2. New compounds with improved biological activity
What is QSAR?
Compounds + biological activity
QSAR
New compounds with improved biological activity

4. Application of QSAR Diagnosis of MOA of drug.
Prediction of activity.
Prediction of toxicity.
Lead compound optimization.
Environmental chemistry.

11. Introduction
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

13. Molecular Descriptors used in QSAR
Molecular descriptors can be defined as a numerical representation of chemical information encoded within a molecular structure via mathematical procedure. This mathematical representation has to be invariant to the molecule’s size and number of atoms to allow model building with statistical methods.
The information content of structure descriptors depends on two major factors:
The molecular representation of compounds.
(2) The algorithm which is used for the calculation of the descriptor.
The three major types of parameters initially suggested are,
(1) Hydrophobic
(2) Electronic
(3) Steric

17. A range of compounds is synthesized in order to vary one physicochemical property and to test it affects the bioactivity.
A graph is then drawn to plot the biological activity on the y axis versus the physicochemical feature on the x axis.
It is necessary to draw the best possible line through the data points on the graph. This done by procedure known as linear regression analysis by the least square method.

18. If we draw a line through a set of data points will be scattered on either side of the line. The best line will be the one closest to the data points.
To measure how close the data points are , vertical lines are drawn from each point.
Log (1/C)
Log P .
0.78
3.82

19. This relative distribution is known as partition coefficient.
HYDROPHOBICITY
Hydrophobic character of a drug is crucial to how easily it crosses the cell membrane and may also important in receptor interactions.
Hydrophobicity of a drug is measured experimentally by testing the drugs relative distribution in octanol water mixture.
This relative distribution is known as partition coefficient.
Partition Coefficient P = conc. Drug in in octanol]
[Conc.of drug in water]

21. Hydrophobicity of the Molecule
Partition Coefficient P =
[Drug
in octanol]
[Drug in water]
High P
High hydrophobicity

22. . Activity of drugs is often related to P
Biological activity log(1/c) = K1 log P + K2
Eg: binding of a drug to serum albumin determined by hydrophobicity and study of 42 compounds.
(straight line - limited range of log P)
Log (1/C)
Log P .
0.78
3.82
log(1/c) = log P + 230
(n= 42, r= s= 0.159)

23. log(1/c) = -K1 (log P)2 + K2 log P + k3
If the partition coefficient is the only factor influencing biological activity, the parabolic curve can expressed by the equation
log(1/c) = -K1 (log P)2 + K2 log P + k3
Few drugs where activity is related to log P factor alone.
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
Log P o
Log (1/C)

24. THE SUBSTITUENT HYDROPHOBICITY CONSTANT (π)
Partition coefficient can be calculated by knowing the contribution that various substituents, is known as substituent hydrophobicity constant(π)
A measure of a substituent’s hydrophobicity relative to hydrogen
Partition coefficient is measured experimently for a standard compound such as benzene with or without a substituent (X).
The hydrophobicity constant (π x) for sustituent X.
The equation is
x= logPx-logPH

25. A negative value indicates that the substituent is less hydrophobic.
A possitive  value shows that the substituent is more hydrophobic than hydrogen
A negative value indicates that the substituent is less hydrophobic.
The  value is charecteristic for sustituent. 
Example:
pCl = 0.71
pCONH = -1.49 2

26. A QSAR equation may include both P and π.
THE SUBSTITUENT HYDROPHOBICITY CONSTANT (π)
Log P(theory) = log P(benzene) + pCl + pCONH =
= 1.35
Log P (observed) = 1.51 2
A QSAR equation may include both P and π.
P measures the importance of a molecule’s overall hydrophobicity (relevant to absorption, binding etc)
π identifies specific regions of the molecule which might interact
with hydrophobic regions in the binding site

27. ELECTRONIC EFFECT
The electronic effect of various sustituents will clearly have an effect on drug ionisation and polarity.
Have an effect on how easily a drug can pass through the cell membrane or how strongly it can interact with a binding site.
Hammet substituent constant(σ) this is a measure of electron with-drawing or electron-donating ability of a substituents on an aromatic ring.

29. σ for aromatic substituents is measured by comparing the dissociation constants of substituted benzoic acids with benzoic acid K H =
Dissociation constant
[PhCO 2 - ] H]

30. = log K logK - X= electron withdrawing group (e.g. NO2,)
Charge is stabilised by X
Equilibrium shifts to right
KX > KH s X =
log K H
logK -
Positive value

31. X= electron donating group (e.g. CH3)
Charge destabilised
Equilibrium shifts to left
KX < KH s X =
log K H
logK -
Negative value

32. e-withdrawing (inductive effect only)
EXAMPLES:
sp (NO2) = 0.78
sm (NO2) = 0.71
meta-Substitution
e-withdrawing (inductive effect only)
para-Substitution
e-withdrawing
(inductive +
resonance effects)

33. σ value depends on whether the substituent is meta or para
σ value depends on inductive and resonance effects
σ value depends on whether the substituent is meta or para
ortho values are invalid due to steric factors
Electronic Factors R & F
R - Quantifies a substituent’s resonance effects
F - Quantifies a substituent’s inductive effects
The constants σ,R and F can only be used for aromatic substituents

34. STERIC FACTORS
The bulk, size and shape of a drug will influence how easily it can approach and interact with binding site.
A bulky substituents may act like a shield and hinder the ideal interaction between a drug and its binding site.
Bulky substituent may help to orient a drug properly for maximum binding and increase activity.

