1. Java Solutions for Cheminformatics March 2005

2. About Us Molecule Drawing and Visualization Structure Searching Cartridge Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

3. History Formed: 1998 Budapest, Hungary Skills base: Chemistry, Software development, Predictive tools Aim: Platform independent software for chemistry Highlights 1998: Custom projects 1999: Java tools for sketching/viewing structures 2000: Structure database support 2001: Clustering and diversity analysis 2003: Pharmacophore screening, property predictions, reaction processing, fragmenting 2004: Cartridge technology, virtual synthesis, improved SMARTS support

4. People Developers: 17 (7 Phd, 10 MSc) Technical expertise Cheminformatics Synthetic and physico- chemistry Virtual drug design Java Web technology Business Support: 3 (1 MSc, 2 BSc) Commercial expertise Negotiation & contracting Relationship management Collaboration steering and development Strategic marketing Mutually benefitial (win win) business relationships

5. Selected Application Areas Global licenses Custom development projects Value added constructions Websites/portal front and back end Educational

6. Product development Chemical drawing 19982003 JChem Applets, Molfiles, stereo support, Windows, Unix SMILES, SMARTS, PDB, Rgroups, isotopes, shortcuts, Marvin Beans Ball and stick, JPG, PNG, SVG, Cut&Paste with Isis/ChemDraw, 2D cleaning, (de)aromatizatio n, reactions 2002200020011999 SDF, RDF, XYZ animations, CML, templates, compressed formats, Swing, 3D rendering Mac support, signed applets, Java Web Start, atom mapping Partial charge, pK a, logP, logD, 3D generation, radicals, Sgroups Oracle, MySQL, SQLServer, Access, hashed fingerprints, substructure and similarity searching DB2, PostgreSQL, Rgroup searching reaction searching, reaction processing, pharmacophore analysis. screening, standardization, fragmentation clustering, diversity Marvin 2004 Marvin file format, enhanced stereo, enhanced SMARTS support, shapes, text boxes, multiple groups, TPSA, Donor/Acceptor... cartridge, enhanced stereo searching, recursive SMARTS, chemical expressions, virtual synthesis… Structure Database and Cheminformatics toolkit

7. Current Products Overview

8. Multiple Deployment Formats Applications Java Applets Signed Java Applets Java Web Start Java Beans Plugins JSP

9. Why ChemAxon? Sophisticated virtual chemistry technology Platform independence and Web (Java) High performance tools (speed, capacity) Client oriented development Comprehensive API for the developers Detailed documentation Competitive prices Fast and reliable support

10. Product Support Fast response to support question – max. 24 hour response (fast solution also!) Final and beta releases available online. Detailed documents available online and extensive help bundled within software Skilled and relevant human support quality (direct developer to developer) Product development based on support requests Developers supporting developers

11. Molecule Drawing and Visualization About Us Molecule Drawing and Visualization Structure Searching Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

12. Operating Systems 100% pure java Windows –95, 98, Me, NT, 2000, XP Macintosh –OS 9, OS X Unix –Linux, Solaris, Irix, etc.

13. Web Browsers Internet Explorer Netscape Mozilla Safari Opera

14. Marvin Various file formats Isotopes, charges, radicals Alias, pseudo atoms Templates Abbreviated groups Reactions Atom maps R-groups Stereo bonds, stereo configurations (R/S, E/Z) Enhanced stereo (ABS/AND/OR) SMARTS properties (atoms, bonds, recursive SMARTS) Chemical error checking Generic atoms and bonds Atom lists and not lists 2D cleaning 3D cleaning Various 3D models Shapes, text boxes Plugins

15. Various File Formats

16. Isotopes, Charges, Radicals

17. Templates

18. Abbreviated Groups

19. R-groups

20. Reactions

21. Rendered 3D displays with MarvinSpace

22. Structure Cleaning CC(C)NCC(O)COC1=C2C=C(C)NC2=CC=C1 3D2D topology

23. Structure Searching About Us Molecule Drawing and Visualization Structure Searching Cartridge Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

