This document discusses structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs) in drug design. It explains that compounds with similar structures to an active drug are often biologically active as well, and studying their SARs can provide information about what parts of the structure are responsible for the drug's effects and side effects. QSARs attempt to mathematically relate biological activity to measurable physicochemical parameters like lipophilicity, electronic effects, and steric effects. Parameters like partition coefficients, Hammett constants, and Taft steric constants are used to represent these properties in equations. Hansch analysis and Craig plots are also discussed as methods to predict potential drug activity based on these quantitative relationships.

1. Principles & Applications of
Structure Activity Relationship
(SAR) Presented By
NIZAM ASHRAF
OST-2018-22-15
KUFOS

2. Structure–activity relationships (SARs)
• Compounds with similar structures to a pharmacologically active drug
are often themselves biologically active.
• This activity may be either similar to that of the original compound but
different in potency and unwanted side effects or completely different
to that exhibited by the original compound.
• These structurally related activities are commonly referred to as
structure–activity relationships (SARs).
• A study of the structure–activity relationships of a lead compound and
its analogues may be used to determine the parts of the structure of
the lead compound that are responsible for both its beneficial
biological activity, that is, its pharmacophore, and also its unwanted
side effects.
• This information may be used to develop a new drug that has
increased activity, a different activity from an existing drug and fewer
unwanted side effects

3. • Structure–activity relationships are usually determined by making
minor changes to the structure of a lead to produce analogues and
assessing the effect these structural changes have on biological activity.
• These changes may be conveniently classified as changing :
1. the size and shape of the carbon skeleton
2. the nature and degree of substitution
3. the stereochemistry of the lead
1. Changing size and shape
The shapes and sizes of molecules can be modified in a variety of
ways, such as :
• Changing the number of methylene groups in chains and rings
• Increasing or decreasing the degree of unsaturation
• Introducing or removing a ring system.
These types of structural change usually result in analogues that
exhibit either a different potency or a different type of activity to the
lead.

5. 2. Introduction of new substituents
• The new substituents may either occupy a previously unsubstituted
position in the lead compound or replace an existing substituent.
• Each new substituent will impart its own characteristic chemical,
pharmacokinetic and pharmacodynamic properties to the analogue.
• Moreover, the practical results of such a structural change will often
be different from the theoretical predictions.
2.1. The introduction of a group in an unsubstituted position
• The incorporation of any group result in analogues with different size
and shape to the lead compound.
• It may introduce a chiral centre, which will result in the formation of
stereoisomers, which may or may not have different pharmacological
activities.
• The introduction of a new group may result in an increased rate of
metabolism, a reduction in the rate of metabolism or an alternative
route for metabolism. These changes could also change the duration
of action and the nature of any side effects.

6. 2.2. The introduction of a group by replacing an existing group
• The choice of group will depend on the objectives and is often
made using the concept of isosteres.
• Isosteres are groups that exhibit some similarities in their
chemical and/or physical properties. (pharmacokinetic and
pharmacodynamic properties).
• The replacement of a substituent by its isostere is more likely
to result in the formation of an analogue with the same type
of activity as the lead than the totally random selection of an
alternative substituent.

7. • However, luck still plays a part, and an isosteric analogue may
have a totally different type of activity from its lead.
• A large number of drugs have been discovered by isosteric
interchanges

9. Quantitative structure–activity relationships
(QSARS)
• QSAR is an attempt to remove the element of luck from drug design
by establishing a mathematical relationship in the form of an
equation between biological activity and measurable
physicochemical parameters.
• The main properties of a drug that appear to influence its activity
are its, lipophilicity, the electronic effects within the molecule and
the size and shape of the molecule (steric effects).
• Lipophilicity is a measure of a drug’s solubility in lipid membranes.
• The electronic effects of the groups within the molecule will affect
its electron distribution, which in turn has a direct bearing on how
easily and permanently the molecule binds to its target molecule.
• Drug size and shape will determine whether the drug molecule is
able to get close enough to its target site in order to bind to that
site.

10. • The parameters commonly used to represent these properties
are partition coefficients for lipohilicity, Hammett σ
constants for electronic effects and Taft Ms steric constants
for steric effects.
• QSAR derived equations take the general form:
biological activity = function{parameter(s)}
in which the activity is normally expressed as
log[1/(concentration term)], usually C, the minimum
concentration required to cause a defined biological response
1. Liphophilicity
Two parameters are commonly used to represent
lipophilicity:
1.1 Partition coefficient (P)
1.2 Lipophilicity substituent constant (π).
The partition coefficient parameter refers to the whole
molecule while the latter is related to substituent groups.

11. 1.1 Partition coefficients (P)
• A drug has to pass through a number of biological membranes
in order to reach its site of action.
• Organic medium/aqueous system partition coefficients were
the obvious parameters to use as a measure of the ease of
movement of the drug through these membranes.
• The accuracy of the correlation of drug activity with partition
coefficients will depend on the solvent system used as a
model for the membrane.
• The nature of the relationship between P and drug activity
depends on the range of P values obtained for the compounds
used. If this range is small the results may be expressed as a
straight line equation having the general form:
k1,k2 are constansts

12. • This equation indicates a linear relationship between the
activity of the drug and its partition coefficient.
• Over larger ranges of P values the graph of log 1/C against log
P often has a parabolic form with a maximum value (log P0).
• The existence of this maximum value implies that there is an
optimum balance between aqueous and lipid solubility for
maximum biological activity.
• Below P0 the drug will be reluctant to enter the membrane
whilst above P0 the drug
will be reluctant to leave the
membrane.
• Log P0 represents the optimum
partition coefficient for biological
activity. This means that analogues
with partition coefficients near
this optimum value are likely to
be the most active and worth further investigation.

