Estrogen receptors (ERs) are basically the group of proteins found inside and on the cells & Estrogen (17β-estradiol) is the activator of Ers. The estrogen belongs to the sex steroid hormones & plays crucial role in female reproductive system and also exerts important effects on non-reproductive targets such as bone, cardiovascular system and neural sites involved in cognition. ER­β is expressed in a variety of the normal and malignant tissues, modulation of immune responses. Quantitative Structure-Activity Relationship(QSAR) is an approach which is designed to find relationship between the chemical structure (structural related properties) and the biological activity (target property) of the studied compounds. So to identify & study various modulators for the ER-Beta and their function has been performed.

1. BY-
Siddharth Singh -1314354041

2. INTRODUCTION
• Estrogen receptors (ERs) are basically the group of proteins found inside and on
the cells & Estrogen (17β-estradiol) is the activator of Ers.
• The estrogen belongs to the sex steroid hormones & plays crucial role in female
reproductive system and also exerts important effects on non-reproductive targets
such as bone, cardiovascular system and neural sites involved in cognition. ERβ is
expressed in a variety of the normal and malignant tissues, modulation of immune
responses.
• Quantitative Structure-Activity Relationship(QSAR) is an approach which is
designed to find relationship between the chemical structure (structural related
properties) and the biological activity (target property) of the studied compounds.
• So to identify & study various modulators for the ER-Beta and their function has
been performed.

3. Objective
 To study the role & implication of estrogen receptor-β in various
diseases.
 To identify different potent inhibitor’s which can modulate the
activity of ER-β.
 To identify different type of QSAR modal development (2D & 3D).
 To develop a QSAR modal for the study of activity modulation as
the function of structural property of ER-β.

4. Method
 Materials
Structure of ER-β (obtained from PDB database).
Modulators (obtained from zinc database).
QSAR (done by multiple regression tools(XURU)).
 Methods
Structure of modulators & ER-beta has been analyzed from Rcsb(Pdb
database).
Collection of literature & structure has been done.
Development of QSAR modal for the study of modulator activity on ER-β
structure has been performed.

5. Identifications of different ER- β modulators.

6. •List of ER- modulating ligand
molecule and their
corresponding activity.
•Total 19 known modulators of
ER- have been selected and
downloaded from zinc
database. Among which 80% of
data were taken as training
dataset and remaining as
testing dataset.
• Training dataset was used for
the model development and
testing dataset was used to test
the model accuracy by
calculating atious error like
absolute error, RMS error and
coefficient of correltion. The
complete list of modulators is
given in table.

7. Regression analysis by online tool
 http://www.xuru.org/rt/MLR.asp#Manually.

8. Result
 The following regression equation was generated after doing multi
regression analysis.
 Y = -1.098918592 X1 +1.61848094 x 10-2 X2 + 1.104466751 x 10-1 X3 -
1.938974863 X4 – 1.514754566 x 10-1 X5 + 8.346848049 X6 +
5.296854305 x 10-2 X7 + 1.734491479 x 10-2 X8 – 5.390398764 x 10-1 X9 +
2.618696083.
 Coefficient from above equation was used to calculate the activity of
test dataset in Microsoft excel 2007 and corresponding errors were
measured between actual and calculated values.
 The table-3 on next slide shows the actual activity and calculated
activity of testing dataset.

10. 0
0.5
1
1.5
2
2.5
3
3.5
1 2 3 4
Calculatedactivity
Actual activity
Correlation of actual vs. calculated
activity
Actual
Calculated
•A graph was plotted between actual activity and
calculated activity as shown in figure 6 to better
understand the correlation.
•The higher accuracy of the model makes it
suitable for the prediction of other modulator
ligand molecules as well. This model can also be
used to assess the effect of structural change in
any descriptor mentioned above on their activity
of respective compound.
•After the structural analysis, it has been found
that the xlogP value, number of Hydrogen bond
donor, Net charge and number of rotatable
bonds of any modulator highly affect the activity
of that compound.
•Any slight variation in these descriptors shows
large change in the activity. Whereas the
remaining descriptors having slightly less effect
on the activity. Hence it can also be concluded
that the activity of any compound is highly
dependent upon its structural properties.