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QSAR BY HANSCH ANALYSIS
Presented by – Vishal Singh Solanki
Guided by – Dr. A. Basu
CONTENT
 Introduction
 Graph and equation
 Regression or correlation coefficient
 Physicochemical properties
 Application of qsar
 Advantages
 Disadvantages
 Hansch equation
 References
INTRODUCTION
 The identification of a new drug molecule requires a lot of
synthesis, time and money. It was identified that out of billion
molecules synthesized, around one or two molecules reach the
clinical trials.
 The quantitative structure activity relationship approach has
proved extremely useful in overcome this problem.
 QSAR approach attempts to identify and quantify the
physicochemical properties of a drug and to see whether any
of these properties has an effect on the drug’s biological
activity.
Graphs and equations
• A range of compounds is synthesized in order to vary one
physicochemical property and to test how this affects the
biological activity. A graph is then plot the biological activity
0n the y-axis versus the physicochemical feature on x-axis.
The best line will be the closet to the data points . To measure how
close the data points vertical lines are drawn from each points. The
best line through the points will be the line where total is minimum.
Conti…
Regression or correlation coefficient
(r) :
It is measure of how well the equation explains the variance in
activity observed in terms of physicochemical parameters
present in the equation.
To illustrate ‘r’ following numerical data will be used.
There are 6 compounds in the study (n=6).
Yexp = log(observed activity)
X = physicochemical property
• ( Yexp – Ycalc)2 = Sscalc
• ( Yexp – Ymean)2 = SSmean
Conti…
The QSAR equation derived from the data is:
log(activity)=Ycalc= k1 X + k2
= -0.47 – 0.002
The correlation coefficient r for the above equation
calculated using:
r2 = 1 – SScalc / SSmean
Where SScalc= measure how much the experimental activity
of compounds varies from calculated value.
SSmean= measure how much the experimental activity varies
from the mean of all experimental activities.
Conti…
If there is a correlation between the activity (Y) and the
parameter (X), the line of the equation should pass closer to
the data pts than representing mean.
It means:
SScalc < SSmean
According to data:
r2= 1 – 0.1912/ 0.5279
= o.638
This shows 64%
variability in activity
due to parameter X .
This should be less
than 80% so equation
is not good one.
For a perfect
correlation
calculated values for
activity =
experimental ones.
r2= 1
Conti…
a) Hydrophobicity Log P (partition coefficient)
LogP = [drug] in octanol / [drug] in water
 Vary log P & see how this affects the biological activity.
 Biological activity normally expressed as 1/C, where C = [drug]
required to achieve a defined level of biological activity. The more
active drugs require lower concentration.
PHYSICOCHEMICAL PROPERTIES
 Plot log 1/C vs. log P
 Typically over a small range of log P, e.g. 1-4, a straight line
is obtained
log 1/C = k1 log P + k2
If graph is extended to very high log P values then get parabolic
curve. Reasons:
 poorly soluble in aqueous phase
 trapped in fat depots
 more susceptible to metabolism
Conti…
Straight line
For parabolic curve
Log 1/C = -k (logp)2 + k2 logp + k3
The substituent hydrophobicity
constant()
x = logpx – logph
Where-
Ph= partition coefficient of std
compound
Px= partition coefficient for std with
substituent
• b) Steric Effect
• The bulk, size and shape of drug will influence how easily it
can approach and interact with binding site. A bulky
substituent may help to orientate a drug properly for
maximum binding n increase activity.
• Examples are:
Taft’s steric factor (Es) (~1956), the value for Es can be
obtained by comparing the rates of hydrolysis of substituted
aliphatic esters against a std ester under acidic conditions.
Es = logkx – logk0
Kx - represents rate of hydrolysis of an aliphatic ester having
substituent X
K0 - represent rate of hydrolysis of reference ester.
Verloop steric parameter
It involves a computer program called sterimol which
calculates steric substituent values from std bond angles,
van der waals radii, bond lengths n conformations
Example : L= length of substituent
B1-B4= radii of grp in different dimensions.
c) Electronic Effect
• Hammet substituent constant ()
This is a measure of the electron-withdrawing or
electron-donating ability of a substituent.
x = log(kx/kh)= logkx – logkh
kh dissociation constant (H signifies that there is no
substituents on aromatic ring).
Examples
COOH COO + H K0
COOH COO + H KpX X
COOH COO + H Km
X X
para = log10
meta = log10
Kp
Km
K0
K0
Electron withdrawing group, result in the aromatic ring
having a stronger and stabilizing influence on carboxylate
anion.
The equilibrium shift more to ionized form such n larger kx
value. (+ve  value).
If substituent X is an electron donating group such as alkyl,
then aromatic ring less able to stabilize the carboxylate ion.
Equilibrium shifts to left n smaller kx value. ( -ve  value)
Conti…
Application of QSAR
Diagnosis of MOA of drug.
Prediction of activity.
Prediction of toxicity.
Lead compound optimization.
Environmental chemistry.
Advantages
• Quantifying the relationship between structure and activity
provides an understanding of the effect of structure on activity.
