QSAR.pptx quantitative Analysis Of Structure Activity Relationship

M pharm 1st year 2 semester drug discovery pharmacology

1. Quantitative Analysis Of Structure Activity Relationship (QSAR) Submitted to : prof.mandade sir Submitted by: jamdade sonali lala Pharmacology department M pharm 1 st year pharmacology Sudhakar Rao Naik Institute Of Pharmacy pusad .

2. Content I ntroduction History Development of QSAR SAR vs QSAR Physicochemical parameters Hansch analysis Fee wils analysis.

3. What is QSAR ? A QSAR is a mathematical relationship between Biological activity Of a molecular system And its Geometric and chemical characteristics.

4. Physicochemical parameter. 1.lipophilic parameters: partition coefficient, pi substitution constant 2. Electronic parameters: Hammet constant, dipole moment. 3. steric parameters: Tafts constant, molar refractivity , verloop steric parameter.

5. Hansch Analysis . For the past few decade scientist used a random drug discovery process which takes 15-20 years to develop a drug candidate with huge expenditure along with high man power. But now a days drug discovery process is advanced by adopting several scientific and mathematical logic. The rational drug discovery approach adopts various parameters to predict the biological responses with the avilable literature such as physicochemical properties.

6. The disciplin QSAR was initiated by prof. Corwin Hansch in 1962. He Said the foundation of QSAR by three important contribution i.e. 1. combination of several physicochemical parameter in one regression equation. 2. definition of lipophilic parameter. 3 formulation of the parabolic model for non linear lipophilicity - bioactivity relationship. Hansch and Fujita combined different physicochemical parameters in one equation . Log 1/C=k1 log P + k2 sigma +K3 these equation is known as hansch euation . Where ,c- molar concn . K1,k2,k3 – coefficients determined by least squares procedure. For in vivo parabolic lipophilicity values in included in above equation, hence it becomes log 1/c=-k1 (log P)2 +k2 log P + k3 Sigma + k4

7. Application