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4.5 Defining SAR and Functional Assays 75
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4.5 Defining SAR and Functional Assays
Compounds that bind to a target RNA and demonstrate target engagement should be tested in at least one functional assay (preferably more to mitigate false positives) to determine if the observed binding leads to a change in the level of protein expression. Once an RNA binder demonstrates on-target functional activity (as further demon­strated by in-cell target engagement, vide supra), the RNA binder is fully validated. By acquiring functional data in tandem with binding data, SAR can be developed and applied to new designs, thus propelling the design-make-test-analyze cycle [118]. Researchers may apply the same principles from protein target-based drug discov­ery to optimizing RNA binders by designing and making structural changes to the binder, gathering and analyzing data, and then formulating new structural changes to improve binding, drug-like properties [119], and functional activity. For RNA drug discovery, this is best exemplied by risdiplam [120] and branaplam [121], splice modulators that will be further discussed in Chapter 7. Further, Ernst and colleagues optimized [122] rocaglamide A and congeners, a class of natural products that inhibits protein synthesis by forming a stable ternary complex with polypurine rich messenger RNAs and eIF4A [123]. The authors made derivatives with improved drug-like properties and discovered eFT226 (zotatin) that is currently in clinical development to treat cancer.
4.5.1 Functional Assays
A functional assay can be designed based on the RNA target of interest and the mechanistic hypothesis. Cellular gene-reporter assays are commonly employed, wherein the level of protein expression is assessed via a surrogate reporter. These can be tested in a cell-free environment rst [124]. Fluorescent proteins and luciferases are examples of such reporters and can be introduced via methods such as viral transduction, transient transfection, or endogenous gene editing. A second reporter driven by an IRES in a bicistronic expression vector can help normalize signal [125]. For example, Todd and co-authors used a dual luciferase reporter assay to conrm if small molecule BIX01294 could inhibit +1CGG translation (as measured by NanoLuciferase luminescence) in HEK293 cells, and at 25μM, +1CGG RNA translation was signicantly reduced although the compound was found to be moderately toxic by measure of FireyLuciferase luminescence and cell morphology [126]. A popular version of luciferase reporter called HiBiT utilizes a split luciferase concept, whereby a small N-terminal sequence of NanoLuciferase can be expressed at the endogenous locus of the target gene and reconstituted with the remainder of the NanoLuciferase in the form of a recombinant protein along with a substrate. This gives a bioluminescent readout for the tagged target protein [127].
Minigene splicing reporters are used to assess compounds that have an eect on mRNA splicing [128]. Precursors for risdiplam, a drug used to treat SMA [129], were identied using a high-throughput screen with a luciferase reporter minigene. Although the discovery was made via a cell-based screen, one could apply such an
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assay to assess functional activity from binding rst approaches. Additional methods of assessing the function of RNA-binding small molecules include immunoassays, which are used to determine the protein levels of the target of interest. These types of assays include western blotting, Simple WesternsTM[130], and many forms of sandwich ELISA such as traditional ELISAs, electrochemiluminescence-based MSD [131], and bead-based (no-wash) AlphaLISA [132]. Mass spectrometry and proteomics are also used for assessing levels of protein coded by a target RNA [133]. These methods are important for conrming changes in the levels of proteins in endogenous settings of cells or animals. Emerging technologies are sure to make this evaluation more robust and easier.
4.5.2 Phenotypic Screens
Phenotypic screens [134] are functional assays that identify compounds based on an observed phenotype (biological eect) without knowledge of molecular target or mechanism (agnostic screening). These screens have also been used to discover RNA binders despite being agnostic to a small molecule’s target. Phenotypic screens can be formatted to be high throughput, and in the cases of risdiplam [120] and branaplam [121], phenotypic screens identied hits that were further optimized to the respective lead series. After several rounds of optimization, risdiplam was approved for treatment of SMA (cf. Section 4.6 and Chapter 7). Careful target engagement and mechanism of action studies should be carried out to determine whether a molecule is acting through an RNA interaction mechanism. For example, didehydro-cortistatin A (dCA) inhibits production of new viral particles from HIV-1-infected cells, but Mousseau and coworkers demonstrated that dCA disrupts transcription of the integrated HIV-1 genome by binding to the TAR-binding domain of Tat, not to TAR RNA [135].
4.6 Identifying a Lead Series
Forsmall molecules, it is well known what constitutes a good lead series [136]. A lead series is identied once RNA binding is conrmed by at least two orthogonal bio­physical methods (cf. Section 4.3), has SAR that repeats across dierent methods, is selective for a target RNA, shows target engagement in cells connected to a cellular response (cf. Sections 4.4 and 4.5), and has reasonable pharmacokinetic properties. Figure 4.10 outlines the process for identifying a lead series with the goal of ulti­mately delivering a compound for clinical development.
