Discovery and characterization of a small molecule that modulates c-Myc mediated transcription via max homodimer stabilization

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Discovery and Characterization of a Small Molecule that Modulates c-Myc Mediated Transcription via Max Homodimer Stabilization

by

Andrew Chen

B.S., Cornell University, 2011

Submitted to the Department of Biological Engineering in partial fulfillment of the requirements for the degree of

Doctor of Philosophy at the

Massachusetts Institute of Technology June 2019

Author ...

S ig natu re red acted

Department of Biological Engineering May 3, 2019

Signature redacted

C ertified by ...

Angela N. Koehler, Ph.D. Associate Professor of Biological Engineering

Signature redacted

Thesis Supervisor

A ccepted by ... MASSACHUSETTS INSTITUTE

OF TECHNOLOGY

JUL 0

3 2019

Forest M. White, Ph.D. Professor of Biological Engineering Committee Chair

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Thesis committee:

Angela N. Koehler, Ph.D.; Associate Professor of Biological Engineering, MIT (Thesis Supervisor)

Forest M. White, Ph.D.; Professor of Biological Engineering, MIT (Committee Chair) Richard A. Young, Ph.D.; Professor of Biology, MIT

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Discovery and Characterization of a Small Molecule that Modulates c-Myc Mediated Transcription via Max Homodimer Stabilization

by

Andrew Chen

Submitted to the Department of Biological Engineering on May 3, 2019, in partial fulfillment of the

requirements for the degree of Doctor of Philosophy

Abstract

The transcription factor Myc is a basic helix-loop-helix leucine zipper (bHLHLZ) protein with crucial roles in regulating normal cellular processes, but its transcriptional activity is deregulated in a majority of human cancers. Myc transcriptional activity is dependent on dimerization with its obligate partner Max, another bHLHLZ transcription factor. Max also forms homodimers as well as heterodimers with other proteins including the Mxd family of proteins, creating a dynamic network of protein-protein interactions to regulate transcriptional programs. Despite the significance of this network, the arsenal of chemical probes to interrogate these proteins in cancer biology remains limited.

Here, we utilized small molecule microarrays and luciferase-based reporter assays to identify compounds that bind Max and modulate Myc transcriptional activity. We discovered the small molecule KI-MS2-008, which stabilizes the Max homodimer while reducing Myc protein and Myc-regulated transcript levels. KI-MS2-008 also decreases viable cancer cell growth in a Myc-dependent manner and suppresses tumor growth in mouse models of Myc-driven cancers. In a cancer cell line model treated with KI-MS2-008, the equilibrium of protein-protein interactions shifts toward a transcriptionally repressed state over time by recruiting Mxd4 and other repressive machinery to Max. This study establishes that perturbing Max dimerization with small molecules is a tractable approach to targeting Myc activity in cancer.

Thesis Supervisor: Angela N. Koehler

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C o n c lu sio n ... 7 4 A ck n o w led g e m e n ts ... 7 5 Chapter 3: Investigating the strategy of modulating Myc-driven transcription via Max homodimer stabilization by profiling the effects of KI-MS2-008 treatment on cellular and murine cancer models ... 7 6 A b str a c t... 7 6 C o n tr ib u tio n s ... 7 7 In tr o d u c tio n ... 7 8 R esu lts a n d d isc u ssio n ... 7 9 K I-M S2-008 displays a wide variety of responses in cancer cell lines... 79

KI-MS2-008 does not appear to have off-target effects in a panel of kinases...83

In P493-6 cells, KI-M S2-008 treatm ent decreases c-M vc protein levels ... 84

KI-MS2-008 treatment decreases c-Myc protein binding and increases Max protein binding at prom oters of active M yc-regulated genes ... 94

KI-MS2-008 exhibits efficacy in cellular cancer models derived from mice ... 96

K I-M S2-008 exhibits efficacy in m urine cancer m odels ... 98

N e x t ste p s ... 1 0 1 Further m urine studies...101

M aterials an d m ethods ... 101

M ycoplasm a testing ... 101

V ia b le c ell a ssay ... 1 0 2 Tim e course of protein levels...102

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Ubiquitination assay ... 103

R N A -seq ... 1 0 4 q P C R ... 1 0 7 C hrom atin im m unoprecipitation sequencing... 107

Im m unofluorescence staining and im aging ... 109

M yc-addicted tum or cell lines in m ice... 110

M etabolic stability studies ... 110

Pharm acokinetics ... 112

Repeat dose toxicity studies...112

LC/M S analysis of plasm a sam ples ... 113

C o n c lu sio n ... 1 1 4 A cknow ledgem ents ... 115

Chapter 4: Characterization of the Max interactome and its perturbations in response to KI-MS2-0 KI-MS2-0 8 tr e a tm e n t...1 1 6 A b str a c t ... 1 1 6 C o n tr ib u tio n s ... 1 1 7 In tr o d u c tio n ... 1 1 8 Results and discussion ... 120

Approach 1: Monitoring the Max interactome in cell lysates treated with compound ... 120

Approach 2: Monitoring the Max interactome in lysates corresponding to cells treated with c o m p o u n d ... 1 2 5 At long time points of 4 and 8 hours, KI-MS2-008 treatment results in recruitment of transcriptional repressive m achinery to the M ax interactom e ... 127

Preliminary validation experiments appeared to support mass spectrometry findings...132

M ax interactom e characterized by m ass spectrom etry in P493-6 cells...137

Perturbations to the M ax interactom e in M V-4-11 cells ... 142

N e x t ste p s ... 1 4 6 Experiments to validate the recruitment of transcriptional repressive machinery ... 146

M aterials an d m ethods ... 146

C o-im m unoprecipitation ... 146

M ass spectrom etry ... 149

Protein association netw ork analysis via string-db...151

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4.

A cknow ledgem ents ... 155 Chapter 5: Conclusion and future directions ... 156 C o n c lu sio n ... 1 5 6

Future directions...158 Measuring mass and mass accumulation rate at the single cell level with suspended

m icrochannel resonators (SM Rs) ... 158 Proteolysis targeting chim eras (PRO TA Cs) and K I-M SI-001 ... 162 Small molecule microarray screens with cell lysates and endogenous levels of transcription fa c to r s ... 1 7 3

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Acknowledgements

It's been a long, challenging journey since I first arrived at MIT in August 2013 as an

excited first-year student. I knew it would be an academically rigorous test from the beginning,

but I didn't expect the other mental obstacles that were part of the experience and I'd be lying if I

told you I didn't break down a few times. Fortunately, I had world-class mentors and teachers to

guide me through the learning process and skills development, as well as a massive support group

made up of old friends, and new friends going through similar experiences or who had just finished

similar journeys. This section would probably be at least ten pages long if I described everyone

I'm thankful for, so I apologize to those I do not explicitly name. I'll reserve this section to the

individuals who had personal impacts on me; the more formal scientific contributions are listed in

later chapters.

I have learned so much from Angela Koehler, who let me join her lab even though I had

no previous experience with small molecules and did not even know what chemical biology was.