36. Taft’s Steric Factor (Es)
Measured by comparing the rates of hydrolysis of substituted aliphatic esters against a standard ester under acidic conditions
Es = log kx - log ko
kx represents the rate of hydrolysis of a substituted ester
ko represents the rate of hydrolysis of the parent ester
Limited to substituents which interact sterically with the tetrahedral transition state for the reaction
Not by resonance or hydrogen bonding
Disadvantages
ES value measures intramolecular steric effect but drugs interact with target binding site in intermolecular process (i.e. a drug binding to a receptor)

37. MR = (n - 1) 2) x mol. wt. density
Molar Refractivity (MR)
this is a measure of a substituent’s volume MR = (n 2 - 1) 2) x
mol. wt.
density
Correction factor
for polarisation
(n=index of
refraction)
Defines volume
This is perticularly significant if the substituent has π electrons or lone pair of electrons

38. - calculated by software (STERIMOL)
Verloop Steric Parameter
- calculated by software (STERIMOL)
- gives dimensions of a substituent from the standard bond angle ,van der Waals radii, bond length and possible conformations for the substituents
- can be used for any substituent L B 3 4 B4 B3 B2 B1
Example - Carboxylic acid

39. CORWIN HANSCH ANALYSIS
The introduction of the Hansch model in 1964 enabled medicinal chemists to formulate their hypothesis of structure activity relationships in quantitative terms and to check these hypotheses by means of statistical methods.
A QSAR equation relating various physicochemical properties to the biological activity of a series of compounds
Usually includes log P, Electronic and Steric factors
Start with simple equations and elaborate as more structures are synthesised

41. Hansch’s Approach

42. 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

43. Free-Wilson analysis (structure-property relationship)
Free and Wilson (1964) formulated an additive model, where the activity is shown as a simple sum of contributions from different substituent's.
BA = ∑ai xi + µ
  BA = is the biological activity,
µ = is the average contribution of the parent molecule,
ai = is the contribution of each structural feature;
xi = denotes the presence Xi = 1 or absence Xi = 0 of a particular
structural fragment.
The biological activity of the parent structure is measured and compared with the activity of analogues bearing different substituent's
An equation is derived relating biological activity to the presence or absence of particular substituents

44. Free and Wilson derived a mathematical model that describes the presence and absence of certain structural features, i.e. those groups that are chemically modified, by values of 1 or 0 and correlate the resulting structural matrix with biological activity values,
the values ai in Eqn. are the biological activity group contributions of the substituents X1, X2,…Xi in the different positions P of compound, the most often the unsubstituted parent structure of a series.
The method of Free and Wilson is based upon an additive mathematical model in which a particular substituent in a specific position is assumed to make an additive and constant contribution to the biological activity of a molecule in a series of chemically related molecules.
This method is based on the assumption that the introduction of a particular substituent at a particular molecular position always leads to a quantitatively similar effect on biological potency of the whole molecule, as expressed by the equation
log 1/C = Σ ai + μ
ai = substituent group contributions.
μ = activity contribution of reference compound

45. Free-Wilson Approach Advantages
No need for physicochemical constants or tables
Useful for structures with unusual substituents
Useful for quantifying the biological effects of molecular features that cannot be quantified or tabulated by the Hansch method
Disadvantages
A large number of analogues need to be synthesised to represent each different substituent and each different position of a substituent
It is difficult to rationalise why specific substituents are good or bad for activity
The effects of different substituents may not be additive (e.g. intramolecular interactions)

46. Mixed Hansch/Free-Wilson model Log 1/C = ∑ai + ∑cj Фj + constant
The similarity in approaches of Hansch analysis and Free-Wilson analysis allows them to be used within the same framework. This is based on their theoretical consistency and the numerical equivalencies of activity contributions. This development has been called the mixed approach and can be represented by the following equation:
Log 1/C = ∑ai + ∑cj Фj + constant
The term ai denotes the contribution for each xi substituent,
whereas Фj is any physicochemical property of a substituent Xj.
Above Equation combines the advantages of Hansch and Free – Wilson analyses and widens the applicability of both methods. Physicochemical parameters describe parts of the molecules with broad structural variation, whereas indicator variables ai (Free Wilson type variables) encode the effects of structural variations that cannot be described otherwise.
A recent study of the P - glycoprotein inhibitory activity of 48 propafenone-type modulators of multidrug resistance, using a combined Hansch/Free-Wilson approach was deemed to have higher predictive ability than that of a stand-alone Free-Wilson analysis.

47. Advantages of QSAR Studies
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