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Looking for molecular targets through a comparative proteomic approach

Looking for molecular targets through a comparative proteomic approach. Marinella Roberti. International Summer School Chemical and Genomics-Based Strategies in the Discovery of Novel Drug Targets Bologna, June 23 -27, 2014. Aims of the Work.

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Looking for molecular targets through a comparative proteomic approach

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  1. Looking for molecular targets through a comparative proteomic approach Marinella Roberti International Summer School Chemical and Genomics-Based Strategies in the Discovery of Novel Drug Targets Bologna, June 23-27, 2014

  2. Aims of the Work Design and synthesis of small libraries of novel biologically active small molecules Drug Discovery Chemical Biology Identification of innovative antileukemia lead candidates Identification of chemical tools to study molecular pathways in leukemia cells

  3. Chronic myeloid leukemia CML is a myeloproliferative disease characterized by increased proliferation of the granulocytic cell line . Typically affects older adults and rarely occurs in children, though it can occur at any age. CML is associated with a characteristic chromosomal translocation between chromosomes 9 and 22, called Philadelphia chromosome which directs the expression of a mutant constitutively active tyrosine kinase called Bcr-Abl that promote cell growth through phosphorylation of signaling proteins. CML is treated with tyrosine kinase inibitors (TKIs) targeting BCR-ABL such as Imatinib mesylate (Gleevec), Dasatinib and Nilotinib. Resistance to these TKIs has emerged therefore warranting the search for alternative targets.

  4. Global Strategy Molecular networks Hits Data analysis Comparative proteomic approach Biological studies Target Design and synthesis of compounds

  5. Design and Synthesis Natural Products as Lead Compounds Wittig reaction Phosphonium salts Aldeydes 40 compounds

  6. Biological studies Evaluation of antiproliferative activity (IC50) and pro-apoptotic activity (AC50) on sensitive acute leukemia HL60 cells. IC50 = 5 ± 0.9 mM AC50 = 50 ± 8.2 mM IC50 = 42 ± 6.4 mM AC50 = >200 IC50 = 0.8 ± 0.1 mM AC50 = 1 ± 0.09 mM IC50 = 0.05 ± 0.008 mM AC50 = 0.1 ± 0.003 mM IC50 = 0.7 ± 0.09 mM AC50 = 0.9 ± 0.1 mM IC50 = 0.03 ± 0.012 mM AC50 = 0.04 ± 0.0045 mM IC50 = 4 ± 0.8 mM AC50 = 8 ± 1.5 mM IC50 = 0.03 ± 0.005 mM AC50 = 0.04 ± 0.0012 mM Roberti, M et al., J. Med. Chem., 2003, 46, 3546-3554 Amorati, R. et al., J. Org. Chem.2004, 69:7101-7107 Tolomeo, M. et al., Int. J. Biochem. Cell Biol.2005, 37:1709-1726 Kaur, G. et al., Tromb. Res.2007, 119, 247-256

  7. Design of stilbene analogues Increasing structural diversity Orto, meta and para-Terphenyls incorporate a phenyl ring as a bioisosteric substitution of the stilbene alkenyl bridge It is demostrated that the terphenyl moiety is a functional and structural mimic of protein a-helix regions, key players in protein-protein associations. As a consequence terphenyls could prevent protein-protein association. Resveratrol 25 compounds R1 = H, Me R2 = H, Me, OH, Ph R3 = H, Me R4 = OH,OMe, CH2OH, (CH2)2OH

  8. Synthesis of Terphenyls Double Suzuki Cross-Coupling + + Boronic acids o-, m-, p-biphenyls Terphenyls Boronic acids o-, m-, p-iodobromobenzenes Reagents and conditions: Pd(Ph3P)4, aqueous Na2CO3, toluene/EtOH 3:1, reflux, 5h(60-95% yield) Reagents and conditions: Na2CO3, Pd(PPh3)4, EtOH/H20 2:1, 150 °C, 50 W, 10 min (70-75% yield)

  9. Biological studies Evaluation of antiproliferative activity (IC50) on both sensitive acute leukemia HL60 cells and Bcr-Abl-expressing K562 cells. Evaluation of pro-apoptotic activity (AC50) of the most active compounds on both HL60 and K562 cells. Evaluation of the effects on the cell cycle progression of the most active compounds on K562 cells. Evaluation of the ability to induce cell differentiation on HL60 cells for the compounds able to induce a stable block in G0-G1.