She constantly creates opportunities for learning through research talks, collaborations, and new

types of experiments. I'm always inspired by her breadth of knowledge and enthusiasm for

research that shows up each meeting or talk. The number of names she remembers is

mind-boggling, as is her ability to secure funding for the Myc project. Apart from science, I'm especially

appreciative of Angela's support in finding a reasonable work-life balance, as I was able to

complete my first marathons and Spartan races while completing my studies at MIT.

I have also been fortunate to have incredible scientists guide me as thesis committee

members. Thanks to Forest White for being the chair of this committee and having a massive

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always great to hear regardless. To Rick Young and Phil Sharp for creating the friendliest, most

supportive learning environment for a topic as difficult and complicated as "cell biology: structure

and functions of the nucleus", and suggesting all types of key experiments for this thesis.

The group of people Angela has recruited has made this experience especially memorable.

Thanks to Francisco Caballero, Melissa Kemp and Jiyoung Hong for being so welcoming and

convincing me to join the lab. Extra thanks to Francisco for being so patient while mentoring me

at the beginning of this journey. Many thanks to Rob Wilson for always asking the thorough

questions no one else wanted to ask for good, meticulous science, and educating me about

basketball and rural Indiana. To Shelby Doyle for always offering to help out with written and oral

communication, and cheering me up when I'm down. Thanks to Andre Richters for support in the

lab and running Spartan races with me. To Becky Leifer for taking care of so many things in lab

and supplying adorable videos of her nephew and niece. To Catherine Henry - as well as Helen

Evans and Marius Pop - for hosting lab get-togethers despite also doing a hundred other things.

Thanks to Kristen Frombach and Hanna Tseng for helping me with experiments and always being

excited, friendly and happy (along with Kimia Ziadkhanpour and Katie Gohres, who earned the

title of quokka as her spirit animal). To the whole Myc team of the Koehler lab (Francisco

Caballero, Brice Curtin, Helen Evans, Dave Freeman, Kristen Frombach, Jiyoung Hong, Dylan

Neel, Marius Pop, Eric Stefan, Nick Struntz, Yulong Su, Hanna Tseng, Mattheus (Thijs)

Wildschut, and Rob Wilson) for work included in our paper and this thesis. To Edward (Ted)

Richards, our honorary Koehler lab member, who gave support both in lab and in life. Finally,

thanks to everyone who shaped the culture of the lab to make it fun and to create memories - like

Andre asking Rob which sport March Madness was about and proceeding to win the office bracket

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If you look through the author list of the paper our lab wrote introducing the small molecule

described in this thesis, you'll notice a diverse set of scientists with whom I've had the pleasure of

working. I'd like to specifically thank Anja Deutzmann of Stanford School of Medicine and

Charles Lin of Baylor College of Medicine for answering a seemingly endless barrage of questions

as we prepared this manuscript. To Monica Schenone, Gaelen Guzman, and Annie Apffel of the

Proteomics group at the Broad Institute for running the mass spec experiments and teaching me so

much about mass spec. To Amedeo Vetere for years of attending Koehler lab group meetings and

giving advice that shaped the direction of so many projects including the ones in this thesis. To

Jaime Cheah for supporting me on so many projects as the High Throughput Screening Facility

leader and for introducing me to Spartan racing as a friend.

I could not have made it to MIT without previous mentorship and guidance. Thanks to

Ailong Ke and Fran Ding for accepting me into their lab at Cornell University and teaching me

the basics starting from how to use a pipette. Thanks to my Cornell academic advisor Dan Luo for

support and advice. Thanks to Jun Tian and Bruce Eagan for teaching me how to grow cells in

shake flasks and bioreactors at Bristol-Myers Squibb and shaping my decision to go to graduate

school.

Outside of the lab, I've had support from so many people. Thanks to the BE class of 2013

for helping me through the BE core classes and for all the social events that kept me sane. Thanks

to my former roommates Jaideep Dudani, Naveen Mehta, Bo Qing, and Ben Mead for all the fun

and support, and to my current roommate Alex Wang for being awesome at music and running.

To Natasha Patel-Murray for being the most amazing TA partner ever. To everyone who ever did

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Thanks to all my friends from the past who visited me in Boston while I was working

toward this thesis: Yufei Chen, Yi Deng, Michelle Huynh, Charles Lee, Dennis Liu, and Michael

Shu. Thanks to Margaret Xu for reminding me I'm getting older each year. Many thanks to Han

Jiang for taking me on a food tour of the greater Boston area throughout this journey.

I owe all the opportunities I've been given to my family, who immigrated to America

before I was born. To my mother and father, Tai-Jen Chang and Ray-Der Chen, for making that

decision that changed everything. It's pretty crazy that they left everyone they knew and the culture

they were familiar with to give their kids more opportunities and further their education, but I'm

glad they did it. I'd like to give additional thanks to my mother, who has always done everything

she could to give me more opportunities and encourage learning - from teaching me math when I

was little to bribing me to get good grades in 5th grade to literally driving me to the MIT interview

through a snowstorm when my flight was cancelled so I could nap on the car. To my sisters, Diana

Chen and JiaYing Grygiel, for being the best role models and being supportive of me throughout

my life. I'm grateful to have grown up with them and it's an amazing feeling to know I can share

anything with them and get advice from them. Also, thanks for all the cute pictures and stories of

their kids. And finally, thanks to my cute niblings - Joseph Grygiel, Paul Grygiel, Lily Ton-Nu,

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List of Figures

Figure 1.1. Crystal structure of heterodimer formed from bHLHLZ regions of c-Myc (blue) and Max

(red) binding the E-box sequence of DNA . ... 21

F igure 1.2. T he M ax netw ork...27

Figure 1.3. Structures of M yc/M ax disrupters. ... 31

Figure 1.4. Structure of Max/Max homodimer stabilizer NSC 13728 ... 33

Figure 2.1. Discovery of putative Max binders using small molecule microarrays... 39

Figure 2.2. Prioritization of Max binders that modulate Myc-driven transcription... 40

Figure 2.3. Prioritization of a lead compound from top hits... 41

Figure 2.4. Chemical structures of KI-MS2-001 analogues to establish cursory SAR. ... 43

Figure 2.5. Analysis of KI-MS2-001 analogues in Myc dual luciferase reporter assays. ... 44

Figure 2.6. Analysis of KI-MS2-001 analogues in CellTiter-Glo@ assays... 45

Figure 2.7. KI-MS2-001 and KI-MS2-008 modulate Myc-driven transcription in cells and inhibit viable cell levels in a M yc-dependent m anner... 48

Figure 2.8. KI-MS2-001 and KI-MS2-008 do not affect viable cell levels of PCl2 cells... 50

Figure 2.9. K I-M S2-081 engages M ax in vitro ... 52

Figure 2.10. KI-MS2-081-linked beads pull down many cellular proteins... 55

Figure 2.11. Workflow schematic for KI-MS2-085... 56

Figure 2.12. KI-MS2-085 engages Max in vitro and in live cells... 57

Figure 2.13. KI-MS2-008 engages Max in live cells as seen by cellular thermal shift assay. ... 59

