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Target Prediction for an Open Access Set of Compounds Active against Mycobacterium tuberculosis Francisco Martnez-Jimnez XII Jornadas de Bioinformtica , Sevilla Thursday, September 25, 14 One third of the worlds population is infected

  1. Target Prediction for an Open Access Set of Compounds Active against Mycobacterium tuberculosis Francisco Martínez-Jiménez XII Jornadas de Bioinformática , Sevilla Thursday, September 25, 14

  2. One third of the world’s population is infected with Mycobacterium tuberculosis, the causative agent of tuberculosis. WHOTuber2012. Global Tuberculosis Report 2012. Thursday, September 25, 14

  3. Tuberculosis incidence... Estimated new TB cases (all forms) per 100 000 population 0–24 25–49 50–149 150–299 ≥ 300 No estimate Not applicable Thursday, September 25, 14

  4. MultiDrugResistant-TB Percentage notified of estimated MDR-TB cases 0–9.9 10–19.9 20–49.9 50–79.9 ≥ 80 ≤ 1 MDR-TB case estimated No data Not applicable Thursday, September 25, 14

  5. Phenotypic screening against Mycobacterium tuberculosis Ballell, L.et al (2013). Fueling open-source drug discovery: 177 small-molecule leads against tuberculosis. ChemMedChem . Thursday, September 25, 14

  6. 776 compounds chemical features Thursday, September 25, 14

  7. Phenotypic screenings � � �� �������������������� �� ���������������������� �� ��������� �� �� �� �������������� �������������� �� �� �� �� �� �� �� � �� � � ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� ���� Figure 3 | Cumulative distribution of new drugs by discovery Swinney, D.C. & Anthony, J. How were new medicines discovered? Nat. Rev. Drug Discov ��������������� � ��������������� Thursday, September 25, 14

  8. Finding out the mode of action... Phenotype Thursday, September 25, 14

  9. Finding out the mode of action... Phenotype Thursday, September 25, 14

  10. Methods 2D-Chemogenomics Historical Approach 3D-Structural Approach Approach George Papadatos Vinod Kumar Francisco Martínez-Jiménez John P . Overington James Brown Marc A. Martí-Renom Thursday, September 25, 14

  11. Similar binding-sites tend to bind similar ligands Activin receptor type-1 co-crystallized A3F Similar binding-sites AQ4 co-crystallized Epidermal growth factor receptor Thursday, September 25, 14

  12. Similar binding-sites tend to bind similar ligands Activin receptor type-1 co-crystallized A3F Similar binding-sites AQ4 co-crystallized Epidermal growth factor receptor Thursday, September 25, 14

  13. Similar binding-sites tend to bind similar ligands Activin receptor type-1 Similar ligands co-crystallized VGM A3F Similar binding-sites AQ4 co-crystallized Epidermal growth factor receptor Thursday, September 25, 14

  14. Similar binding-sites tend to bind similar ligands Activin receptor type-1 Similar ligands co-crystallized VGM A3F Similar binding-sites AQ4 co-crystallized Epidermal growth factor receptor Thursday, September 25, 14

  15. Network-based Method nAnnolyze Thursday, September 25, 14

  16. Applying the method, modeling genomes... 2. Binding-site inheritance 1. Modeling 3D model Mycobacterium smegmatis Mycobacterium tuberculosis Mycobacterium bovis Ursula Pieper PDB templates Andrej Sali Bacterial proteomes 3D reliable models 5,008 no overlapping Different Proteins 5,008 different proteins Inherited binding-sites 30,000 Thursday, September 25, 14

  17. Looking for targets... t1 t2 GSK . Drug . . tN Thursday, September 25, 14

  18. Looking for targets... t1 t2 GSK . Drug . . tN Thursday, September 25, 14

  19. Looking for targets... t1 t2 GSK . Drug . . tN Thursday, September 25, 14

  20. Looking for targets... t1 t2 GSK . Drug . . tN Ligand Target Distance Global Z-score Local Z-score GSK1 pknB Kinase 1.3 -1.6 -2.5 GSK1 mapB 2.5 2.3 1.02 GSK1 sahH 1.9 -1.6 -3.16 GSK1 Mmpl3 2.6 2.42 2.97 Thursday, September 25, 14

  21. Statistical assessment of predicted links between compounds and targets • We merged all the predictions from the 3 methods. • Significance of links using groups of similar compounds and the targets KEGG pathways . • LogOdds. Odds of an observation given its probability. • p-value using Fisher´s exact test for 2x2 contingency table comparing two groups of annotations. Thursday, September 25, 14

  22. Compound dataset diversity Thursday, September 25, 14

  23. Compound dataset diversity Thursday, September 25, 14

  24. Targeting essential aminoacids metabolism pathways LogOdds Probability .0 .01 .02 .03 .04 .05 .06 .07 -1.5 0 1.5 mtu00400 mtu00410 mtu03410 mtu00550 mtu03420 mtu00290 mtu00300 mtu00250 HIST CHEM mtu00623 1 mtu00860 2 10 mtu00450 mtu00660 11 mtu00562 2 24 mtu00740 mtu01053 34 mtu00780 mtu00521 Streptomycin biosynthesis Folate biosynthesis mtu00790 STR Nitrogen metabolism mtu00910 mtu00970 Aminoacyl-tRNA biosynthesis Purine metabolism mtu00230 mtu00311 Penicillin and cephalosporin biosynthesis D-Arginine and D-ornithine metabolis mtu00472 One carbon pool by folate mtu00670 Thursday, September 25, 14

