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2. Chemometrices:  Signal processing  Classification & pattern reccognation  Experimental design  Multivariative calibration  Quantitative Structure - Activity Relationship(QSAR) 2

3. Quantitative Structure-Activity Relationship (QSAR) Models Set of molecules Y paramete r Molecular Descriptors (X i )  QSAR Y = f(X i ) Interpretation Prediction 3

4. Step1: Formulation of Classes of Similar Compounds Step 2: Structural Description and Definition of Design Variables Step 3 : Selection of the Training Set of Compounds Step 4: Biological Testing Step 5 : QSAR Development Step6 : Validation and Predictions for Non-Tested Compounds 4

5. 5 Data setTest SetExternalInternalTraining Set Data Set

6.  well-balanced distribution & contain representative compound  systematically & simultaneously 6 Selection of the Training Set of Compounds

7. 7 Drug Design

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9. set of neuropeptides Relative activity against NK1 receptors o 2 9 full FD 512 structures o 2 9-4 fractional design 32 structures 512-32 = 480 9 9 of 11 positions

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11. 11 Set of 32 training structures

12.  Same molecular set  full molecular library F ormal I nference-based R ecursive M odeling (FIRM) methodology  Same key points  not preserve exactly the same ordering or magnitude of Importance Second order interactions 12 QSAR:Same molecular set

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14. 14 Y = 25.094 + 8.031 [Leu] + 8.094 [Phe-2] + 5.781 [Leu] [Phe-2] + 11.593 [Phe-1] + 9.094 [Gln-2] + 7.844 [Phe-1] [Gln-2] + 5.031 [Gln-2] [Gln-1] + 7.031 [Pro-2] [Phe-1] Interaction effect important Experimental Response Variability = 5% Variation ► Least a change of 5% in the molecular activity

15.  Predictive capability of a QSAR model  Strategy used for selecting the compounds in the training set 15 Dipeptides (Inhibiting the Angiotensin Converting Enzyme)

16. FFD  Table 1. The 2 4-1 FFD for z 1, and z 2 for a peptide varied at two positions (I and 2). The design is cornpleinentcd with a centcr point. Dipeptidcs (DP) corresponding approxiniatcly to the settings of the angiotcnsin data are givcn. 16

17. Table 2. The 2 4 FD for z 1, and z 2 at position 1 and 2. Peptide analogs, approximatcly corresponding to thc design matrix, were selected from the set of 48 bitter dipcptidcs. 17 FD

18.  Full Factorial Design(FD)  Fractional Factorial Design (FFD)  change-one-separate-feature-at-a-time (COST) design 18 TrainingTestR2R2 Q2Q2 FD2 4 16420.780.68 FFD2 4-1 + 19490.970.53 COST34 240.640.52