QSAR

(Quantitative Structure Activity Relationship)

Quantitative structure-activity

relationships collectively referred to as QSARs, theoretical models that can be

used to predict the physicochemical and biological properties of molecules. A structure-activity relationship (SAR)

is a (qualitative) association between a chemical substructure and the

potential of a chemical containing the substructure to exhibit a certain

biological effect. A quantitative structure-activity relationship (QSAR) is a

mathematical model that relates a quantitative measure of chemical structure

(e.g. a physicochemical property) to a physical property or to a biological

effect (e.g. a toxicological endpoint).

This approach attempts to identify and

quantify the physicochemical properties of a drug and to see whether any of

these properties has an effect on drugs biological activity. If such a relationship holds true, an

equation can be drawn up which quantifies the relationship and allows the

medicinal chemist to say with some confidence that property has an important

role in the distribution or mechanism of the drug. By quantifying

physiochemical properties, it should be possible to calculate in advance what

the biological activity of a novel analogue might be.

PURPOSE

OF QSAR

There

are many practical purposes of a QSAR and these techniques are utilized widely

in many situations. The purpose of in silico studies, therefore, includes the

following:

To

predict biological activity and physico-chemical properties by rational means.

To

comprehend and rationalize the mechanisms of action within a series of

Chemicals.

Underlying

these aims, the reasons for wishing to develop these models include

Savings

in the cost of product development (e.g. in the pharmaceutical, pesticide,

Personal products, etc. areas).

Predictions

could reduce the requirement for lengthy and expensive animal tests.

Reduction

(and even, in some cases, replacement) of animal tests, thus reducing animal

use and obviously pain and discomfort to animals.

Other

areas of promoting green and greener chemistry to increase efficiency and

eliminate waste by not following leads unlikely to be successful.

Graphs and equations

A range of compounds are synthesized in

order to vary one physiochemical property (log P) and to test how this affects

the biological activity (log 1/C). A graph is then drawn to plot the biological

activity on the y-axis and physiochemical features on the x-axis. It is

necessary to draw the best possible line through the data points on the graph.

This is done by a procedure known as ‘linear regression analysis by the least

square method’. 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. These verticals are measured and then squared in order to eliminate the

negative values. The squares are then added up to give a total. The best line

through the points will be the line where this total is a minimum.

The equation of the straight line will be

y = k1x + K2 where k1 and K2 are constants. By varying k1 and K2, different

equations are obtained until the best line is obtained. This whole process can

be speedily done by computer programme. The significance of the equation is

given by a term known as the regression coefficient (r). This coefficient can

again calculated by computer. For a perfect fit r2 = 1. Good fits generally

have r2 values of 0.95 or above.

Physiochemical properties

There are many physical, structural and

chemical properties which have been studied by the QSAR approach, but the most

commonly studied are hydrophobic, electronic and steric. This is because it is

possible to quantify these effects relatively easy.

Hydrophobicity

The hydrophobic character of a drug is

crucial to how easily it crosses the cell membranes and may also be important

in receptor interactions. Changing substituents on a drug may well have

significant effects on its hydrophobic character and hence its biological

activity. Therefore it is important to have a means of predicting this

quantitatively.

The

partition coefficient (P)

The hydrophobic character of a drug

can be measured experimentally by testing the drug’s relative distribution in

an octanol/water mixture. Hydrophobic molecules will prefer to dissolve in the

octanol layer of this two-phase system, whereas hydrophilic molecules will

prefer the aqueous layer. The relative distribution is known as the partition

coefficient and is obtained from the following equation:

P

= Concentration of drug in octanol/ Concentration of drug in aqueous solution

Hydrophobic

compounds will have a high P value, whereas hydrophilic compounds will have a

low P value.

The

graph is dawn by plotting log (1/C) versus log P; a straight line graph is

obtained showing that there is a relation between hydrophobicity and biological

activity. Such a line would have the following equation:

log

(1/C) = k1log P + k2

Electronic

effect

The electronic effect of various

substituents will clearly have an effect on a drug’s ionization or polarity.

This in turn may have an effect on how easily a drug can pass through cell

membrane or how strongly it can bind to a receptor.

Hammett

Substitution Constant (?)

Hammett constant

(1940) is a measure of e-withdrawing or e-donating effects exerted by the

substituents on the reaction center.

The

e-withdrawing groups stabilize the carboxylate ion: larger Kx, and have positive ? values, e.g.

Cl, CN, CF3.

The

e-donating groups (e.g. alkyl), equilibrium shifts left (favouring protonated):

lower Kx and negative ? values.

Hammett

constant takes into account both resonance and inductive effects; thus, the

value depends on whether the substituent is Para or Meta substituted.

The ortho position is not measured due to steric effects. In some

positions only inductive effects effect & some both resonance &

inductive effects play a part. The electronic substitute constants are also

available for aliphatic groups

Example

of resonance forms that stabilize the negative charged carboxylate in

p-nitrobenzoic acid

The Hammett

constants, ? can be related to

the free energy of ionization via the Vant Hoff relationship (In this case ? would correspond to the equilibrium

constant, K, allowing for Hammett

This

relationship is to also be referred to as linear free energy relationship

(LFER)). Uses: Only one known example where just Hammett constants effectively

predict activity (insecticides, diethyl phenyl phosphates. These drugs do not

have to pass into or through a cell membrane to have activity).

Log

(1/C) = 2.282 s – 0.348

Steric

effects

It

is much harder to quantify. Examples are:

·

Taft’s steric factor (Es) (~1956), 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 der Waals radii, bond lengths.

Hansch

Analysis

It

is proposed that drug action could be divided into 2 stages: 1)

Transport & 2) Binding

Log

1/C = k1P = k2P2 + k3s + k4Es + k5

Hansch Analysis looks

at size and sign for each component of the equation.

If

values of r 0. Pa and Pi are the estimates of probability for the compound to be

active and inactive respectively for each type of activity from the biological

activity spectrum. Their values vary from 0.000 to 1.000. It is reasonably that

only those types of activities may be revealed by the compound, which Pa >

Pi and so they are put into the biological activity spectrum.

If Pa > 0.7 the compound

is very likely to reveal this activity in experiments, but in this case the

chance of being the analogue of the known pharmaceutical agents for this

compound is also high.

If 0.5