Figure 2.14. KI-MS2-008 engages chemically stabilized Max...60

Figure 2.15. KI-MS2-008 induces Max/Max homodimerization... 62

Figure 3.1. Profiling of KI-MS2-001 and KI-MS2-008 in cancer cell lines... 80

Figure 3.2. Dose-response curves for viable cell levels in a variety of cancer cell lines, including some derived from KrasLSL-GI2 D/+;Trp53Flox/Flox (KP) mouse models, in response to treatment with KI-MS2-008. ... 8 1 Figure 3.3. Normalized viability values for a panel of almost 500 adherent cell lines at 4 doses of KI-M S2-008 as m easured by PR ISKI-M ... 82

Figure 3.4. Normalized viability values for a panel of almost 300 suspension cell lines at 4 doses of KI-M S2-008 as m easured by PR ISKI-M ... 83

Figure 3.5. K inase profiling of K I-M S2-008... 84

Figure 3.6. KI-MS2-008 decreases Myc protein levels, while other protein levels in the network were u n ch an g ed . ... 8 5 Figure 3.7. Protein levels of c-Myc after treatment with KI-MS2-008 in various cell lines. ... 86 Figure 3.8. Time course of c-Myc, c-Myc (pS62), c-Myc (pT58) and corresponding vinculin protein

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Figure 3.9. Dose-response effect of KI-MS2-008 on c-Myc, c-Myc (pT58) and vinculin protein levels. 89

Figure 3.10. KI-MS2-008 affects the global Myc transcriptional program... 93

Figure 3.11. KI-MS2-008 treatment decreases c-Myc protein binding and increases Max protein binding at prom oters of M yc-occupied genes...95

Figure 3.12. KI-MS2-008 treatment specifically decreases Myc-regulated gene expression. ... 96

Figure 3.13. KI-MS2-008 exhibits efficacy in cellular and murine cancer models. ... 98

Figure 3.14. Metabolism and toxicity in mouse microsomes and mice... 100

Figure 4.1. Quantitative mass spectrometry allows comparisons of relative protein abundance between sam p les... 1 19 Figure 4.2. Workflow for Max-anchored pulldown of cell lysates treated with 20 pM KI-MS2-008 or DMSO, followed by quantitative mass spectrometry. ... 120

Figure 4.3. Immunoblots of c-Myc and Max when P493-6 lysates were treated with 20 IM KI-MS2-008 or D M S O ... 12 1 Figure 4.4. Max interactome when cell lysate was treated with KI-MS2-008... 122

Figure 4.5. Effect of KI-MS2-008 on Max interactome when cell lysate was treated with KI-MS2-008. ... 12 3 Figure 4.6. Workflow for Max-anchored pulldowns of proteins from cell lysates generated from P493-6 cells treated with 20 tM KI-MS2-008 or DMSO, followed by quantitative mass spectrometry... 125

Figure 4.7. Immunoblots of c-Myc and Max when P493-6 cells were treated with 20 pM KI-MS2-008 or D M SO at various tim e points. ... 126

Figure 4.8. Effect of KI-MS2-008 on the Max interactome when P493-6 cells were treated with 20 [tM K I-M S2-008 or D M SO . ... 128

Figure 4.9. Max network analysis at 4 and 8 hours for P493-6 cells treated with KI-MS2-008 or DMSO. ... 13 0 Figure 4.10. Preliminary validation of Max-Mxd4 and Max-Mxd4-Sin3a interactions strengthened by K I-M S2-008 treatm ent. ... 133

Figure 4.11. Kinetics of Max interactome protein levels increased in response to KI-MS2-008 treatment. ... 13 5 Figure 4.12. Kinetics of Max interactome protein levels decreased in response to KI-MS2-008 treatment. ... 13 6 Figure 4.13. Max interactome defined by Max-anchored co-immunoprecipitations followed by mass sp ectrom etry ... 13 9 Figure 4.14. Preliminary Max interactome using the cell lysate-based approach... 140

Figure 4.15. Prothymosin alpha (Ptma) was discovered to be enriched in the Max interactome in MV-4-11 cells treated w ith 50 pM K I-M S2-008... 143 Figure 5.1. Mass accumulation rate (MAR) and cell mass distributions for P493-6 cells treated with

D M S O ... 16 0

Figure 5.2. Mass accumulation rate distributions for P493-6 cells treated with 10 gM KI-MS2-008 or D M S O for 8 h ours. ... 16 1

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Figure 5.3. Structure of K I-M S1-001... 164

Figure 5.4. Effect of KI-MS1-001 on Myc transcriptional activity and P493-6 viable cell levels... 164

Figure 5.5. Cell line profiling for KI-MS1-001 across the NCI CTD2 cell line panel of over 800 cell lin e s... 16 5 Figure 5.6. Correlation between sensitivity of cell lines toward KI-MSI-001 and gene expression of the M y c ... 16 6 Figure 5.7. Dose-response curves for effect of KI-MS1-001 on kinases most sensitive to compound treatm en t. ... 16 7 Figure 5.8. Effect of ATP and KI-MSI-001 concentrations on Haspin activity (top) and Lineweaver-Burk plot of 1/v vs. 1 [S] to evaluate the effect of KI-MS1-001 on Haspin (bottom). ... 168

Figure 5.9. Immunoblots of Haspin, c-Myc and Max from samples containing proteins pulled down by beads linked to KI-MS1-055 with varying amounts of compound on the beads. ... 170

Figure 5.10. Cursory structure-activity relationships for KI-MS1-001 with activity in Myc transcriptional reporter and inhibitory effect on H aspin... 171

Figure 5.11. Schematic for SM M screens of cellular lysates... 175

Figure 5.12. Recombinant c-Myc protein was produced from E. coli. ... 176

Figure 5.13. Snapshots of subarrays from a completed small molecule microarray screen. ... 178

Figure 5.14. Myc dual luciferase reporter assay results for 16 of the 19 hits from small molecule microarray screens of purified c-Myc and c-Myc containing cell lysates. ... 179

Figure 5.15. Viable cell counts of various SMM hits and lead compounds MS1-001 (MS 1) and KI-M S2-001 (KI-M S2) 72 hours after treatm ent... 181

Figure 5.16. 3 novel compounds (BRD-9694, BRD-7700 and BRD-6589) inhibited the growth of NAMALWA cells in a dose dependent manner comparable to our lead compounds KI-MS1-001 (KI-M S1) and K I-(KI-M S2-001 (K I-(KI-M S2). ... 182

Figure 5.17. 3 novel compounds inhibited c-Myc transcriptional activity in HEK-293T cells in a dose dependent manner similarly to lead compounds KI-MS1-001 (KI-MS1) and KI-MS2-001 (KI-MS2).. 183

Figure 5.18. Dose-response curves of viable cell levels in response to treatment with BRD-9694 and BRD-6589 in P493-6 cells with or without doxycycline... 184

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List of Tables

Table 1. Analysis of KI-MS2-001 analogues in cellular assays... 46

Table 2. Proteins most strongly recruited to the Max interactome when P493-6 cell lysate was treated w ith 20 pM K I-M S2-008. ... 124 Table 3. Proteins most strongly recruited to the Max interactome when P493-6 cells were treated with 20

pM K I-M S2-008 for 8 hours... 129

Table 4. Values for proteins most strongly recruited to the Max interactome at long time points of 4 and 8 h o u rs... 13 1 Table 5. Values for proteins most strongly recruited to the Max interactome at long time points of 4 and 8

hours in P 493-6 cells... 137

Table 6. Proteins in the M ax interactom e... 138 Table 7. Values for proteins most strongly recruited to the Max interactome at 30 minutes in MV-4-1 1

ce lls... 14 4

Table 8. Values for proteins most strongly recruited to the Max interactome at 8 hours in MV-4-1 1 cells.