  10. TR_9 induce a morfological and functional differentiation TR9 Untreated HL60 cells Band neutrophil Phagocytosis of apoptotic bodiesby a macrophage Biological results IC50 (HL60) = 7.0 ± 1.2 mM; AC50 (HL60) = 25 ± 3 mM IC50 (K562) = 20.0 ± 0.2 mM; AC50 (K562) = 75 ± 12 mM TR_9 TR_9 induce a stable block of the cell cycle in G0-G1 phase Control TR9 HIT IDENTIFICATION Pizzirani, D. et al. J.Med.Chem. 2006, 49, 3012-3018

  11. Biologically validated moiety Natural product-like scaffold Novel potentially bioactive compounds or or Spiro ring system, widespread in many natural products Efficently assembled by multi-component domino reaction Hybrid molecules Byiphenyls and terphenyls previously synthesized by us Design strategy of hybrid compounds Pizzirani, D. et al. ChemMedChem 2008,3, 345-355

  12. Methylene-activated compounds aminoacid aldeydes boronic acids or (K-DA-E) Suzuki Coupling spirocyclic ketons enone Bi- and ter-phenyl-substituted spiro triones General synthetic strategy 1. Domino Knoevenagel/Diels-Alder/Epimerization sequence (K-DA-E) for the construction of natural product-like core 2. Suzuki Coupling for the derivatization step

  13. 1,3-indandione Meldrum’s acid 74% 90% Domino Knoevenagel/Diels-Alder / Epimerization sequence (K-DA-E) 4-Bromo benzaldeyde (E)-4-phenyl-3-buten-2-one 4’-Bromobiphenyl-4-carbaldeyde 80% 76% Reagents and conditions: aldehyde (1.0 equiv), 1,3-dione (1.0 equiv), (L)-DMTC (0.2 equiv), enone (2 equiv), MeOH (1M), rt, 72h.

  14. or or R1 = H, OMe R2 = H, CH2OH, OMe, OH, CF3, CHO R3 = H, OMe or Suzuki Coupling or 25 hybrid molecules (90-30% yield) Reagents and conditions: K-DA-E product (1.0 equiv), arylboronic acid (2.0 equiv), Pd(Ph3P)4 (0.5 equiv), aq. Na2CO3 (3.0 equiv), Toluene/EtOH 3:1.

  15. Biological studies Evaluation of antiproliferative activity (IC50) on both sensitive acute leukemia HL60 cells and Bcr-Abl-expressing K562 cells. Evaluation of pro-apoptotic activity (AC50) of the most active compounds on both HL60 and K562 cells. Evaluation of antiproliferative activity (IC50) of the most active compounds on normal cells (lymphocytes). Evaluation of the effects on the cell cycle progression and Bcl-2 expression of the most active compounds on K562 cells. Evaluation of the ability to induce cell differentiation on HL60 cells for the compounds able to induce a stable block in G0-G1.

  16. block of the cell cycle in G0-G1 phase then……… a stable block of the cell cycle in G0-G1 phase G1=63% S=26% G2-M=11% A=2% G1=72% S=20% G2-M=8% A=2% G1=34% S=64% G2-M=2% A=55% G1=44% S=39% G2-M=17% A=4% Apoptosis 24h 72h 24h 72h IND_S1or 32.8% decrease MEL_T1 Untreated HL60 cells Monocytic cells Phagocytosis of apoptotic bodies Bcl-2 expression Biological results 2nd generation hits IC50 = 14  2 AC50 = 80  9 IC50 = 8  1.1 AC50 = > 100 IC50 = 8  0.9 AC50 = 25  3 IC50 = 9  15 AC50 = 33  5 IND_S7 MEL_S3 IND_S1 MEL_T1 Pizzirani, D. et al. J.Med.Chem. 2009, 52, 6936-6940

  17. Comparative proteomic profiling K562 cell culture untreated or treated with each selected compound (30 mmol) Total protein extraction Each protein samples was separated by two dimensional gel electrophoresis 2D-PAGE Spots from each gel were detected, normalize and quantified Image analysis with PDQuest v. 8.0.1 software Protein identification with MALDI-TOF MS Validation by Western Blot Data mining with MetaCore v. 6.6 software RT-qPCR analysis

  18. 2D-Gels 3 pI 10 220 Mr (Kda) 5 Untreated K562 cells K562 cells trated with IND_S1 K562 cells trated with MEL_T1 K562 cells trated with IND_S7 K562 cells trated with MEL_S3 K562 cells trated with TR_9

  19. Differentially expressed protein spots Proteome-level changes in K562 cells induced by treatment with TR_9,IND_S1, MEL_T1, IND_S7 and MEL_S3. The protein spots that showed at least two times enhanced/decreased expression were selected for identification and were examinated by MALDI-TOF mass spectrometry. 36 differentially expressed protein spots were identified: 13 upregulated (red circle) and 23 downregulated (green square)

  20. Protein identification (I)

  21. Protein identification (II)

  22. Multivariate analysis Two-way hierarchical clustering of the 74 differentially expressed protein spots between K562 cells treated with the four synthetic small molecules and control cells. Pearson's dissimilarity as distance measure and Ward's method for linkage analysis were used. Log2 ratios are color coded as indicated. Names of the identified protein spots are shown on the right. The largest number of differentially expressed spots was achieved for K562exposed to IND_S7 and MEL_S3 with approximately the same number of of up- and down- regulated protein spots.

