HIV Remission: Compound screening and optimization Michael D. Miller
Can we drive HIV into remission in large numbers of patients? "George Bernard Shaw, speaking as an Irishman, summed up an approach to life, 'Other people, he said, see things and say why? But I dream things that never were and I say, why not?" John F. Kennedy Only those who dare to fail greatly can ever achieve greatly. Robert F. Kennedy 2
Latent HIV infection: A major hurdle to HIV remission The presence and persistence of latent HIV-1 reservoirs ensures viral rebound upon cessation of ART R. Siliciano
HIV latent reservoir may be seeded during infection of activated CD4 + T-cells Resting T-cell HIV Antigen Active T-cell Antigen Resting HIV infected Memory T-cell (Latent Reservoir)
Flush and kill strategy Thanks to Brad Jones for 5 inspiring this image http://www.gundogmag.co m/2012/03/20/controllingyour-dog-birds-galoreequals-sensory-overload/
Flush and Kill Strategy for HIV Remission DA FLUSH Kill Antiretroviral therapy HIV genome Memory CD4 + T cell HIV RA HIV proteins HIV particles Dying infected cell Uninfected cell Thanks to Sharon Lewin for this figure
Developing a new medicine takes an average of 10 15 years The Congressional Budget Office reports that relatively few drugs survive the clinical trial process Drug Discovery Preclinical Clinical Trials FDA Review Scale-Up to Mfg. Post-Marketing Surveillance ~ 5,000 10,000 250 5 COMPOUDS OE FDA- APPROVED DRUG PRE-DISCOVERY 3 6 YEARS ID SUBMITTED PHASE 1 UMBER OF VOLUTEERS 6 7 YEARS PHASE 2 PHASE 3 20 100 100 500 1,000 5,000 DA SUBMITTED 0.5 2 YEARS IDEFIITE Sources: Drug Discovery and Development: Understanding the R&D Process, www.innovation.org; CBO, Research and Development in the Pharmaceutical Industry, 2006. 7
Clinical Proof of Concept for Latent HIV Activator Archin et al., ature (2012) 487,482 485 HIV mra Expression Stimulated in latent T-cells following oral administration of SAHA in vivo
Searching for new latent HIV transcription activators Compounds with several mechanisms of action stimulate transcription of latent HIV genes, including: Overt T cell activators (e.g., PHA,anti-CD3 + anti- CD28) PKC agonists (e.g., prostratin, bryostatin) HDAC inhibitors (e.g., vorinostat, panobinostat, romidepsin) Might compounds with different MOAs be useful, alone or in combination with compounds of known MOA? 9
2C4 cells: A luciferase-expressing Jurkat HIV latency model (constructed by Jon Karn laboratory) LTR phr -TATH13L -LUC-IRES-ef, TAT H13L Rev Δgag-pol Env Tat Tat Rev LUC IRES ef LTR RLU 20000 15000 10000 SAHA TSA Prostratin HMBA 5000 0-10 -9-8 -7-6 -5 log [compound] Assay Conditions: 2,000 cells/well (3ul), 0.25% DMSO, 24 hour incubation at 37C and 98% Rh. Luminescent exposure time of 120 seconds.