... 14 5 Table 9. List of cell lines most sensitive to KI-MS1-001 treatment... 166 Table 10. Common enzyme inhibition types, the mechanism of action and the slopes and y-intercepts in

the L inew eaver-B urk plot. ... 169 Table 11. The 3 novel compounds had comparable solubility and potency in the viability assay... 182

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List of Abbreviations Used

acetonitrile (ACN)

Administrative Panel on Laboratory Animal Care (APLAC) analytical ultracentrifugation (AUC)

basic helix-loop-helix leucine zipper (bHLHLZ) bioluminescence imaging (BLI)

a G 1/S-specific cyclin-D 1 (CCND 1) cyclin dependent kinase (CDK) cellular thermal shift assay (CETSA)

chromatin immunoprecipitation sequencing (ChIP-seq) collision induced dissociation (CID)

chromosomal passenger complex (CPC) counts per million mapped reads (CPMs) CellTiter-Glo@ (CTG)

elution (E)

Enhancer boxes (E-boxes)

ethylenediaminetetraacetic acid (EDTA) ethyleneglycol tetraacetic acid (EGTA)

eukaryotic translation initiation factor 3 subunit A (Eif3a) eukaryotic translation initiation factor 4E (EIF4E)

enzyme-linked immunosorbent assays (ELISAs) electrophoretic mobility shift assays (EMSAs) enrichment scores (ES)

10058-F4 (F4) formic acid (FA)

fluorescence resonance energy transfer (FRET) flow through (FT)

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gene set enrichment analysis (GSEA) threonine 3 of histone 3 (H3T3)

HALLMARKMYCTARGETS _V2 (HALLMARK MYC) hepatocellular carcinoma (HC)

haemotoxylin and eosin (H&E)

2-Hydroxypropyl)-p-cyclodextrin (HPBCD) human serum albumin (HSA)

input (I)

inhibitor of acetyltransferases (INHAT)

isobaric tags for relative and absolute quantification (iTRAQ) Institutional Animal Care and Use Committee (IUCAC) Kras LSL-GI2D/+; Trp53Flox/Flox (KP)

liquid chromatography - mass spectrometry (LCMS)

Matrix Assisted Laser Desorption/Ionization (MALDI) mass accumulation rate (MAR)

mechanism of action (MoA) moesin (Msn)

Max dimerization protein 4 (Mxd4)

nucleus accumbens-associated protein 2 (Nacc2) normalized enrichment scores (NES)

NSC13728 (NSC)

NOD/SCID/IL-2Ry"nul (NSG)

osteosarcoma (OS)

protein-fragment complementation (PCA) propidium iodide (PI)

phosphatidylinositol 3-kinase (PI3K) protein-protein interactions (PPI)

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prothymosin alpha (Ptma) REST corepressor 1 (Reorl)

reads per million per basepair (rpm/bp) structure-activity relationship (SAR) size exclusion chromatography (SEC)

stable isotope labeling by amino acids in cell culture (SILAC) small molecule microarrays (SMMs)

suspended microchannel resonators (SMRs) signal to noise ratio (SNR)

surface plasmon resonance (SPR) serine/arginine protein kinase (SRPKl) transcriptional activation domain (TAD) T-cell acute lymphoblastic leukemia (T-ALL) tandem mass tags (TMT)

transcriptional start sites (TSSs) wash (W)

extracted ion chromatograms (XIC)

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Chapter 1: Introduction

Myc: a master regulator and common oncoprotein

As a master regulator aberrant in -70% of human cancers, the transcription factor c-Myc

has become one of the most studied proteins in history. In 1911, Peyton Rous demonstrated that

cell-free filtrates isolated from chicken sarcomas could be used to induce tumor formation in

recipient chickens (Rous, 1911). This work paved the way toward the discovery of MC29, a virus

that causes myelocytomatosis in chickens, eventually contributing to the name MYC. The virus

itself was found to consist of a gag-myc fusion gene, from which the v-myc gene was characterized

(Hu et al., 1979; Mellon et al., 1978; Sheiness et al., 1978). Finally in 1982, the cellular homologue

c-myc was discovered (Vennstrom et al., 1982).

Since its discovery, a plethora of information has been published surrounding c-Myc

including studies related to structure and mechanism of action. The N-terminus of c-Myc contains

a transcriptional activation domain (TAD), which contacts proteins associated with RNA

polymerase II for transcription and mediates degradation through ubiquitination (Salghetti, 1999;

Tansey, 2014). At the C-terminus, c-Myc contains a basic helix-loop-helix leucine zipper

(bHLHLZ) region that binds to DNA (Prendergast and Ziff, 1991). To bind DNA, however, c-Myc

must first form a heterodimer with another bHLHLZ protein called Max. This interaction causes

c-Myc to change from an intrinsically disordered state to a structured state with coiled coils that

interact with Max (Figure 1.1) (Tansey, 2014). c-Myc-Max heterodimers can then bind to

Enhancer boxes (E-boxes) with the canonical sequence "CACGTG" (Jones, 2004; Blackwood and

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increases transcription of target genes, though repression is also well-known (eg. through binding

with Miz-1) (Salghetti, 1999; Tansey, 2014).

Figure 1.1. Crystal structure of heterodimer formed from bHLHLZ regions of c-Myc (blue) and

Max (red) binding the E-box sequence of DNA (Tansey, 2014).

In addition to the previously mentioned c-Myc interactors Max and Miz- 1, some additional

interactors include TRRAP, PTEF-b and TFIIF. Interactions with TRRAP are necessary to recruit

GCN5 for histone acetyltransferase activity (McMahon et al., 2000), and these interactions are

critical for tumor initiation (Kalkat et al., 2018). Interactions with TFIIF and PTEF-b facilitate

phosphorylation of RNA Pol II and transcriptional pause release, which can accelerate tumor

growth (Bres et al., 2008; Eberhardy and Farnham, 2002; Kalkat et al., 2018). Other c-Myc

interactors are involved in transcriptional activation, transcriptional repression and post

translational modifications (Tu et al., 2015). However, the larger c-Myc interactome remains

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discovery of very different lists of putative c-Myc interacting proteins (Agrawal et al., 2010;

Kalkat et al., 2011; Kim et al., 2010; Koch et al., 2007). This observation suggests that c-Myc

binding proteins may depend on experimental conditions such as the technique used, the cell type

and cell state.