  23. Distribution of differently expressed proteins RNA processing Cytoskeleton 6% 13% Defense 3% Energy metabolism Signal transduction 3% 19% 3% 6% 31% 13% Carbohydrate metabolism 3% Chaperone Transcription Most of the identified proteins are related to cellular metabolism and were located in mitochondria and are down regulated suggesting an overall bienergetic deficit Mitochondrion Cytoplasm 34% 56% 34% Biological function Cytoplasm/Nucleus 19% FUNCTIONAL CLASSIFICATION 10% Cytoplasm/Cell membrane 3% Endoplasmic reticulum Cellular location Inorganic ion metabolism

  24. Hsp70 is one of the ATP-dependent molecular chaperones that assist the folding of newly synthesized polypeptides, the assembly of multi-protein complexes and the transport of proteins across cellular membranes. Hsp70 is abundantly expressed in most cancer cells. It is considered a very good inhibitors of apoptosis, able to block different apoptotic pathways and its cellular contents has been correlated with the cells’ resistance to death stimuli including anticancer therapy. Hsp70 is very abundant in CML characterized by Bcr-Abl expression. This overexpression is associated with the resistance to Imatinib. Hsp70 and apoptosis Guo, G. et al. Blood 2005, 105, 1246-1254; Poclay, M. et al. Leukemia, 2007, 21, 93-101

  25. Hsp70 and apoptosis pHSF-1 STIP1 Hsp70 Bcr-Abl STAT5 Bax AIF apoptosome DISC P-caspase-9 P13/AKT Pim-2 P-Bad Bcl-xL Bad Caspase-9 Bcl-2 Caspase-3 hnRNP L Apoptosis Guo, G. et al. Blood 2005, 105, 1246-1254

  26. Validation of proteomic results Top, Representative immunoblots of each protein and GAPDH, as a loading control. Bottom, Bar graphs showing the densitometric analysis of Western blots. For each treatment series, protein values were normalized to GAPDH and expressed as a ratio relative to control K562 cells.. Dash-dotted line represents transcription levels of genes encoding HSP70, Sti1 and hnRNP L, as determined by qPCR. Western blot analysis to evaluate the expression levels of proteins. RT-qPCR analysis to evaluate the transcriptional levels of proteins.

  27. Network analysis of identified proteins Enzyme Kinase Protein kinase Protein phosphatase Protease Protein Binding protein Receptor Receptor ligand Transcription factor Voltage-gated ion channel Compound Transporter MetaCore software generate an interaction network among the identified proteins and the rest of the protein objects showing physical or functional interactions. The complex network data demonstrated a high number of interactions between differentially expressed proteins and various signaling proteins

  28. Network analysis of identified proteins To investigate the transcriptional factors that we don’t identified by 2-Dimensional gels analysis we apply the transcriptional regulating algoritm. By this analysis we identified several TFs that could be a key regulator proteins involved in the mechanism of action of our hits.

  29. Network analysis of identified proteins Up-regulated Down-regulated Mixed-signal Effects Positive/activation Negative/inhibition Unspecified * * The top scored (by the number of pathways) trancriptional regulating network * * Gene expression data IND_S1 MEL_T1 IND_S7 MEL_S3 Protein Generic binding protein Generic enzyme Generic kinase Generic protease Generic phosphatase Transcription factor Voltage-gated ion channel A complex or a group qPCR determination of mRNA abundance of SP1 in K562 cells trated with the small molecules

  30. Network analysis of identified proteins Up-regulated Down-regulated Mixed-signal Effects Positive/activation Negative/inhibition Unspecified The second scored (by the number of pathways) trancriptional regulating network Gene expression data * qPCR determination of mRNA abundance of c-Myc in K562 cells trated with the small molecules Protein Generic binding protein Generic enzyme Generic kinase Generic protease Generic phosphatase Transcription factor Voltage-gated ion channel A complex or a group * * IND_S1 MEL_T1 IND_S7 MEL_S3