24. Rapid fingerprint-based database scanning Sophisticated graph-based searching Integration with databases –Oracle –MS SQL Server –DB2 –MYSQL –PostgreSQL –InterBase –Access Custom standardization JChem Cartridge for searching in Oracle JSP integration JChem Base Features

25. Import with JChem Base Manager

26. Exact structure Substructure Atom lists and notlists Explicit hydrogens Generic atoms Generic bonds SMARTS atom properties –Aliphatic, aromatic –Hydrogen count –Connection count –Valence –Ring count –Smallest ring size –Recursive SMARTS Stereo atoms Stereo bonds R-group queries –R-groups –Occurence –if / then conditions –RestH Reaction search –Transformation recognition –Component identification –Stereospecific reactions (inversion, retention) Diastereomers –Enhanced stereo groups (Abs, And, Or) Query Features

27. JChem Base JSP Integration Thin client support: only a web browser and Java required

28. Cartridge Technology About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

29. JChem Cartridge for Oracle Oracle can be extended to support chemical database operations using the JChem Cartridge for Oracle Examples: Substructure search displaying ID, SMILES codes, and molweight: SELECT cd_id, cd_smiles, cd_molweight FROM my_structures WHERE jc_contains(cd_smiles, 'CC(=O)Oc1ccccc1C(O)=O') = 1; Finding benzene derivatives conforming the Lipinskis rule of five: SELECT count(*) FROM my_structures WHERE jc_compare(structure, 'c1ccccc1','sep=!t:s!ctFilter: (mass() <= 500) && (logP() <= 5) && (donorCount() <= 5) && (acceptorCount() <= 10)') = 1; JChem Cartridge for Oracle

30. Example Oracle search returning similar structures with logP >1, which were acquired after April 14th, 2002. MarvinView below.

31. Structure Standardization About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

32. Standardization Explicit hydrogens Aromatic bonds Mesomers Tautomers Counterions

33. Standardization Example afterbefore

34. Molecular Predictions About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

35. Calculator Plugins Available Calculations Elemental analysis Charge distribution Polarizability pK a logP logD Polar surface area Huckel Analysis H-bond donor-acceptor Major microspecies Refractivity Calculation Interface Marvin GUI Command line Chemical Terms API

36. Elemental Analysis

37. Polar Surface Area

38. Partial Charge Distribution

39. Partial Charge Distribution Calculation Partial Equalization of Orbital Electronegativities (PEOE) Orbital electronegativity defined by Mulliken Orbital electronegativity of atom i: i =a t +b t q i +c t q i 2 q i : partial charge Partial charge of atom i is iteratively calculated based on Gasteigers method: i (0) = a t q i (0) = 0 q i (n+1) = q i (n) + ) n ( i - k )/ max( i, k ) k: index of a neighbor of atom i

40. Polarizability

41. logP

42. logP = f i f I : atomic logP increment logP Example

43. Validation of the logP prediction

44. logD

45. logD is computed using micro ionization constants (k i ), micro partition coefficients (p i ), and pH 123 (0) 1 + (1) 2 + (2) 3 - (3) 1 + 2 + (4 ) 1 + 3 - (5) 2 + 3 - (6) 1 + 2 + 3 - (7) k1k1 k2k2 k3k3 k4k4 k5k5 k6k6 k7k7 logD Example

46. pKapKa

47. pKa Plugin - Microconstants Micro ionization constants (logk) are calculated from regression equations that have three types of calculated parameters: Polarizabilities Partial charges Intramolecular interactions logk

48. Macro ionization constants (pK a ) are calculated from the microconstants (logk) pK a Plugin - Macroconstants Ionization scheme 1 - 1 - 2 + 1232 + 1 - 3 - 1 - 2 + 3 - 3 - 2 + 3 - 12 3