As a master regulator, it is estimated that c-Myc controls 15% of all genes (Patel et al.,

2004). c-Myc controls diverse cellular processes such as the cell cycle, metabolism, protein

synthesis and apoptosis, and interacts with many signaling transduction pathways including the

Wnt pathway and MAPK cascade (Dang, 2013, 2012; Nie et al., 2012). As c-Myc is so crucial for

normal functioning, healthy cells must have tight regulation of c-Myc, which occurs at the

transcription, translation, and post translational steps. c-Myc transcription is regulated through

transcription initiation and release of paused RNA polymerase II in elongation (Bentley and

Groudine, 1986; Eick and Bornkamm, 1986; Krystal et al., 1988). Furthermore, the transcription

initiation factor eIF4E controls the export of c-Myc mRNA to the cytoplasm (Culjkovic et al.,

2006). During the process of forming c-Myc protein, translation can be repressed by the

RNA-binding protein TIAR and is limited by the relatively short half-life of the c-Myc mRNA (~ 10

minutes) (Dani et al., 1984; Mazan-Mamczarz et al., 2006). Finally, the c-Myc protein is controlled

through posttranslational modifications such as phosphorylation, acetylation, glycosylation and

ubiquitination (Chou et al., 1995; Vervoorts et al., 2006, 2003). For example, phosphorylation at

Ser62 stablizes c-Myc and the subsequent phosphorylation at Thr58 marks c-Myc proteins for

degradation (Dang, 2012). Ubiquitination and prolyl isomerization are especially important in

controlling c-Myc protein levels with E3 ubiquitin ligase components and other proteins to

decrease Myc stability, including Fbw7, Skp2, Fbx29, and PinI (Farrell and Sears, 2014; Thomas

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Myc is phosphorylated at Thr58 and Ser62 to lead to dephosphorylation at Ser62. SCFFbw7 _then

recognizes Myc phosphorylated only at T58 to label it for degradation by the 26S proteasome

(Farrell and Sears, 2014; Yeh et al., 2004). These processes limit c-Myc protein half-life to 15 to

20 minutes (Dang, 2012; Hann and Eisenman, 1984).

As an example of normal Myc function and regulation in cell growth and proliferation,

addition of growth factors or mitogens to quiescent cells activates signal transduction pathways,

such as the Wnt pathway and Raf/Mek/Erk kinase cascade (Dang, 2012; Kerkhoff et al., 1998), which can result in 10 - 40 fold increases in expression of Myc mRNA within three hours (Kelly

et al., 1983) and subsequent increases in Myc protein levels three to five hours after addition of

mitogen stimulation (Bretones et al., 2015, Waters et al., 1991). Myc activates expression of many

proteins involved in progression of the cell cycle, including cyclin dependent kinases (CDKs),

cyclins and E2F transcription factors (Bretones et al., 2015). For example, Myc induces expression

of cyclin D2 to advance the cell through the G 1 phase through activated cyclin D2/Cdk4 and cyclin

D2/Cdk6 (Bouchard et al., 2001; Malumbres and Barbacid, 2005). Additionally, Myc increases

expression of cyclin El, which activates cyclin E/Cdk2 in late G1 phase and leads to synthesis of

DNA (Perez-Roger et al., 1997), and promotes transcription of Cdk4 to regulate G1/S phase

transitions (Bretones et al., 2015; Hermeking et al., 2000). Myc activates transcription of

phosphatase Cdc25a (Galaktionov et. al., 1996), which is expressed during early GI phase to

activate CDKs (e.g. Cdk2, Cdk4) and cause cells to move through the GI phase (Zbrmig and Evan,

1996). Activation of CDKs in the G1 phase results in phosphorylation of retinoblastoma protein

to inactivate it and allows the cell to continue the cell cycle to S phase through the release of E2F

transcription factors (Nevins, 2001; Zrnig and Evan, 1996). Other examples of Myc's ability to

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and p27 by repressing transcription of p21 - for example, by interacting with Miz-1 (M6r6y et al.,

2011) - and activating expression of SCFSIP2 _{ubiquitin ligase complex components to ubiquitinate}

p27 to lead to its degradation (Bretones et al., 2011). Meanwhile, to promote cell growth, Myc

regulates enzymes involved in nucleotide production as well as enyzmes involved in glycolysis

and glutaminolysis that provide inputs for the tricarboxylic acid cycle, promotes production of

fatty acids and cholesterol for membrane production, and leads to production of ribosome

components and growth of mitochondria to fuel growing cells (Stine et al., 2015). When the

growth factor or mitogen is no longer present, or when cells reach confluence, c-Myc mRNA and

protein levels decrease rapidly due to their short half lives and aforementioned regulation (Dean

et al., 1986; Waters et al., 1991, Z6mig and Evan, 1996).

Cancers involving deregulated c-Myc activity are estimated to cause the deaths of 100,000

Americans and millions of people worldwide each year (Tansey, 2014). In most of these cancers,

c-Myc is overexpressed rather than mutated. Overexpression of c-Myc typically occurs through

changes in the MYC loci to increase c-Myc mRNA levels (gene amplification, translocations and

increased activation of distal enhancers) and aberrations that sabotage the regulatory mechanisms

of c-Myc (Pomerantz et al., 2009; Tansey, 2014; Wright et al., 2010). Super-enhancers, or large

clusters of enhancers that regulate genes associated with cell identity, can be found in the vicinity

of the Myc gene in tumor cells and vary in location with respect to the Myc gene depending on

cell type (e.g. upstream, within, and downstream of the Myc gene), but are not present in healthy

cells (Hnisz et al., 2013; Schuijers et al., 2018). Elevated levels of c-Myc drive overexpression of

its active target genes rather than upregulate a new group of targets (Lin et al., 2012). Aberrant

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pathways, enhances growth, changes metabolic pathways, damages DNA, and promotes

angiogenesis for metastasis.

In fact, cancer cells with deregulated c-Myc are so transformed that they are "addicted" to

this oncogene and disruption of c-Myc can cause cancer cells to die through a phenomenon called

oncogene addiction (Tansey, 2014). As a proof of concept, the dominant negative Omomyc can

dimerize with Myc proteins, preventing Max from binding Myc (Soucek et al., 1998) and blocking

binding to E-box sequences on DNA (Soucek et al., 2002). In mouse models of lung cancer driven

by Kras G12D, expression of Omomyc decreased the counts of proliferating cells and caused

regression of both early-stage lung adenomas and established lung tumors (Soucek et al., 2008).

As Myc regulates proliferation for normal cells as well, side-effects on rapidly proliferating tissues

such as the skin, testes and gastrointestinal tract are a concern. However, restoration of Myc

function after 4 weeks of Myc inhibition resulted in recovery of these organs (Soucek et al., 2008).

Recently, purified Omomyc has also been shown to cross cell membranes of cancer cells to inhibit

Myc transcriptional activity. This discovery has translated into studies showing its efficacy in

mouse models of lung adenocarcinoma (Beaulieu et al., 2019). Additionally, conditional

transgenic mouse models have been used to show that Myc inactivation via doxycycline addition

can cause a variety of responses such as differentiation, apoptosis and senescence (Felsher, 2010).

The response of the tumors toward Myc inactivation was cell type-specific, ranging in responses

from differentiation with Myc inactivation and apoptosis after restoration of Myc in osteosarcoma

to apoptosis in lymphomas (Felsher, 2010). Outside of the tumor cell, Myc also served crucial

roles in maintenance of the tumor microenvironment in a RIP 1 -Tag2 mouse model, specifically

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While Myc does not dimerize with bHLHLZ proteins other than Max, Max forms dimers

with a family of Mxd proteins and Mga (Conacci-Sorrell et al., 2014) (Figure 1.2). In contrast to

Myc, Max is constitutively expressed (Jiang et al., 2009), and regulation of its effects occurs

through these other binding partners. Through these other interactions, Max exists in a dynamic

equilibrium of protein-protein interactions in which the predominant dimers can influence the

effects on transcription of Myc target genes. For example, Myc/Max heterodimers can recruit

demethylases and histone acetyltransferases to mark chromatin for transactivation and allow RNA

polymerase II to bind the promoter. On the other hand, while Max is bound to Mxd proteins, this

alternative heterodimer form competes with Myc/Max heterodimers for E-box binding and recruits

histone deacetylases to repress transcription of Myc target genes (Poole and Van Riggelen, 2017).