  25. Significant drug-protein pairs MoA Prediction against TB Table 2. Significant links between GSK compound families and KEGG pathways. Table 2. Cont. GSK Family Compound Target Pathways GSK Family Compound Target Pathways 1 GSK975784A Glycerolipid metabolism (mtu00561) GSK1829729A Rv3855 No Pathway Rv2182c Rv0053 Ribosome (mtu03010) Glycerophospholipid metabolism (mtu00564) Rv0379 No Pathway Rv2483c No Pathway Rv0650 Glycolysis/Gluconeogenesis (mtu00010) GSK975810A Glycerolipid metabolism (mtu00561) Rv2182c Galactose metabolism (mtu00052) Glycerophospholipid metabolism (mtu00564) Starch and sucrose metabolism (mtu00500) Rv2483c No Pathway Amino sugar & nucl. sugar metab. (mtu00520) Streptomycin biosynthesis (mtu00521) GSK975839A Rv2182c Glycerolipid metabolism (mtu00561) Glycerophospholipid metabolism (mtu00564) GSK1829816A Rv0053 Ribosome (mtu03010) Rv2483c No Pathway Rv0379 No Pathway Rv2299c No Pathway Rv0650 Glycolysis/Gluconeogenesis (mtu00010) Galactose metabolism (mtu00052) GSK975840A Glycerolipid metabolism (mtu00561) Rv2182c Starch and sucrose metabolism (mtu00500) Glycerophospholipid metabolism (mtu00564) Amino sugar & nucl. sugar metab. (mtu00520) Rv2483c No Pathway Streptomycin biosynthesis (mtu00521) GSK975842A Glycerolipid metabolism (mtu00561) Rv2182c GSK479031A Rv0053 Ribosome (mtu03010) Glycerophospholipid metabolism (mtu00564) Rv0379 NoPathway (mtu00000) Rv2483c No Pathway Rv0650 Glycolysis/Gluconeogenesis (mtu00010) Rv2045c No Pathway Galactose metabolism (mtu00052) Rv2139 Pyrimidine metabolism (mtu00240) Starch and sucrose metabolism (mtu00500) Rv2299c No Pathway Amino sugar & nucl. sugar metab. (mtu00520) Rv2483c No Pathway Streptomycin biosynthesis (mtu00521) 3 GSK957094A Rv3170 Gly, Ser and Thr metabolism (mtu00260) GSK547481A Rv0194 ABC transporters (mtu02010) Arginine and proline metabolism (mtu00330) GSK547490A Rv0194 ABC transporters (mtu02010) Histidine metabolism (mtu00340) Tyrosine metabolism (mtu00350) GSK547491A Rv0194 ABC transporters (mtu02010) Phenylalanine metabolism (mtu00360) GSK547499A Rv0194 ABC transporters (mtu02010) Tryptophan metabolism (mtu00380) Rv0053 Ribosome (mtu03010) GSK547500A Rv0194 ABC transporters (mtu02010) Rv0379 No Pathway GSK547511A Rv0194 ABC transporters (mtu02010) Rv0650 Glycolysis/Gluconeogenesis (mtu00010) Galactose metabolism (mtu00052) GSK547512A Rv0194 ABC transporters (mtu02010) Starch and sucrose metabolism (mtu00500) GSK547527A Rv1640c Aminoacyl-tRNA biosynthesis (mtu00970) Amino sugar & nucl. sugar metab. (mtu00520) Rv3598c Aminoacyl-tRNA biosynthesis (mtu00970) Streptomycin biosynthesis (mtu00521) Rv0194 ABC transporters (mtu02010) 9 GSK1188379A Rv0194 ABC transporters (mtu02010) GSK547528A Rv1640c Aminoacyl-tRNA biosynthesis (mtu00970) GSK1188380A Rv0194 ABC transporters (mtu02010) Rv3598c Aminoacyl-tRNA biosynthesis (mtu00970) 16 GSK1825940A Rv0194 ABC transporters (mtu02010) Rv0194 ABC transporters (mtu02010) GSK1825944A Rv0194 ABC transporters (mtu02010) GSK547543A Rv0194 ABC transporters (mtu02010) 35 BRL-10143SA Rv1649 Aminoacyl-tRNA biosynthesis (mtu00970) 7 GSK1829727A Rv0053 Ribosome (mtu03010) Rv2763c One carbon pool by folate (mtu00670) Rv0379 No Pathway Folate biosynthesis (mtu00790) Rv0650 Glycolysis/Gluconeogenesis (mtu00010) One carbon pool by folate (mtu00670) Galactose metabolism (mtu00052) Rv2764c Pyrimidine metabolism (mtu00240) Starch and sucrose metabolism (mtu00500) Amino sugar & nucl. sugar metab. (mtu00520) BRL-51093AM Rv2763c One carbon pool by folate (mtu00670) Rv2764c Folate biosynthesis (mtu00790) Streptomycin biosynthesis (mtu00521) One carbon pool by folate (mtu00670) Thursday, September 25, 14

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