49. Hydrogen Bonds in pK a Calculation logk = a q i - q k ) + b a,b: regression parameters Intramolecular hydrogen bonds are also taken into account

50. Validation of the pK a prediction

51. Chemical Expressions About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

52. Chemical Terms searching match("olefine.mol") && !match("c1ccncc1") && (atomCount(16) == 0) || (mass() < 300); goal functions inhibitor = inhibitor.mol; (similarity(inhibitor, pharmacophore_tanimoto) > 0.8) && (similarity(inhibitor, chemical_tanimoto) < 0.5); filtering (mass() <= 500) && (logP() <= 5) && (donorCount() <= 5) && (acceptorCount() <= 10); structure matching functions (describing functional groups, reaction sites, similarity…) property calculations (partial charge distribution, pKa, logP, electrophility…) arithmetic and logic-operators Elements of the language Chemical Terms examples

53. Applications of Chemical Terms CT virtual synthesis reaction and synthesis rules pharmacophore analysis pharmacophore definitions drug design goal functions structure searching advanced query expressions

54. Screening About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

55. Pharmacophore Mapping hydrophobic (h) aromatic (r) acceptor (a) acceptor / donor (a/d) donor / cationic (d/c) donor / aromatic (d/r) atom type colors pharmacophore type colors

56. Topological Pharmacophore Fingerprint hh h h h h h d/+ r/d r r r r r r r r d/a

57. Hypothesis Fingerprints AdvantagesDisadvantages Minimum strict selection of common features very sensitive to one missing feature Average not that sensitive to outliers less selective if actives are similar

58. Dissimilarity Metrics Euclidean standard normalized weighted asymmetric Tanimoto standard scaled asymmetric

59. Screening Optimization 10,000 test compounds (from NCI) 50 active compounds (ß-adrenoreceptor antagonists) 9,700 validation 300 optimization 1/3 training set 1/3 spikes 1/3 query set TRAINING VALIDATION

60. Screening Validation ß2-adrenoreceptor antagonists All compounds:9,700 Known active compounds:18 minimum hypothesis before optimization after optimization all hits2,47618 known active hits1518 enrichment3.27539.89

61. Mixing 18 active compounds with random 9,700 NCI molecules. Sorting by pharmacophore similarity. Active Hit Distribution ß2-adrenoreceptor antagonists

62. Screening Validation 10,000 NCI compoundsbefore optimizationafter optimization familyactivesall hitsactive hitsenrichmentall hitsactive hitsenrichment ACE76,53761.27171647.01 Angiotensin24177340.40663105.50 D25417522.90315269.08 delta7605106.7095495.25 FTP131020117.971310422.30 mGluR17174432.38107571.10 NPY Y5496370381.181454547.12 thrombin3328219.6572109.64

63. Optimized Screening JSP Example

64. Optimized Screening JSP Example Hits

65. Clustering About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

66. JKlustor Jarvis­Patrick Ward

67. Ward's minimum variance method Murtagh's reciprocal nearest neighbor (RNN) algorithm O(n 2 ) time complexity O(n) memory complexity Ward Clustering Features

68. 8 active compound sets –5-HT3-antagonists –ACE inhibitors –angiotensin 2 antagonists –D2 antagonists –delta antagonists –FTP antagonists –mGluR1 antagonists –thrombin inhibitors Ward Pharmacophore Clustering Example

69. Ward Centroids

70. A Ward Cluster D2 antagonists

71. Maximum Common Substructure Clustering

72. Drug Design About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

73. RECAP fragmentation example amide:1 amine:2ether:2 ether:1 amine:1 amide:2

74. Virtual Synthesis About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

75. The Ideal Virtual Reaction Generic (simple) –the equation describes the transformation only –few hundred generic reactions can form the basic armory of a preparative chemist Specific (complex) –chemo-, recognizes reactive and inactive functional groups –regio-, "knows" directing rules –stereo-, inversion/retention Customizable –to improve reaction model quality