Through a simplified version of the Max network, we can visualize various forms of Max dimers

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proliferation growth arrest self-renewal differentiation N-Myc Max c-Myc Max Mxd3 L-Myc gMn E-Box

Figure 1.2. The Max network. Cartoon diagram of the Max (green) dimerization network

displaying transcriptional activation by the Myc (blue)/Max heterodimer, transcriptional attenuation by the Max/Max homodimer, and transcriptional attenuation and repression by other Max-containing dimers such as the Max/Mxd4 (purple) heterodimer (Conacci-Sorrell et al., 2014).

In 2002, James Darnell argued that targeting transcription factors overactive in human

cancers provides the most direct approach for therapeutics, as there are fewer possible targets and

multiple signaling pathways can converge on the same transcription factor (Darnell, 2002).

However, transcription factors like c-Myc lack enzymatic activity and have thus been dubbed

"undruggable." Unlike enzymes with known active sites, these proteins lack obvious binding

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points and lack hydrophobic folds (Berg, 2008; McKeown and Bradner, 2014). Modulation of

transcription factors would instead require disruption of DNA-protein and protein-protein

interactions (PPI), but defined rules for discovering small molecule PPI disrupters do not yet exist

(Koehler, 2010). Thus, it has been challenging for the scientific community to build high-quality

chemical probes - that is, small molecules that specifically modulate a protein of interest to allow

interrogation of its function in vitro, in cells and/or in animals (Arrowsmith et al., 2015) - for Myc

and Max. In addition to providing an orthogonal tool to CRISPR and RNAi to study the roles of

proteins of interest, chemical probes have advantages in that they can rapidly and reversibly affect

the protein of interest, as well as easily provide tunable dose-responsive effects and temporal

information (Arrowsmith et al., 2015).

Myc-Max heterodimer disrupters

As Myc requires Max for DNA binding, many groups have focused on inhibiting the

Myc/Max interaction, which involves a large protein-protein interface between the two proteins

stretching an area of 3,206

A

2 _{(Nair & Burley, 2003). Using fluorescence resonance energy transfer} (FRET) and enzyme-linked immunosorbent assays (ELISAs), compounds IIA6B 17 and IIA4B20

were found to inhibit c-Myc/Max dimerization and were further shown to block Myc-dependent

oncogenic chicken embryo fibroblast transformation (Berg et al., 2002). Chemical changes to the

core of the molecule were made to improve specificity, leading to a small molecule library of 240

compounds, which was screened using an oncogenic transformation assay. Two small molecules,

II-A5B 12 (Mycmycin- 1) and II-A3B 16 (Mycmycin-2), were found to nearly completely inhibit

Myc-dependent oncogenic transformation at 20 ptM with specificity for Myc compared to Src or

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10050-Cb, 10074-A4, 10074-G5, 10031-B8, 10075-G5, and 10058-F4 - which disrupted c-Myc/Max domain binding in yeast two-hybrid assays, inhibited growth of fibroblasts and c-Myc dependent

transcription (Yin et al., 2003). Of these seven compounds, four (10009-G9, 10050-C1O,

10074-A4 and 10058-F4) were tested in vivo and inhibited tumor growth in mice when Rat la-c-Myc cells

were pre-treated in vitro and then inoculated into nude mice (Yin et al., 2003). Janda and Vogt

discovered NY2267, NY2276, NY2279, and NY2280 from a library of mostly planar and aromatic

moieties via FRET and that these compounds inhibited Myc functions in chicken embryo fibroblast

assays (Xu et al., 2006). As c-Myc mediated transcription requires DNA binding, DNA binding

assays were used to screen libraries of 17,000 and ~1,400 compounds, leading to the discovery of

Mycrol, Mycro2 and Mycro3 (Berg, 2011). These compounds inhibited the c-Myc/Max

interaction, cell proliferation, transcription and oncogenic transformation (Kiessling et al., 2006).

More recently, sAJM589 was discovered via a protein-fragment complementation (PCA) assay.

This compound showed relatively potent effects on viable cell levels (IC5 0 of 1.9 piM in P493-6

cells without doxycycline), affected transcription in a manner consistent with Myc depletion, and

decreased Myc protein levels with treatment possibly due to increased ubiquitin-mediated

degradation (Choi et al., 2017). This brief review of inhibitors of the Myc/Max interaction does

not discuss all of the inhibitors discovered to date, but provides a sense of the significant effort put

in by the scientific community to disrupt this interaction and the types of mechanism-specific

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0 0 N "fCO 2tBu N H H NHMe S02 o ci I B r /N C I Boo IIA6B 17 0 0 N' - CO2tBu BOc-N N H N 'COOH HN 2 Mycmycin- 1 02N N H 10009-G9 0 IIA4B20 N O CO 2tBu N _H _HN _- ₂ 'CONHMe Boc N -/Mycmycin-2 clcl N 0 N

IN0

0-HN O2 N H HN50CN 10050CCI/ CI CI N HO 0 N 0 -10074-A4 O NK CI -N 0 1007 5-G5 NO₂ N 0 N~ N HN 10074-G5 0 NH 10058-F4 0 _o -02C 1003 1-B8 N HO N sAJM589

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N' 0 0 N N 101,O 0 0 tBuO 0 x HN, tBuO 0- HN, 0 0 NY2267 00 N 0 tBuO - HN, 0 NY2279 F F, ,, F 0 NN 0 '- N H N X Mycro 1 C I 0 0 NN 0 C~ - N HN N Mycro3 NY2276 00 N --y0 tBuO 0 HN 0 NY2280 F F,-, F N- N HN Mycro2 02N

/

NO H2N 0 KJ-Pyr-9

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However, many of the aforementioned small molecules failed to show efficacy in vivo. To

my knowledge, the first example of a Myc-Max interaction inhibitor to show efficacy in vivo

without first pre-treating the tumor cells came from the labs of Vogt and Janda (Hart et al., 2014).