HIV Latency SAHA Synergy uht Screen Objective: To Identify Compounds that potentially synergize with HDACi s 2,900,000 Compounds HIV LTR Induction With 250 nm SAHA Initial Screen, n=3 HIV LTR Induction With 250 nm SAHA Confirmatory assays, n=3 Dose response assays, n=2 HIV LTR Induction With 250 nm SAHA HIV LTR Induction Without SAHA Toxicity @ 48 hours CTG FκB BLA reporter counter screen Data analysis/ Hit Selection ~4,500 Compounds Follow-up Analysis
HIV Latency Hits from uhts Compounds with unknown mechanism HDAC Inhibitors Farnesyl Transferase Inhibitors 17.4% 16.1% 66.5%
HDACi s: A Target Based Approach to HIV Latency Drug Development Effects on latent HIV gene expression validated in vitro and in HIV infected patients w/broad spectrum agents (vorinostat) Can we improve upon on these agents by understanding: Medicinal Chemistry Biology An Ideal HDACi for HIV Eradication? VOR (SAHA) ext Gen HDACi s Oral + ++ Potent +/- ++ HDAC spectrum +/- ++ Tolerable +/-???? on-toxic - (Ames?) ++ Appropriate PK-PD???? ++ o DDIs ++ ++
What is farnesyl transferase and why would you want to inhibit it? FT is a heterodimer of α and β subunits FT transfers a farnesyl group to proteins with a C-terminal CaaX motif Farnesylation promotes membrane association, often required for small signalling proteins (e.g., ras) The human genome encodes ~115 proteins with CaaX boxes Figure from: Bell, I. J. Med. Chem. 2004, 47, 1869-187814
FTi s with Differential Binding Modes and Structures A B MRK-16 MRK-17 From: Bell, I. J. Med. Chem. 2004, 47, 1869-1878. X-ray Crystallographic images of different farnesyl-transferase inhibitor binding modalities. (A) Zinc Binding, (B) Exit Groove Blocker
Structures of Representative FTi s Identified from Phenotypic uhts Screen Cl O Br Br Cl O H 2 H 3 C O O CH 3 C J. Med. Chem. 2004, 47, 1869. O Lonafarnib Bioorg. Med. Chem. Lett. 2001, 11, 1257. H 3 C O H Bioorg. Med. Chem. Lett. 2001, 11, 865. H O O C J. Med. Chem. 2004, 47, 1869. HS H 2 CH 3 O J. Med. Chem.1996, 39, 1345. O 16 Diverse array of FTi with different binding modes identified
Positive Correlation Between Farnesyl Transferase Inhibition and HIV Latency Activation Farnesyl-Transferase Enzymatic Assay IC 50 (µm) Jurkat T-cell Induction (EC50, µm) Correlation between FTi potency (IC 50 enzyme assay) and HIV latency activation (EC 50 in Jurkat 17 T-cell model system)
Knock-down of FTβ subunit sensitizes & constitutively reactivates the latent provirus in 2d10 Jurkat cells Latently infected Jurkat T-cell: 2d10 Un-stimulated (+) 100pg/ml TFα (+) 250nM SAHA 3% 14% 10% 2d10_shFTα knock-down 3d post-infection 18% 10d post-infection 4% 3d post-infection (+) 100pg/ml TFα (+) 250nM SAHA 9% 7% Maximum (%) 2d10_shFTβ knock-down 24% 88% 53% 53% d2egfp (Data obtained from Dr. Biswajit Das & Dr. Jonathan Karn, Case Western Reserve Univ. School of Medicine)
FTI s Synergize with HDACi s in a Jurkat HIV Latency Model system (2C4 cells) 3.0 10 06 2.0 10 06 RLU 1000000 Drug Concentration (µm) [MRK-17] nm o SAHA +250nM SAHA 0 0.001 0.01 0.1 1 10 [SAHA] µm SAHA alone SAHA + 0.02µM MRK-17 SAHA + 2µM MRK-12 SAHA + 2µM MRK-16 19
Summary of FTi Compounds CARE ame 2C4 EC 50 (µm) o SAHA 2C4 Emax (vs SAHA) 2C4 EC 50 (µm) + 250nM SAHA 2C4 Emax (vs SAHA) Cytotoxicity CC 50 MRK-12 0.5 ~20% 0.5 60% >40µM MRK-13 0.75 ~20% 0.75 ~80% 20µM MRK-14 >40 <10% 1-2 40-50% 17µM MRK-15 0.2 15% 0.2 ~60% 20µM MRK-16 0.2 15% 0.2 65% >40µM MRK-17 0.04 15% 0.04 70% >40µM MRK-18 8 10% 8 60% >10µM MRK-19 0.3 15% 0.3 50% 2µM MRK-20 1 10% 1 60% 8.5µM MRK-21 1 10% 1 30% 4µM MRK-22 2 20% 2-3 50% >40µM 11 FTi compounds were shared with the CARE collaboratory. These compounds were structurally /chemically validated and their synergistic activity with SAHA (EC 20 10 ) was re-confirmed in 10-point titrations. Cytotoxicity (Cell Titer Glow) of the compounds alone is shown. EC 50 and Emax values +/- SAHA were calculated from experiments using the 2C4 Jurkat HIV latency model system