76. Processing selective "smart" reactions Batch mode (sequential or combinatorial combinations) Reverse direction High performance (speed and capacity) Customizable Reaction Engine! Reaction Modeling

77. Chemoselective Reaction Definition REACTIVITY:!match(ratom(3), "[#6][N,O,S:1][N,O,S]", 1) && !match(ratom(3), "[N,O,S:1][C,P,S]=[N,O,S]", 1)

78. Reactants 2920 amines, alcohols and thiols 369 isocyanates and isothiocyanates

79. Chemoselective Reaction Products 1,264,391 single site products

80. Regioselectivity (Markovnikov, Zaitsev) An elimination reaction definition with Zaitsevs rule. r2 Addition reaction definition with the Markovnikov rule. r1 SELECTIVITY:hcount(ratom(2)) SELECTIVITY:-hcount(ratom(2))

81. Regioselective Reaction Example Chlorine migration example in four steps by consecutive elimination and addition reactions. r2r1 r2r1r1

82. Regioselectivity (SeAr) Reaction definition of aromatic electrophile bromination of the benzene ring. The expression defines a regioselectivity rule for the major product. SELECTIVITY:-charge(ratom(1)) TOLERANCE:0.0045

83. Regioselectivity (SeAr) Products The virtual bromination of toluene with the above reacton definition results the ortho and para isomer as main product… … and bromine is directed into the meta position in case of nitro-benzene.

84. Regioselectivity (SeAr) Example Products 1,198 monobrominated main products (tolerance is set to zero)

85. Multiple steps Flexible compound dispatching Synthesis rules Synthesis tree building Memory, file and database mode Graphical synthesis browser Building block coloring Customizable Synthesis Engine! Virtual Synthesis

86. Synthesis Example Derek S. Tan, Michael A. Foley, Matthew D. Shair, Stuart L. Schreiber*, J. Am. Chem. Soc., 1998, 120, 8565-8566 lacton aminolysisalkyne coupling esterification

87. Synthesis Definition Component set definition Set1: A Set2:B1, B2, B3 Set3: Set4:D1, D2 Set5: Set6:F1, F2 Set7: "Smart" reaction library R1: alkyl-iodid + alkyne >> alkyl-alkyne R2: lacton + amine >> amide R3: alcohol + carboxylic acid >> ester Synthesis route definition Step1:A + B C R1 Step2: C + D E R2 Step3: E + F G R3

88. Synthesis Browser

89. Current Developments About Us Molecule Drawing and Visualization Structure Searching Cartridge Technology Structure Standardization Molecular Predictions Chemical Expressions Screening Clustering Fragment Analysis Virtual Synthesis Current Developments

90. Recent Developments Automatic searching of low-energy conformers Improved Oracle cartridge Structure searching combined with chemical calculations Exhaustive Synthesis for metabolism applications R-group decomposition Maximum common substructure search in molecule pairs and in libraries

91. Current Developments MarvinSpace, an OpenGL based 3D molecule and surface visualisation engine for small and macromolecules Instant JChem Base, a desktop and enterprise chemical database client with form builder IUPAC naming plugin Isoelectric point plugin Random Synthesis for building up a diverse virtual space of synthetically feasible compounds Extension of the reaction library Further descriptors in the Topology Analysis plugin

92. Future Plans Metabolic transformation library Diverse database of synthetically accessible compounds Search in Markush compounds Peptide builder Fragment-based activity analysis of compound libraries AnalogMaker (fragment based random evolutionary analog design) Retrosynthesis

93. Visit us Home page –www.chemaxon.com Forum –www.chemaxon.com/forum Animated demos and tutorials –www.chemaxon.com/demos Presentations and posters –www.chemaxon.com/conf

94. Máramaros köz 3/a Budapest, 1037 Hungary info@chemaxon.com www.chemaxon.com Thank you for your attention