From a fluorescence polarization screen and an assay to test the efficiency of Myc-induced

oncogenic transformation in chicken embryo fibroblasts, four small molecules were found to be

effective. Among these, KJ-Pyr-9 (Figure 1.3) had the highest solubility in water and became the

subject of further study. This molecule exhibited specificity for Myc and N-Myc compared to other

oncoproteins: v-Src, v-Jun and an H1047R mutant of phosphatidylinositol 3-kinase (P13K). In

P493-6 cells, an engineered B cell line with a Tet-off system for Myc, the compound inhibited

proliferation and downregulated expression of Myc-regulated genes. The compound also

suppressed the growth of a xenograft of MDA-MB-231 in mice given daily intraperitoneal

injections of 10 mg/kg, becoming the first Myc/Max disrupter to exhibit in vivo efficacy (Hart et

al., 2014). The potential of Myc/Max disrupters to display in vivo efficacy was also observed with

Mycro3, which increased cancer cell apoptosis, reduced cell proliferation and promoted tumor

shrinkage of mutant KRAS-driven pancreatic ductal adenocarcinoma when moribund mice were

treated with daily oral doses of 100 mg/kg Mycro3 (Stellas et al., 2014). Additionally, obstacles

delivering Myc/Max inhibitors were overcome when a prodrug version of 10058-F4 was

encapsulated in nanoparticles targeting integrin-expressing multiple myeloma cells (Soodgupta et

al., 2015). In this study, the use of a prodrug enabled stabilization and encapsulation of the drug in

the hydrophobic portion of the nanoparticles to prevent early release during delivery. The inhibitor

10058-F4 without nanoparticle-aided delivery did not provide improvements in survival of mice

and this study provided the first evidence that Myc/Max inhibitors previously limited by poor

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Max-Max stabilization as an alternative method to inhibit Myc

As an alternative strategy to regulate Myc function, Vogt's group postulated that

stabilization of the Max homodimer could attenuate Myc-driven transcription by reducing the

amount of Max available to bind Myc and form Myc/Max heterodimers to mediate transcription.

Using virtual ligand screening on the full structures of Myc/Max and Max/Max dimers, they

identified three sites that contained 85% of the compounds predicted to bind Myc/Max and

Max/Max dimers. The compound NSC13728 (Figure 1.4) bound to the third binding site, which

provided specificity for Max/Max dimers over Myc/Max dimers compared to the other two binding

sites due to a binding site in the Max/Max dimer that is blocked by Max residues Arg 254 and Gln

261 in the Myc/Max heterodimer. Stabilization of the Max/Max homodimer by NSC 13728 was

reinforced by FRET and analytical ultracentrifugation observations. NSC 13728 was found to also

directly inhibit the Myc/Max interaction via co-immunoprecipitation, ELISA and surface plasmon

resonance (SPR) experiments. The compound decreased the proliferation of Q8 cells (a cell line

transformed by v-myc), inhibited Myc-mediated oncogenic transformation of chicken embryonic

fibroblasts (IC50 of 3 pM) and decreased Myc-mediated transcription in HEK293T cells (Jiang et

al., 2009). The discovery of this molecule suggested that stabilization of the Max homodimer could

indirectly attenuate Myc-driven transcription. Despite the success of this strategy to indirectly

inhibit Myc, this area of research has been understudied.

N N N N

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Chapter 2: Discovery of a Max-binding small molecule that modulates

Myc-driven transcription via stabilization of the Max homodimer

Abstract

Due to the challenges in designing small molecules to bind intrinsically disordered

proteins, small molecule microarrays (SMMs) were used to screen a library of 45,000 compounds

for ability to bind purified recombinant Max. After specificity and purity filters, 16 compounds

were tested for inhibitive effects on Myc transcriptional activity. Of the 6 compounds with IC50

values less than 5 pM, KI-MS2-001 emerged as a lead compound with reasonable

physicochemical properties. Cursory structure-activity relationship (SAR) studies led to the

discovery of the analogue KI-MS2-008, which could be accessed through a simplified synthetic

pathway and had slightly more potent activity in Myc reporter and viable cell assays compared to

the original SMM hit. The SAR studies also led to the development of two analogues with

modifications that enabled target engagement experiments, which further suggested binding of the

compound to Max in both cell lysate and live cells. Target engagement to Max was also supported

by cellular thermal shift assays and NMR spectroscopy. In electrophoretic mobility shift assays

(EMSAs), analytical ultracentrifugation (AUC), and size exclusion chromatography (SEC),

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This chapter reuses material from:

Nicholas B. Struntz*, Andrew Chen*, Anja Deutzmann, Robert M. Wilson, Eric Stefan, Helen L. Evans, Maricela A. Ramirez, Tong Liang, Francisco Caballero, Mattheus H. E. Wildschut, Dylan V. Neel, David B. Freeman, Marius S. Pop, Marie McConkey, Sandrine Muller, Brice H. Curtin, Hanna Tseng, Kristen R. Frombach, Vincent L. Butty, Stuart S. Levine, Clementine Feau, Sarah Elmiligy, Jiyoung A. Hong, Timothy A. Lewis, Amedeo Vetere, Paul A. Clemons, Scott E. Malstrom, Benjamin L. Ebert, Charles Y. Lin, Dean W. Felsher, Angela N. Koehler. "Stabilization of the Max homodimer with a small molecule attenuates Myc-driven transcription." Cell Chemical Biology, 26, 1 - 13, 2019.

* co-first authors

Contributions

A.N.K. performed the small molecule microarray screens. M.M. and B.L.E. performed the

secondary screen of Myc transcriptional activity. F.C. performed cellular assays for KI-MS2-001

analogues. E.S., H.L.E., B.H.C., and T.A.L. synthesized small molecules. M.S.P., D.B.F, and

B.H.C. analyzed NMR studies. N.B.S. performed target engagement studies with KI-MS2-085

and KI-MS2-008, and performed mechanistic studies involving Max/Max homodimer

stabilization. G. Guzman and M. Schenone performed mass spectrometry experiments associated

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Introduction

As previously discussed, inhibition of transcription factors often involves disruption or

stabilization of protein-protein or protein-DNA interactions (Koehler, 2010). These interfaces are

typically large and lack obvious binding pockets from which small molecules could be designed

(McKeown and Bradner, 2014). Due to the challenges in small molecule design, our approach to

discovering small molecules with specific binding and functional properties involved

implementation of a critical path containing high-throughput screening assays coupled to

functional and mechanistic assays. We then synthesized analogues of lead compounds to

understand cursory structure-activity relationships, which enabled use of analogues for target

engagement studies validating binding of the lead compound to the target proteins in both in vitro

and cellular settings.

For a primary screen in this critical path, we used the small molecule microarray (SMM)

technology. These screens involve glass slides functionalized with up to 12,288 printed chemical

array features, enabling fast, robust screening of tens of thousands of small molecules (Figure

2. lA). For isocyanate-mediated attachment to the glass slide, the small molecule must contain a

reactive nucleophile such as an amine, hydroxyl, phenol, carboxyl, thiol, urea, hydroxamic acid or

amide (Casalena et al., 2012). Small molecules with multiple functional groups can be displayed

in multiple orientations, allowing many different binding orientations to be sampled for such small

molecules. In contrast to many of the other high-throughput screening approaches used to discover

inhibitors of the Myc/Max interaction, small molecule microarrays offer a mechanism-unbiased

approach, screening for small molecules capable of binding a target protein throughout its structure

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In this study, a solution of purified recombinant Max protein was used to screen against

the compound library and SMM positives would be expected to bind to Max protein directly. The

small molecule microarray platform has also been used to study binding - whether direct or

indirect - to a protein of interest in cellular lysates (Bradner et al., 2006; Bradner et al., 2006). The

lysate-based strategy is expected to retain proteins in a more native state, as - especially often the

case with transcription factors - they may be more folded and structured when bound to their

usual binding partners. In this case, the small molecule could interact with the more folded and

structured version of the protein, but could also bind to nearby complex members (Bradner et al.,

2006; Vegas et al., 2008).

