Screening a Virtual Compound Space

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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 Nóra Máté György Pirok Zsuzsanna Szabó Jenő Varga Miklós Vargyas

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Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker

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Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker

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Virtual Screening Find something similar to a fistful of needles

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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

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0000000100001101000000101010000000000110000010000100001000001000 0100010110010010010110011010011100111101000000110000000110001000 0100010100011101010000110000101000010011000010100000000100100000 0001101110011101111110100000100010000110110110000000100110100000 0100010100110100010000000010000000010010000000100100001000101000 0100011100011101000100001011101100110110010010001101001100001000 0101110100110101010111111000010000011111100010000100001000101000 0100010100111101010000100010000000010010000010100100001000101000 0001000100010100010100100000000000001010000010000100000100000000 0100010100010011000000000000000000010100000010000000000000000000 0100010100010100000000000000101000010010000000000100000000000000 0101010101111100111110100000000000011010100011100100001100101000 0100010100011000010000011000000000010001000000110000000001100000 0000000100000000010000100000000000001010100000000100000100100000 0100010100010100000000100000000000010000000000000100001000011000 0001000100001100010010100000010100101011100010000100001000101000 0100011100010100010000100001001110010010000010001100000000101000 0101010100010100010100100000000000010010000010010100100100010000 queries targets hypothesis fingerprint metric target fingerprints Virtual screening using fingerprints Multiple query structures 0100010100011101010000110000101000010011000010100000000100100000 0001101110011101111110100000100010000110110110000000100110100000 0100010100110100010000000010000000010010000000100100001000101000 0101110100110101010111111000010000011111100010000100001000101000 0001000100010100010100100000000000001010000010000100000100000000 0100010100010100000000000000101000010010000000000100000000000000 0101010101111100111110100000000000011010100011100100001100101000 0100010100011000010000011000000000010001000000110000000001100000 0000000100000000010000100000000000001010100000000100000100100000 0101110100110101010111111000010000011111100010000100001000101000

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Optimized virtual screening asymmetry factor scaling factor Parameterized metrics

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How good is optimized virtual screening? β2-adrenoceptor antagonist

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Is virtual screening a discovery tool? Scaffold hopping

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Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker

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JChem AnalogMaker Workflow Lead Candidates

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Fragmentation Examples Fragmentation rules Amide Original molecule Generated fragments Ester

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Fragmentation RECAP rules 1 = amide 2 =ester 3 = amine 4 = urea 5 = ether 6 = olefin 7 = quaternary nirogen 8 = aromatic N carbon 9 = lactam N carbon 10 = aromatic carbon – aromatic carbon 11 = 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

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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 JChem AnalogMaker General algorithm

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Variant generation Example: TOPAS modifier G. Schneider et al, J. Comput.-Aided Mol. Design, 14(2000): 487-494 G. Schneider et al, Angew. Chem. Int. Ed., 39(2000): 4130-4133

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Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker

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Drug research Finding or making a needle in the hay stack? virtual screening JChem Screen de novo design JChem AnalogMaker ? ?

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de novo design JChem AnalogMaker virtual screening JChem Screen Drug research Screening a virtual compound space random virtual synthesis JChem Synthesizer

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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

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

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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)

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

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

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

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Smart reaction library Baeyer-Villiger ketone oxidation Generic reaction

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Smart reaction library Example Baeyer-Villiger ketone oxidation

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JChem Synthesizer Workflow Smart reaction library Virtual compound space Available chemicals

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JChem Synthesizer example Dopamine D2 actives

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

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JChem Synthesizer example Best virtual hits 9.88 9.82 9.53 9.73

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JChem Synthesizer example Synthesis path step 1 Knoevenagel-Doebner condensation

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step 2 Baylis-Hillman vinyl alkylation JChem Synthesizer example

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step 3 Lawesson thiacarbonylation JChem Synthesizer example

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step 4 Dess-Martin alcohol oxidization JChem Synthesizer example

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Software and performance data virtual reactions: 500-1000 reactions/s random synthesis: 10-20 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 1.4.2 database server: P4 2.4GHz, Windows XP, MySQL JChem Synthesizer example

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Acknowledgements François Petitet Alex Allardyce ChemAxon

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Contact Miklós Vargyas mvargyas@chemaxon.hu office: +36 1 453 2661 mobile: +36 70 381 3205