• It is also possible to make predictions leading to synthesis of
novel analogues.
The results can be used to help understand interaction between
functional groups in the molecules of greatest activity with
those of their target
Disadvantages
 False correlations because biological data that are
considerable experimental error.
If training dataset is not large enough , the data collected may
not reflect the complete property.
Features may not be reliable. This is particularly serious for 3D
features because 3D structures of ligands binding to receptor
may not available
HANSCH EQUATION
• In a simple situation where biological activity is related to
only one such property, a simple equation can be drawn up.
The biological activity of most drugs, however, is related to a
combination physicochemical properties. In such cases,
simple equations involving only one parameter are relevant
only if the other parameters are kept constant. In reality, this
is not easy to achieve and equations which relate biological
activity to a number of different parameters are known as
HANSCH EQUATION.
• They relate biological activity to the most commonly used
physicochemical properties (logp or ,  and a steric factor).
 If the range of hydrophobicity values is limited then the
equation will be linear , as follows:
• Log(1/C) = k1 logP + k2 + k3 Es + k4
•
• If the logP values are spread over the large range, then the
equation will be parabolic:
• LogP= -k1 (logP)2 + K2 logP + k3  + k4 Es +k5
• (the constants k1-k5 are determined by computer software in
order to get best fitting equation)
HANSCH EQUATION
Hansch equations
log 1/C = 1.22  – 1.59  + 7.89
(n=22; s=0.238; r= 0.918
log 1/C = 0.398  + 1.089  + 1.03 Es + 4.541
(n=9; r= 0.955)
log Cb = 0.765  = 0.540  2 + 1.505
log 1/c = 1.78  – 0.12  + 1.674
Merits of Hansch Analysis
•
1. Correlates activities with physicochemical parameters
2. “Outside” predictions are possible
Limitations of Hansch analysis
• 1. There must be parameter values available for the
substituent’s in the data set
• 2. A large number of compounds is required.
• 3. Depends on biological results (Chance of error)
• 4. Interrelationship of parameters
• 5. Groups should be selected in such a way that it should
contain at least one representative from each cluster.
• 6. Lead optimization technique, not a lead discovery
technique.
• 7. Risk of failure in “too far outside” predictions
conclusion
 QSAR relate the physiological properties of a series of
drug to their biological activity by means of
mathematically equation.
REFERENCES
 Patrick L. Graham “An introduction to medicinal chemistry’’ 4th edition by
Oxford University , New York
 http://www.ccl.net/qsar/archives/0207/0029.html
 http://www.srmuniv.ac.in/downloads/qsar.pdf&sa=u&ved
THE END!

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Qsar by hansch analysis

  • 1. QSAR BY HANSCH ANALYSIS Presented by – Vishal Singh Solanki Guided by – Dr. A. Basu
  • 2. CONTENT  Introduction  Graph and equation  Regression or correlation coefficient  Physicochemical properties  Application of qsar  Advantages  Disadvantages  Hansch equation  References
  • 3. INTRODUCTION  The identification of a new drug molecule requires a lot of synthesis, time and money. It was identified that out of billion molecules synthesized, around one or two molecules reach the clinical trials.  The quantitative structure activity relationship approach has proved extremely useful in overcome this problem.  QSAR approach attempts to identify and quantify the physicochemical properties of a drug and to see whether any of these properties has an effect on the drug’s biological activity.
  • 4. Graphs and equations • A range of compounds is synthesized in order to vary one physicochemical property and to test how this affects the biological activity. A graph is then plot the biological activity 0n the y-axis versus the physicochemical feature on x-axis.
  • 5. The best line will be the closet to the data points . To measure how close the data points vertical lines are drawn from each points. The best line through the points will be the line where total is minimum. Conti…
  • 6. Regression or correlation coefficient (r) : It is measure of how well the equation explains the variance in activity observed in terms of physicochemical parameters present in the equation. To illustrate ‘r’ following numerical data will be used. There are 6 compounds in the study (n=6). Yexp = log(observed activity) X = physicochemical property
  • 7. • ( Yexp – Ycalc)2 = Sscalc • ( Yexp – Ymean)2 = SSmean Conti…
  • 8. The QSAR equation derived from the data is: log(activity)=Ycalc= k1 X + k2 = -0.47 – 0.002 The correlation coefficient r for the above equation calculated using: r2 = 1 – SScalc / SSmean Where SScalc= measure how much the experimental activity of compounds varies from calculated value. SSmean= measure how much the experimental activity varies from the mean of all experimental activities. Conti…
  • 9. If there is a correlation between the activity (Y) and the parameter (X), the line of the equation should pass closer to the data pts than representing mean. It means: SScalc < SSmean According to data: r2= 1 – 0.1912/ 0.5279 = o.638 This shows 64% variability in activity due to parameter X . This should be less than 80% so equation is not good one. For a perfect correlation calculated values for activity = experimental ones. r2= 1 Conti…
  • 10. a) Hydrophobicity Log P (partition coefficient) LogP = [drug] in octanol / [drug] in water  Vary log P & see how this affects the biological activity.  Biological activity normally expressed as 1/C, where C = [drug] required to achieve a defined level of biological activity. The more active drugs require lower concentration. PHYSICOCHEMICAL PROPERTIES
  • 11.  Plot log 1/C vs. log P  Typically over a small range of log P, e.g. 1-4, a straight line is obtained log 1/C = k1 log P + k2 If graph is extended to very high log P values then get parabolic curve. Reasons:  poorly soluble in aqueous phase  trapped in fat depots  more susceptible to metabolism Conti…
  • 12. Straight line For parabolic curve Log 1/C = -k (logp)2 + k2 logp + k3 The substituent hydrophobicity constant() x = logpx – logph Where- Ph= partition coefficient of std compound Px= partition coefficient for std with substituent
  • 13. • b) Steric Effect • The bulk, size and shape of drug will influence how easily it can approach and interact with binding site. A bulky substituent may help to orientate a drug properly for maximum binding n increase activity. • Examples are: Taft’s steric factor (Es) (~1956), the value for Es can be obtained by comparing the rates of hydrolysis of substituted aliphatic esters against a std ester under acidic conditions. Es = logkx – logk0 Kx - represents rate of hydrolysis of an aliphatic ester having substituent X K0 - represent rate of hydrolysis of reference ester.
