A Quantitative Structure-Activity Relationship Study on Multiple Sclerosis (MS) Drugs

Torkashvand, Rezvan | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43757 (03)
  4. University: Sharif University of Technology
  5. Department: Chemistry
  6. Advisor(s): Jalali-Heravi, Mehdi
  7. Abstract:
  8. In the present work we report a quantitative structure-activity relationship (QSAR) study on S1P1 receptor’s agonists that have therapeutic potential for autoimmune disorders such as Multiple Sclerosis (MS). Such studies play an important role in drug design and lead optimization by developing a mathematical relationship between the chemical structures of compounds and their biological activities.
    We used both linear and nonlinear techniques such as MLR and ANN respectively to model these compounds together with techniques such as Stepwise-MLR, GA-MLR and GA-ANN in the variable selection step as it is an important step in every QSAR study. Since topological descriptors are well interpreted, we focused on these descriptors to make all the models. The algorithms all are based on Monte-Carlo cross validation and generally repeated for 100,000 times. Comparing the results of these techniques, dedicates that the GA-MLR model is the best model that shows the structure-activity relationship of the S1P1 receptor’s agonists and most important variables found are MPC05, VEA1, MPC10 and BAC.
    Superiority of the linear over the nonlinear models revealed that activity of these agonists has linear characteristics and it could be suggested that mechanism of action of S1P1 receptor’s agonists relies on the larger substituent on the molecule
  9. Keywords:
  10. Genetic Algorithm ; MS Disease ; Quantitative Structure-Activity Relationship (QSAR)Model ; Sphingosine-1-Phosphate (S1P)

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