compounds in the same
structural class (e.g. ethers)
•However, log Po is similar for anaesthetics of different structural
classes (ca. 2.3)
•Structures with log P ca. 2.3 enter the CNS easily
(e.g. potent barbiturates have a log P of approximately 2.0)
•Can alter log P value of drugs away from 2.0 to avoid CNS side
effects
Hydrophobicity
Notes:
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16. Electronic Effects
Hammett Substituent Constant (s)
Notes:
•The constant (s) is a measure of the e-withdrawing or e-donating influence of
substituents
•It can be measured experimentally and tabulated
(e.g. s for aromatic substituents is measured by comparing the
dissociation constants of substituted benzoic acids with benzoic acid)
X=H K H = Dissociation constant= [PhCO 2-]
[PhCO 2H]
+CO2H CO2 H
X X
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17. +
X = electron
withdrawing
group
X
CO2CO2H
X
H
X= electron withdrawing group (e.g. NO2)
s X = log
K X
K H
= logK X - logK H
Charge is stabilised by X
Equilibrium shifts to right
KX > KH
Positive value
Hammett Substituent Constant (s)
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18. X= electron donating group (e.g. CH3)
s X = log
K X
K H
= logK X - logK H
Charge destabilised
Equilibrium shifts to left
KX < KH
Negative value
Hammett Substituent Constant (s)
+
X = electron
withdrawing
group
X
CO2CO2H
X
H
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19. NOTES:
s value depends on inductive and resonance effects
s value depends on whether the substituent is meta or para
ortho values are invalid due to steric factors
Hammett Substituent Constant (s)
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20. QSAR Equation:
Diethylphenylphosphates
(Insecticides)
log 1
C



= 2.282s - 0.348
Conclusion: e-withdrawing substituents increase activity
Hammett Substituent Constant (s)
X
O P
O
OEt
OEt
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21. Aliphatic electronic substituents
•Defined by sI
•Purely inductive effects
•Obtained experimentally by measuring the rates of hydrolyses of aliphatic esters
•Hydrolysis rates measured under basic and acidic conditions
X= electron donating Rate sI = -ve
X= electron withdrawing Rate sI = +ve
Basic conditions: Rate affected by steric + electronic factors
Gives sI after correction for steric effect
Acidic conditions: Rate affected by steric factors only (see Es)
+
Hydrolysis
HOMe
CH2 OMe
C
O
X CH2 OH
C
O
X
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22. Steric Factors
Verloop Steric Parameter
- calculated by software (STERIMOL)
- gives dimensions of a substituent
- can be used for any substituent
L
B
3
B
4
B4 B3
B2
B1
C
O
O
H
H O C O
Example - Carboxylic acid
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24. 3D-QSAR
•Physical properties are measured for the molecule as a whole
•Properties are calculated using computer software
•No experimental constants or measurements are involved
•Properties are known as ‘Fields’
•Steric field - defines the size and shape of the molecule
•Electrostatic field - defines electron rich/poor regions of molecule
•Hydrophobic properties are relatively unimportant
Advantages over QSAR
•No reliance on experimental values
•Can be applied to molecules with unusual substituents
•Not restricted to molecules of the same structural class
•Predictive capability 24

25. 3D-QSAR
•Comparative molecular field analysis (CoMFA) - Tripos
•Build each molecule using modelling software
•Identify the active conformation for each molecule
•Identify the pharmacophore
Method
NHCH3
OH
HO
HO
Active conformation
Build 3D
model
Define pharmacophore
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26. 3D-QSAR
•A probe atom is placed at each grid point in turn
Method
•Measure the steric or electrostatic interaction of the probe atom
with the molecule at each grid point
.
.
.
.
.
Probe atom
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27. 3D-QSAR
•Define fields using contour maps round a representative molecule
Method
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29. Properties Explored in QSAR
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