Synergy of FTIs with other HIV Latency Activating Compounds (Jurkat 2C4 Line) Percent Activation (ormalized to 1 µm SAHA) Log [FTI] (M) MRK 23 (HDACi) Prostratin TFα o Enhancer Jurkat T-cells were incubated for 24 hours with the indicated concentrations of compound in the absence (pink lines) or presence of an EC 20 concentration of TFα (0.2ng/ml), prostratin (700nM) or MRK-23 (HDACi) (220nM)
FTI s and HDACi are additive in a Primary T-cell HIV latency model (T H 17 Jon Karn) o Stimulation 500nM SAHA 10µM FTi 10µM FTi + 500nM SAHA egfp Active PTEF-b B530-A R780-A 96.39% 3.61% 74.00% 26.00% 58.75% 41.25% 23.54% 76.46% 2.62% Stimulated 22.20% Stimulated 35.86% Stimulated 67.32% Stimulated 3.6% 25% 41.3% 76.5% 92.99% Unstimulated 0.00% 0.00% R670-A EF 0.72% 0.90% 95.25% Unstimulated R2: 96.39% 0.54% Stimulated R6: 0.72% 95.87% 2.51% B530-A R780-A 71.88% Unstimulated 0.34% 4.68% 88.49% Unstimulated R2: 74.00% 0.00% 0.00% R670-A EF 5.46% Stimulated R6: 0.34% 89.75% 5.24% B530-A R780-A 57.24% Unstimulated R2: 58.75% 0.00% 0.00% R670-A EF 0.90% 45.52% 50.37% Unstimulated 47.21% Stimulated R6: 0.90% 50.90% 2.69% B530-A R780-A 22.37% Unstimulated 1.00% 49.44% 46.14% Unstimulated R2: 23.54% 0.00% 0.00% R670-A EF 0.9% 4.7% 45.5% 49.4% 51.62% Stimulated R6: 1.00% 46.70% 2.86% YG610-A Cyclin D3 YG610-A Cyclin D3 YG610-A Cyclin D3 YG610-A Cyclin D3 SAHA opens chromatin to allow access to transcription factors FTI mobilizes P-TEFb and triggers cyclin D3 synthesis - begins to drive cells out of G 0
HIV production by the resting CD4 T-cells of Patient 00425 after ex-vivo treatment with SAHA and MRK17 DMSO Ctrl. SAHA Merck 17 250 nm 40 nm (minimal) SAHA & Merck 17 Data from ancie Archin and David Margolis, UC and CARE
Will any uhts latency hits synergize with compounds of known MOA? ~2000 HIV Latency uhts hits (non-hdaci) Complete Dose Response, +/- EC 20 of SAHA, HDACi (1,2,3), TFα, JQ1, HMBA, Prostratin Jurkat HIV Latency T- cell Model (Luc reporter) =3 Cytotoxicity of Compounds +/- EC 20 of known HIV Activators =3 Complete Dose Response of uhts hits +/- EC 20 of known HIV Activators Re-test of compounds with decreased EC 50 and/or increased Emax in the presence of known HIV activators
Summary of Synergy Results with uhts Hits EC 50 Synergy E max Synergy EC 50 and E max Synergy HMBA 0 0 0 JQ1 12% 72% 7% PKC 15% 81% 11% HDACi (1,2,3) 14% 78% 10% TFa 13% 80% 9% 25
Examples of uhts Hit Synergy Profiles Percent Activation (ormalized) to SAHA) o PKC Synergy Multiple Synergies Multiple Synergies PKC EC 50 Synergy SAHA Prostratin TFα o Enhancer Log Compound (M) 26
Reactivation of latent HIV LTR Step 1 Relaxation of Chromatin HDACi HMTi HIV TSS nuc-0 nuc-1 Step 2 Activation of Transcription P-TEFb FAT FκB + Histones nuc-0 HMTi = Histone Methyltransferase inhibitors HDACi = Histone Deacetylation Inhibitor
Conclusions Farnesyl transferase inhibitors (FTIs) are a newly identified class of compounds that activate latent HIV gene transcription FTIs synergize with compounds representing diverse MOAs (e.g., HDACi, TFα, PKC agonists) also in primary cell latency model and patient cells (limited data) Synergistic activity is common Many hits from highthroughput screen (unknown MOA) synergize with other MOAs (Jurkat 2C4 cells) Critical questions and next steps: Activity in primary cell subsets (e.g., T CM, T TM, T EM ) Downstream target(s) of FTIs? Follow up work on unknown MOA compounds 28
Acknowledgments Merck Richard Barnard Daria Hazuda Erica Cook Kate Holloway David Powell University of orth Carolina ancie Archin David Margolis Jing Li Renee Hrin Steve Carroll Min Xu Case Western Reserve University Biswajit Das Jon Karn 29
HIV Remission: Compound screening and optimization Michael D. Miller