13. 1.2 Lipophilic substituent constants (π)
• Lipophilic substituent constants are also known as hydrophobic
substituent constants.
• They represent the contribution that a group makes to the partition
coefficient and were defined by Hansch and co-workers by the
equation:
• where PRH and PRX are the partition coefficients of the standard
compound and its monosubstituted derivative respectively.
• When several substituents are present, the value of π for the
compound is the sum of the π values of each of the separate
substituents.
• The value of π for a specific substituent will vary with the structural
environment of the substituent and also depends on the solvent
system used to determine the partition coefficients.

14. • A positive π value indicates that a substituent has a higher
lipophilicity than hydrogen and so will increase the concentration of
the compound in the lipid material of biological systems.
• A negative π value shows that the substituent has a lower
lipophilicity than hydrogen and so probably increases the
concentration of the compound in the aqueous media of biological
systems.
2. Electronic effects
• The distribution of the electrons in a drug molecule has an influence
on the activity of a drug.
• Non-polar and polar drugs in their unionized form are more readily
transported through membranes than polar drugs and non-polar
drugs in their ionized forms.
• Once the drug reaches its target site the distribution of electrons in
its structure will control the type of bond it forms with that target,
resulting in its biological activity.
• The first attempt to quantify the electronic affects of groups on the
physicochemical properties of compounds was made by Hammett

15. • The Hammett constant (σ)
• The distribution of electrons within a molecule depends on the
nature of the electron withdrawing and donating groups found in
that structure.
• Hammett used this concept to calculate what are now known as
Hammett constants (σX ) for a variety of monosubstituted benzoic
acids. He used these constants to calculate equilibrium and rate
constants for chemical reactions.
• Hammett constants (σX ) defined as :

16. • Hammett postulated that the σ values calculated for the ring
substituents of a series of benzoic acids could also be valid for
those ring substituents in a different series of similar aromatic
compounds.
• This relationship has been found to be in good agreement for
the meta and para substituents of a wide variety of aromatic
compounds but not for their ortho substituents due to steric
hindrance or due to intramolecular hydrogen bonding.
• Hammett substitution constants contain the disadvantage
that they only apply to substituents directly attached to a
benzene ring.
• However, attempts to relate biological activity exclusively to
the values of Hammett substitution and similar constants
have been largely unsuccessful, since electron distribution is
not the only factor involved.

17. 3. Steric effects
• The first parameter used to show the relationship between
the shape and size of a drug, the dimensions of its target site
and the drug’s activity was the Taft steric parameter (Es).
• Followed by Charton’s steric parameter, Verloop’s steric
parameters and the molar refractivity (MR). The most used of
these additional parameters is probably the molar refractivity.
• The molar refractivity is a measure of both the volume of a
compound and how easily it is polarized. It is defined as:

18. • where n is the refractive index, M the relative mass and p the
density of the compound. The M/p term is a measure of the
molar volume whilst the refractive index term is a measure of
the polarizability of the compound.
• Although MR is calculated for the whole molecule, it is an
additive parameter, and so the MR values for a molecule can
be calculated by adding together the MR values for its
component parts.
4. Hansch analysis
• Hansch analysis attempts to mathematically relate drug
activity to measurable chemical properties.
• It is based on Hansch’s proposal that drug action could be
divided into two stages:
– the transport of the drug to its site of action;
– the binding of the drug to the target site.

19. • Each of these stages is dependent on the chemical and physical
properties of the drug and its target site.
• Hansch postulated that the biological activity of a drug could be
related to these parameters by simple mathematical relationships
based on the general format:
log 1/C = k1(partition parameter) +k2(electronic parameter) + k3(steric
parameter) + k4
• where C is the minimum concentration required to cause a specific
biological response and k1, k2, k3 and k4 are numerical constants.
• The accuracy of a Hansch equation will depend on
– the number of analogues (n) used : the greater the number the higher
the probability of obtaining an accurate Hansch equation
– the accuracy of the biological data used in the derivation of the
equation
– the choice of parameter

20. • The accuracy of a Hansch equation may be assessed from the
values of the standard deviation (s) and the regression
constant (r) given by the statistical package used to obtain the
equation.
• Values of r that are significantly lower than 0.9 indicate that
either unsuitable parameter(s) were used to derive the
equation or there is no relationship between the compounds
used and their activity.
• Hansch equations may be used to predict the activity of an as
yet unsynthesized analogue

21. Craig plots
• Craig plots are two dimensional plots of one parameter
against another.
• The plot is divided into four sections corresponding to the
positive and negative values of the parameters.
• They are used, in conjunction with an already established
Hansch equation for a series of related aromatic compounds,
to select the aromatic substituents that are likely to produce
highly active analogues.
• For example, suppose that a Hansch analysis carried out on a
series of aromatic compounds yields the Hansch equation:

23. • To obtain a high value for the activity (1/C) it is necessary to
pick substituents with a positive π value and a negative σ
value.
• If high activity analogues are required, the substituents should
be chosen from the lower right hand quadrant of the plot.
• However, the use of a Craig plot does not guarantee that the
resultant analogues will be more active than the lead because
the parameters used may not be relevant to the mechanism
by which the analogue acts.

24. THANK YOU