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Screening a Virtual Compound Space ChemAxon Ltd. Máramaros köz 3/a 1037 Budapest Hungary www.chemaxon.com Szabolcs Csepregi Ferenc Csizmadia Szilárd Dóránt.

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Presentation on theme: "Screening a Virtual Compound Space ChemAxon Ltd. Máramaros köz 3/a 1037 Budapest Hungary www.chemaxon.com Szabolcs Csepregi Ferenc Csizmadia Szilárd Dóránt."— Presentation transcript:

1 Screening a Virtual Compound Space ChemAxon Ltd. Máramaros köz 3/a 1037 Budapest Hungary Szabolcs Csepregi Ferenc Csizmadia Szilárd Dóránt Nóra Máté György Pirok Zsuzsanna Szabó Jenő Varga Miklós Vargyas

2 Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen advantages disadvantages fast hits are readily available for in vitro screening limited number of available compounds advantages disadvantages practically unlimited virtual compound space structural novelty synthetic accessibility of virtual hits is a problem de novo design JChem AnalogMaker

3 Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen advantages disadvantages fast hits are readily available for in vitro screening limited number of available compounds advantages disadvantages practically unlimited virtual compound space structural novelty synthetic accessibility of virtual hits is a problem de novo design JChem AnalogMaker

4 Virtual Screening Find something similar to a fistful of needles corporate database known actives structures found

5 Molecular similarity How to tackle it? Sequences/vectors of bits, or numeric values that can be compared by distance functions, similarity metrics. Quantitative assessment of similarity/dissimilarity of structures need a numerically tractable form molecular descriptors, fingerprints, structural keys

6 queries targets hypothesis fingerprint metric target fingerprints Virtual screening using fingerprints Multiple query structures hits

7 Optimized virtual screening asymmetry factor scaling factor asymmetry factor weights Parameterized metrics

8 How good is optimized virtual screening? β2-adrenoceptor antagonist

9 Is virtual screening a discovery tool? Scaffold hopping

10 Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen advantages disadvantages fast hits are readily available for in vitro screening limited number of available compounds advantages disadvantages practically unlimited virtual compound space structural novelty synthetic accessibility of virtual hits is a problem de novo design JChem AnalogMaker

11 Workflow Lead Candidates

12 Fragmentation Examples Fragmentation rules Amide Original moleculeGenerated fragments Fragment 1 amide 2 Fragment 2 amide 1 ester 1 Ester Fragment 3 ester 2

13 Fragmentation RECAP rules 1 = amide2 =ester3 = amine4 = urea 5 = ether6 = olefin7 = quaternary nirogen8 = aromatic N carbon 9 = lactam N carbon10 = aromatic carbon – aromatic carbon11 = sulphonamide Xiao Qing Lewell, Duncan B. Judd, Stephen P. Watson, Michael M. Hann; RECAP – retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J. Chem. Inf. Comput. Sci. 1998, 38, 511–522

14 create building block library generate pharmacophore hypothesis of active compounds create several starting compounds by random combination of some building blocks select parent structure generate variants of parent start stop convergence or end of optimization JChem AnalogMaker General algorithm

15 Variant generation Example: TOPAS modifier G. Schneider et al, J. Comput.-Aided Mol. Design, 14(2000): G. Schneider et al, Angew. Chem. Int. Ed., 39(2000):

16 Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker advantages disadvantages fast hits are readily available for in vitro screening limited number of available compounds advantages disadvantages practically unlimited virtual compound space structural novelty synthetic accessibility of virtual hits is a problem

17 Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker advantages disadvantages fast hits are readily available for in vitro screening limited number of available compounds advantages disadvantages practically unlimited virtual compound space structural novelty synthetic accessibility of virtual hits is a problem ????

18 advantages disadvantages practically unlimited virtual compound space structural novelty synthetic accessibility of virtual hits is a problem de novo design JChem AnalogMaker virtual screening JChem Screen advantages disadvantages fast hits are readily available for in vitro screening limited number of available compounds Drug research Screening a virtual compound space advantages disadvantages fast virtual molecules are likely to be synthetically available practically infinite virtual compound space structural novelty random virtual synthesis JChem Synthesizer

19 Screening a virtual compound space Smart reactions 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

20 Smart reactions Chemoselectivity REACTIVITY:!match(ratom(3), "[#6][N,O,S:1][N,O,S]", 1)

21 Smart reactions Chemoselectivity 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)

22 Smart reactions Regioselectivity SELECTIVITY:-charge(ratom(1)) TOLERANCE:0.0045

23 Smart reactions Regioselectivity SELECTIVITY:-charge(ratom(1)) TOLERANCE:0.0045

24 Smart reaction library Example Baeyer-Villiger ketone oxidation SELECTIVITY: charge(ratom(2), "sigma")

25 Smart reaction library Baeyer-Villiger ketone oxidation Generic reaction

26 Smart reaction library Example Baeyer-Villiger ketone oxidation

27 JChem Synthesizer Workflow Smart reaction library Synthesizer Virtual compound space Available chemicals Screen Hits Active set 1 Screen Hits Active set n

28 JChem Synthesizer example Dopamine D2 actives Active sets were kindly provided by Aureus Pharma within a research collaboration between Aureus and ChemAxon.

29 Virtual hits similarity: 2D pharmacophore fingerprint, weighted Euclidean metric optimized for 20 random d2 actives JChem Synthesizer example

30 Best virtual hits

31 JChem Synthesizer example Synthesis path step 1 Knoevenagel-Doebner condensation

32 step 2 Baylis-Hillman vinyl alkylation JChem Synthesizer example

33 step 3 Lawesson thiacarbonylation JChem Synthesizer example

34 step 4 Dess-Martin alcohol oxidization JChem Synthesizer example

35 Software and performance data virtual reactions: reactions/s random synthesis: structures/s pharmacophore fingerprint generation: 100 structure/s (includes pharmacophore point perception) metric optimization: 57 sec (13 parameterized metrics, 20 structures in training set, 50 spikes) virtual screening: 7500 structure/s pure Java client: P4 1.6GHz, RH Linux, java database server: P4 2.4GHz, Windows XP, MySQL JChem Synthesizer example

36 Acknowledgements Modest von Korff, Matthias Steger (Axovan is now part of Actelion.) François Petitet Alex Allardyce ChemAxon Jean-Michael Drancourt

37 Contact Miklós Vargyas office: mobile:


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