Since lead compounds were discovered to bind the target protein in an in vitro setting using

small molecule microarrays, additional studies should be completed to confirm that the compound

binds the target protein in more cellular settings. Additionally, since small molecule microarrays

could select compounds with a variety of mechanism of actions (MoAs), MoA studies will be

required to establish a high-quality chemical probe (Frye, 2010). While it may seem like a

disadvantage to use a mechanism-unbiased screening approach and be required to interrogate the

mechanism of action later, this property of the SMM can also be viewed as an advantage. The

simple and flexible nature of the SMM can cast a wider net compared to a mechanism-specific

assay such as FRET or PCA, allowing discovery of small molecules with favorable properties that

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Results and discussion

Small molecule microarrays and Myc reporter assays led to the prioritization of KI-MS2-001 from a library of 45,000 compounds.

Previously, small molecule microarrays were used to screen a library of 15,252 compounds against 100 proteins that were diverse in terms of sequence and structure, and related to transcriptional regulation. These compounds included commercial compounds common in many chemical libraries (6,152 compounds), academic compounds created via diversity-oriented synthesis (6,623 compounds) and natural products (2,477 compounds). One of the 100 proteins screened was purified recombinant Max (Clemons et al., 2010). When combined with an additional screen against a library of compounds derived from diversity-oriented synthesis, a total of-45,000 compounds were screened against purified recombinant Max, yielding 117 putative Max binders (Figures 2.1B and 2.1C).

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B C ~-;t--~ ~/ / 500 400 N 300 200 100 0-5.0 * Compound *Hit DMSO -2.5 25 5.0 7.5 Composite Z C 0 0 500 400 300 200 100 0 -5.0 Z Score C -1 0 Z Score A ~ Z Score C 4 -21 Z Score AZ o

Figure 2.1. Discovery of putative Max binders using small molecule microarrays. (A) Schematic

of a small molecule microarray (SMM) showing SMM positives (red spots), which were detected

by AlexaFluorTM _{647-labeled antibodies against the His-tag on the purified Max protein. (B) SMM}

screening results for DIV06 compound library, which is comprised mostly of products of diversity-oriented synthesis (n = 3 technical replicates). Histogram of composite Z-scores and 3D scatterplot

showing Z-scores of feature to background ratios in triplicate for compounds on the SMMs. (C) SMM screening results for NPC 'Natural Products and Commercials' compound library array set, which contains natural products and commercial 'drug-like' compounds (n = 3 technical

replicates). Histogram of composite Z scores and 3D scatterplot showing Z scores of feature to background ratios in triplicate for compounds on the SMMs.

After prioritizing small molecule microarray positives specific to Max compared to the

other proteins screened against the same set of molecules and filtering out small molecules less

than 70% pure as measured by liquid chromatography - mass spectrometry (LCMS), 16

compounds were evaluated for their ability to inhibit Myc transcriptional activity in a dual

luciferase reporter. In this assay, tandem repeats of the Myc response element are located upstream

of firefly luciferase, while Renilla luciferase is constitutively expressed as a control. Thus,

* Compound Hit DMSO

A

-2.5 0.0 2.5 Composite Z 5.0 7.5 A

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from firefly luciferase to Renilla luciferase (Figure 2.2A). Using this reporter assay, we identified

six compounds that inhibited Myc transcriptional activity with an IC50 less than 5 piM (Figures

2.2B and 2.3A). Among these six compounds, the DOS polycyclic lactam BRD-K19261677

(KI-MS2-001) had one of the lowest IC50 values at 1.06 ptM, retained activity upon resynthesis and

exhibited reasonable physicochemical properties (Figures 2.3B and 2.7A). Overall, we prioritized

the small molecule KI-MS2-001 from a library of ~45,000 compounds (Figure 2.3C).

A Myc dual reporter assay Myc RE - BRD-K47764688 BRD-K86761848 1.5 - BRD-K37194137 - BRD-K19261677 - BRD-K11302628 -+1BRD-KO0944562 1.0 -BRD-K89131691 BRD-K90970053 a, 24 _{BRD-K05452595} S0.5 - BRD-K77877933 0 z BRD-K94173926 - BRD-K39984193 - BRD-K90849765 0.0 - BRD-K89156937 0.1 1 10 100 - BRD-K16290432 Concentration (pM) - BRD-K55071917

Figure 2.2. Prioritization of Max binders that modulate Myc-driven transcription. (A) Myc dual reporter assay design to filter SMM hits. (B) Dose-response curves of Myc-transcriptional activity for SMM positives after purity triage. Red curves correspond to the six compounds with IC5o values less than 5 pM (n = 3 technical replicates, error bars represent mean SD).

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-41 A HO N N KI-MS2-001 BRD-K19261677 IC, = 1.06 pM: SMM CompZ = 3.54 cLogP = 5.15 N₃ -OH OM HO N N N₃ BRD-K55071917 IC_{50 =}2.68 pM: SMM CompZ = 3.81 cLogP = 2.38 Property KI-MS2-001 Mean protein _>99.9 bound (%) Mean recovery ₈₆ Solubility (PBS, pM) 9 Solubility (intestinal fluid. pM) 200 Solubility (gastric fluid, pM) 51.2 CACO-2 permeability 23.6 (10- cm/s) Efflux ratio (BA/AB) Liver microsome stability (min) NO U BRD-K371 94137 IC5 = 4.24 pM; SMM CompZ =4.14 cLog P = 6.79 O9~oH HH H N 0 N N N0 BRD-K16290432 IC5 0 =0.794 pM; SMM CompZ= 3.63 cLogP = 4.78 C Number of compounds HN3 BRD-K90849765 IC5 = 1.63 pM; SMM CompZ = 3.81 cLogP = 3.56 N3 0 HO O N NH2 N3 BRD-K89156937 IC5 = 3.48 pM: SMM CompZ = 4.26 cLogP = 2.25 Screening activity Criteria for advancement -45,000 primary Max SMM binding assay compZscore > 3.5

117 specificity filter vs. >100 proteins selective for Max evaluation of purity in DMSO stocks > 70% by LCMS

16 Myc reporter gene assay in dose IC5 < 5 pM

6 evaluation of physicochemical properties, potential reactivity, ease of synthesis

N 0

N- 0 N--- 0

BRD-K19261677 KI-MS2-008

(KI-MS2-001)

21

Figure 2.3. Prioritization of a lead compound from top hits. (A) Chemical structures for the 6

SMM hits against purified Max protein after dose-response Myc dual reporter assay. Blue side chains denote site of attachment to SMMs. cLogP values were calculated by ChemDraw Professional 15.0. (B) Experiments were conducted at Cerep. Fraction of the compound that is bound to proteins as determined by a protein binding assay that simulates human plasma, solubility of KI-MS2-001 in aqueous buffers, bidirectional permeability of KI-MS2-001, and liver microsome stability of KI-MS2-001. (C) Prioritization scheme for Max binders that modulate Myc-driven transcription leading to hit stock solution BRD-K19261677 (resynthesized as

KI-MS2-001) and KI-MS2-008 as a more potent and synthetically accessible probe.