Developing qsar, evaluation of qsar model and virtual screening

1. Lecture 11 – Developing QSAR, Evaluation of QSAR model and virtual screening,
Applications of QSAR
BTT- 516– Drug Designing and Development

2. Topics to be covered today
1. Historical QSAR equation
2. Deriving QSAR
3. Validation methods
4. Homework

3. Rationale for QSAR Studies
• A quantitative structure-activity relationship (QSAR) correlates measurable
or calculable physical or molecular properties to some specific biological
activity in terms of an equation.
• Once a valid QSAR has been determined, it should be possible to predict the
biological activity of related drug candidates before they are put through
expensive and time-consuming biological testing. In some cases, only
computed values need to be known to make an assessment.

4. History of QSAR
• The first application of QSAR is attributed to Hansch (1969), who
developed an equation that related biological activity to certain electronic
characteristics and the hydrophobicity of a set of structures.
log (1/C) = k1log P - k2(log P)2 + k3s + k4
C = minimum effective dose
P = octanol - water partition coefficient
s = Hammett substituent constant
kx= constants derived from regression analysis

5. Hansch’s Approach
• Log P is a measure of the drug’s hydrophobicity, which was selected as a
measure of its ability to pass through cell membranes.
• The log P (or log Po/w) value reflects the relative solubility of the drug in
octanol (representing the lipid bilayer of a cell membrane) and water (the
fluid within the cell and in blood).
• Log P values may be measured experimentally or, more commonly,
calculated.

6. Calculating Log P
Log P = Log K (o/w) = Log ([X]octanol/[X]water)
• Most programs use a group additivity approach:
1 Aromatic ring 0.780
7 H’s on Carbon 1.589
1 C-Br bond-0.120
1 alkyl C 0.195 Sum = 2.924 = calc. log P
• Some use more complicated algorithms, including factors such as the dipole
moment, molecular size and shape.
CH2 Br

7. Hammett Equation
• Hammett observed a linear free energy relationship between the log of the
relative rate constants for ester hydrolysis and the log of the relative acid
ionization (equilibrium) constants for a series of substituted benzoic esters
& acids.
log (kx/kH) = log (Kx/KH) = rs
• He arbitrarily assigned r, the reaction constant, of the acid ionization of
benzoic acid a value of 1.

8. Hammett Plot
• Aryl substituent constants (s) were determined by measuring the effect of a
substituent on a reaction rate (or Keq).
• Reaction constants (r) for other reactions may also be determined by
comparison of the relative rates (or Keq) of two differently substituted
reactants, using the substituent constants described above.
• Some of these values (s and r) are listed on the following slide.

9. Evaluation of the quality of QSAR models
Statistical quality of QSAR models are separate three parts
(1)Measure of goodness-of-fit.
(2)Validation of model stability.
(3) Predictivity analysis, which is itself highly dependent on the
Domain of Applicability.

10. Evaluation of the quality of QSAR models
For validation of QSAR models, usually various strategies are adopted:
• Internal validation or cross-validation (actually, while extracting data, cross
validation is a measure of model robustness, the more a model is robust
(higher q2) the less data extraction perturb the original model);
• External validation by splitting the available data set into training set for
model development and prediction set for model predictivity check;
• Blind external validation by application of model on new external data
• Data randomization or Y-scrambling for verifying the absence of chance
correlation between the response and the modeling descriptors.

11. Application of QSAR
1. Drug design
2. Prediction of Chemical Toxicity
3. Prediction of environmental activity
4. Prediction of Molecular Properties
5. Investigation of retention mechanism

12. Virtual screening can be defined as a set of computational methods that analyzes
large databases or collections of compounds in order to identify potential hit
candidates.
Virtual screening

13. Thank you
Er. Rajan Rolta
Faculty of Applied Sciences and Biotechnology
Shoolini University,
Village Bhajol, Solan (H.P)
+91-7018792621 (Mob No.)
rajanrolta@shooliniuniversity.com