Coefficient Symbol Equation Limits

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2 1 Coefficient Symbol Equation Limits Squared Correlation Coefficient R 2 or r 2 0 r 2 N 1 2 ( Yexp, i Ycalc, i ) 2 ( Yexp, i Y ) i= 1 2 Cross-Validated R 2 q 2 r 2 or Q 2 or q 2 N 2 ( Yexp, i Ypred, i ) 1 3 Y-scrambling r 2 ys and q 2 ys r q 2 i= 1 = 1 N 1 2 i= 1 = N i= 1 ( Y exp, i Y ) 2 r 2 ys r 2 q 2 ys q 2 4 Prediction Error SDEP SDEP N i= 1 = ( Y Y 2 exp, i pred, i ) N As low as possible Introduction to Ligand-Based Drug Design Chimica Farmaceutica 2

3 Molecular descriptors are numerical values that characterize properties of molecules The descriptors fall into Four classes Topological Geometrical Electronic Hybrid or 3-D Descriptors Fingerprints Introduction to Ligand-Based Drug Design Chimica Farmaceutica 3

4 Dragon 7.0 calculates 5,270 molecular descriptors, organized in different logical blocks as in the previous versions. Blocks are further divided into sub-blocks to make management, selection, and analysis of descriptors easier. Following, the summary of molecular descriptors blocks calculated by Dragon 7.0 is reported. The complete list of all 5,270 calculated descriptor is also available. Block no. Block name # Descriptors Block no. Block name # Descriptors 1 Constitutional RDF descriptors Ring descriptors D-MoRSE descriptors Topological indices WHIM descriptors Walk and path counts GETAWAY descriptors Connectivity indices Randic molecular profiles 41 6 Information indices Functional groups count D matrix-based descriptors Atom-centred fragments D autocorrelations Atom-type E-state indices Burden eigenvalues CATS 2D P-VSA-like descriptors D Atom Pairs ETA indices D Atom Pairs Edge adjacency indices Charge descriptors Geometrical descriptors Molecular properties D matrix-based descriptors Drug-like indices D autocorrelations CATS 3D 300 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 4

5 Description of Molecules with Molecular Interaction Fields (MIF) Introduction to Ligand-Based Drug Design Chimica Farmaceutica 5

6 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 6

7 Reduction of Dimensionality into Few New Highly Informative Entities Principal Components Introduction to Ligand-Based Drug Design Chimica Farmaceutica 7

8 PLS + MIF CoMFA! Introduction to Ligand-Based Drug Design Chimica Farmaceutica 8

9 Physical properties are measured for the molecule as a whole Properties are calculated using computer software No experimental constants or measurements are involved Properties are known as Fields Steric field - defines the size and shape of the molecule Electrostatic field - defines electron rich/poor regions of molecule Hydrophobic properties are relatively unimportant Advantages over classical QSAR No reliance on experimental values (i.e. logp) Can be applied to molecules with unusual substituents Not restricted to molecules of the same structural class Improved predictive capability Introduction to Ligand-Based Drug Design Chimica Farmaceutica 9

10 Training Set Molecular Alignment Molecular Interaction Fields (MIF) Model Generation Internal and External Validation Introduction to Ligand-Based Drug Design Chimica Farmaceutica 10

11 Training Set Molecular lignment Molecular Interaction Fields (MIF) Model Generation Internal and External Validation Introduction to Ligand-Based Drug Design Chimica Farmaceutica 11

12 Training Set Molecular Alignment Molecular Interaction Fields (MIF) Model Generation Internal and External Validation Introduction to Ligand-Based Drug Design Chimica Farmaceutica 12

13 Training Set Molecular Alignment Molecular Interaction Fields (MIF) Model Generation Internal and External Validation Introduction to Ligand-Based Drug Design Chimica Farmaceutica 13

14 Training Set Molecular lignment Molecular Interaction Fields (MIF) Model Generation Internal and External Validation Introduction to Ligand-Based Drug Design Chimica Farmaceutica 14

15 Training Set Molecular Alignment Molecular Interaction Fields (MIF) Model Generation Internal and External Validation SDEP = ( y y ) exp 2 / n 1 pred q 2 ( ) 2 y ( ) exp y pred / yexp = 1 y 2 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 15

16 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 16

17 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 17

18 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 18

The Lattice Model: A General Paradigm for

44. Baroni, M.; Costantino, G.; Cruciani, G.

, Generating Optimal Linear Pls Estimations

19 The Lattice Model: A General Paradigm for Shape-Related Structure/Activity Correlation Cramer, R.D., and Milne, M., Abstracts ACS Meeting, Honolulu, 1979, COMP 44. Baroni, M.; Costantino, G.; Cruciani, G.; Riganelli, D.; Valigi, R.; Clementi, S., Generating Optimal Linear Pls Estimations (Golpe) an Advanced Chemometric Tool for Handling 3D QSAR Problems. Quant Struct Act Rel 1993, 12, (1), Introduction to Ligand-Based Drug Design Chimica Farmaceutica 19

20 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 20

21 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 21

22 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 22

23 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 23

24 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 24

25 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 25

26 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 26

27 CoMFA 3-D QSAutoGrid/R Introduction to Ligand-Based Drug Design Chimica Farmaceutica 27

28 GRS GRS GRS Introduction to Ligand-Based Drug Design Chimica Farmaceutica 28

29 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 29

30 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 30

31 Introduction to Ligand-Based Drug Design Chimica Farmaceutica 31

Description of Molecules with Molecular Interaction Fields (MIF)

Description of Molecules with Molecular Interaction Fields (MIF) Introduction to Ligand-Based Drug Design Chimica Farmaceutica 2 Reduction of Dimensionality into Few New Highly Informative Entities -----