  31. Network analysis of identified proteins Up-regulated Down-regulated Effects Positive/activation Negative/inhibition Unspecified * The third scored (by the number of pathways) trancriptional regulating network * * Gene expression data IND_S1 MEL_T1 IND_S7 MEL_S3 qPCR determination of mRNA abundance of HNF4-alpha in K562 cells trated with the small molecules Protein Generic binding protein Generic enzyme Generic kinase Generic protease Generic phosphatase Transcription factor Voltage-gated ion channel A complex or a group

  32. Network analysis of identified proteins * Up-regulated Down-regulated * * IND_S1 MEL_T1 IND_S7 MEL_S3 Effects Positive/activation Negative/inhibition Unspecified Trancriptional regulating network EGR1 is involved in a megakaryocyte differentiation Gene expression data qPCR determination of mRNA abundance of EGR1 in K562 cells trated with the small molecules Protein Generic binding protein Generic enzyme Generic kinase Generic protease Generic phosphatase Transcription factor Voltage-gated ion channel A complex or a group

  33. K562 cells are capable of multilineage differentiation EGR1 is known to be implicated in megakaryocyte differentiation Differentiation is a possible therapeutic alternative in CML The ability of the four molecules to induce differentiation in K562 cells was investigate Back to cells experiments ……………

  34. * * * IND_S1 MEL_T1 IND_S7 MEL_S3 Differentiation marker analysis Flow cytometry analysis qPCR determination of mRNA abundance of EGR1 in K562 cells trated with the small molecules Expression of glycoprotein IIb/IIIa (CD41) in K562 cells cultured with or without 15 mM of different molecules. Turroni, Silvia; Tolomeo, Manlio; Mamone, Gianfranco; et al. PLOS ONE, 2013, 8, 2, e57650

  35. Differentiation activity Morphological changes observed in K562 cells after 72-h exposure to 15 μM of MEL_S3. (A) Control; (B, C and D) MEL_S3-treated K562 cells with the presence of large cells with megakaryocytic morphological aspects.

  36. * Apoptosis * * IND_S1 MEL_T1 IND_S7 MEL_S3 * G1=34% S=64% G2-M=2% A=55% G1=44% S=39% G2-M=17% A=4% * IC50 = 9  15 AC50 = 33  5 MEL_S3 IND_S1 MEL_T1 IND_S7 MEL_S3 24h 72h (CD41) * 32.8% decrease Megakaryocytedifferentiation Bcl-2 expression MEL_S3 is our Hit??? HNF4-alfa block of the cell cycle in G0-G1 phase then……… EGR1

  37. By a comparative proteomic analysis of K562 cells treated with different probes we identified several proteins that are over- or under-expressed compared to the untreated cells The MetaCore bioinformatic tool revealed some transcriptional factors (not visualized on 2D gels) that might be key regulatory proteins involved in the mechanism of action of the molecules Conclusions (1) Through an integrated chemical biological strategy we obtained some newly-shaped small molecules (probes) able to interfere with cellular functions in Leukemia cells

  38. qPCR validation of central hubs showed that the compounds MEL_S3 induced high mRNA levels of the transcriptional factors HNF4-alpha and EGR1. Consistently with the known EGR1 involvement in the regulation of of differentiation along megakaryocyte lineage, MEL_S3 was able to induce differentiation in K562 cells. Further study are warranted to confirm MEL_S3 contribution to CML menagement as well to define its potential application in other malignancies characterizes by similar pathway alterations. Conclusions (2)

  39. In our study the compound MEL-S3 induced a 40 times increase in Hepatocyte nuclear factor 4-alfa (HNF4-alpha) gene transcription. Considering that enforced expression of HNF4-alpha alleviated hepatic fibrosis and blocked hepatocellular carcinoma (HCC) occurrence, now we are studing the effects of MEL-S3 on HEPG2 and PL5 hepatocellular cancer cells. Perspectives (1)

  40. Considering the key role of HNF4 in normal functioning of endocrine pancreas and insulin secretion, we are performing new studies to understand the potential role of MEL-S3 in diabetes and glucose metabolism pathologies. Perspectives (2) Stay tuned……

  41. Acknowelegments Department of Pharmacy and Biotechnology University of Bologna Patrizia Brigidi Silvia Turroni Maurizio Recanatini Daniela Pizzirani Elisa Giacomini Cristina Ianni Department of Experimental, Diagnostic and Specialty Medicine University of Bologna Giuseppina di Stefano Marina Vettraino Interdepartmental Research Centre on Clinical Oncology (C.I.R.O.C) University of Palermo Manlio Tolomeo Stefania Grimaudo Antonietta Di Cristina Institute of Food Science (ISA) CNR - Avellino Gianfranco Mamone Gianluca Picariello

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