  • 14. Verloop steric parameter It involves a computer program called sterimol which calculates steric substituent values from std bond angles, van der waals radii, bond lengths n conformations Example : L= length of substituent B1-B4= radii of grp in different dimensions.
  • 15. c) Electronic Effect • Hammet substituent constant () This is a measure of the electron-withdrawing or electron-donating ability of a substituent. x = log(kx/kh)= logkx – logkh kh dissociation constant (H signifies that there is no substituents on aromatic ring).
  • 16. Examples COOH COO + H K0 COOH COO + H KpX X COOH COO + H Km X X para = log10 meta = log10 Kp Km K0 K0
  • 17. Electron withdrawing group, result in the aromatic ring having a stronger and stabilizing influence on carboxylate anion. The equilibrium shift more to ionized form such n larger kx value. (+ve  value). If substituent X is an electron donating group such as alkyl, then aromatic ring less able to stabilize the carboxylate ion. Equilibrium shifts to left n smaller kx value. ( -ve  value) Conti…
  • 18. Application of QSAR Diagnosis of MOA of drug. Prediction of activity. Prediction of toxicity. Lead compound optimization. Environmental chemistry.
  • 19. Advantages • Quantifying the relationship between structure and activity provides an understanding of the effect of structure on activity. • It is also possible to make predictions leading to synthesis of novel analogues. The results can be used to help understand interaction between functional groups in the molecules of greatest activity with those of their target
  • 20. Disadvantages  False correlations because biological data that are considerable experimental error. If training dataset is not large enough , the data collected may not reflect the complete property. Features may not be reliable. This is particularly serious for 3D features because 3D structures of ligands binding to receptor may not available
  • 21. HANSCH EQUATION • In a simple situation where biological activity is related to only one such property, a simple equation can be drawn up. The biological activity of most drugs, however, is related to a combination physicochemical properties. In such cases, simple equations involving only one parameter are relevant only if the other parameters are kept constant. In reality, this is not easy to achieve and equations which relate biological activity to a number of different parameters are known as HANSCH EQUATION. • They relate biological activity to the most commonly used physicochemical properties (logp or ,  and a steric factor).  If the range of hydrophobicity values is limited then the equation will be linear , as follows:
  • 22. • Log(1/C) = k1 logP + k2 + k3 Es + k4 • • If the logP values are spread over the large range, then the equation will be parabolic: • LogP= -k1 (logP)2 + K2 logP + k3  + k4 Es +k5 • (the constants k1-k5 are determined by computer software in order to get best fitting equation) HANSCH EQUATION
  • 23. Hansch equations log 1/C = 1.22  – 1.59  + 7.89 (n=22; s=0.238; r= 0.918 log 1/C = 0.398  + 1.089  + 1.03 Es + 4.541 (n=9; r= 0.955) log Cb = 0.765  = 0.540  2 + 1.505 log 1/c = 1.78  – 0.12  + 1.674
  • 24. Merits of Hansch Analysis • 1. Correlates activities with physicochemical parameters 2. “Outside” predictions are possible
  • 25. Limitations of Hansch analysis • 1. There must be parameter values available for the substituent’s in the data set • 2. A large number of compounds is required. • 3. Depends on biological results (Chance of error) • 4. Interrelationship of parameters • 5. Groups should be selected in such a way that it should contain at least one representative from each cluster. • 6. Lead optimization technique, not a lead discovery technique. • 7. Risk of failure in “too far outside” predictions
  • 26. conclusion  QSAR relate the physiological properties of a series of drug to their biological activity by means of mathematically equation.
  • 27. REFERENCES  Patrick L. Graham “An introduction to medicinal chemistry’’ 4th edition by Oxford University , New York  http://www.ccl.net/qsar/archives/0207/0029.html  http://www.srmuniv.ac.in/downloads/qsar.pdf&sa=u&ved