Hit conrmation involves structure conrmation by resynthesis and purication, which is critical to ensure that the presumed structure is correct. Conrmed hits should also demonstrate binding to an RNA by at least two orthogonal biophysical methods. Further, SAR around similar analogs should be consistent across dierent biophysical methods. Hit optimization entails improvements in SAR regarding binding anity and functional activity. Compounds in this stage should also demonstrate target engagement (cf. Sections 4.4 and 4.5) and should be screened
4.6 Identifying a Lead Series 77
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Hit confirmation: structure
confirmation by resynthesis and
purification, binding by 2
orthogonal biophysical methods,
tractable SAR
Lead optimization: lead series
identified with detailed SAR,
reasonable pharmacokinetics,
selective, cellular response linked
to in-cell target engagement
Figure 4.10 Process for identifying a lead series with the goal of making a compound for clinical development. First, a hit is found, confirmed, and optimized using methods discussed in Sections 4.1 through 4.5. The lead series is further optimized to a drug candidate that should demonstrate activity and selectivity in vitro and in vivo and have toxicological data acquired in multiple species.
Hit optimization: improve SAR in
binding affinity and functional
activity, demonstrate target
engagement, improve selectivity,
improve pharmacokinetic
properties
Drug candidate: demonstrated
activity and selectivity in vitro
and in vivo
for selectivity for the RNA of interest among other RNAs in the transcriptome. Pharmacokinetic properties should also be tested for and improved in this stage. A lead series is selected after gathering detailed SAR across binding and functional assays, reasonable pharmacokinetics, selectivity information regarding RNA targets and protein targets, and linking any cellular response to in-cell target engagement. Ultimately, the lead series can be further optimized to a drug candidate that should demonstrate activity and selectivity in vitro and in vivo and have toxicological data acquired in multiple species.
4.6.1 Hit Optimization
Also known as hit-to-lead [137], the goal of hit optimization is to improve an RNA binder’sanity,functional activity,selectivity,and pharmacokinetic properties with the eventual goal being to assess in vivo ecacy. Work in this phase consists of SAR investigations around an RNA binder, combining data gathered from binding and functional assays, and making new structural hypotheses to further improve a compound. If structural information about an RNA is known, structure-based drug design techniques can be applied to develop the SAR faster and in a more focused way.
Selectivity and toxicity should also be interrogated, optimized, and mitigated, respectively, at this point. Selectivity may be assessed through several methods. First, a selectivity panel of RNAs can be tested for binding by a hit analog using one of the biophysical methods previously mentioned in this chapter. Second, a PEARL-seq probe (or a similar probe mentioned in Section 4.4) may be developed
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for a hit analog that assesses target engagement across the transcriptome [23]. Third, RNA-seq [138] may be used to assess selectivity by measuring global gene expression changes induced by treatment with an RNA binder. Fourth, tradi­tional methods may be used to interrogate selectivity and toxicity such as in vitro pharmacological proling by using o-target screening panels [139].
4.6.2 Risdiplam Hit-to-Lead
SMA is a genetic disease caused by mutation or deletion of the survival motor neuron 1 (SMN1) gene and is a leading genetic cause of infant and toddler mortality [120b]. Survival motor neuron (SMN) protein is expressed in all body tissues and is essen­tial for development and functional homeostasis in many species [140]. In humans, SMN protein is produced by two genes: SMN1 and SMN2, although the latter gene produces low levels of full-length mRNA due to alternative splicing of exon 7. Nusin­ersen, an RNA antisense oligonucleotide, was the rst approved treatment for SMA and works by inhibiting a splicing silencer that allows for SMN2 exon 7 splicing, thus expressing SMN protein [141]. Although a breakthrough drug, nusinersen must be administered intrathecally, i.e. by injection in the cerebrospinal uid of the spine.
Risdiplam, an FDA approved oral small-molecule splice modulator of SMN2 exon 7, was discovered rst by using a high-throughput phenotypic screen designed to identify small-molecule compounds that increase the inclusion of exon 7 during SMN2 pre-mRNA splicing in an SMN2 minigene reporter assay (HEK293 cells) [120b]. Ratni and co-authors identied coumarin derivative R-1 as a promising hit (Figure 4.11). In parallel, SAR was started on both the coumarin and benzoxazole moieties of the molecule, along with scaold hopping around the coumarin core. Isocoumarin SMN-C1, coumarin SMN-C2, and pyridopyrimidinone SMN-C3 were
Et
N Et
SMN2 splicing EC
SMN protein EC
Figure 4.11 Initial coumarin hit R-1 and lead series containing a pyridopyrimidine core. Although potent, SMN-C1 and SMN-C2 possessed selectivity and chemical instability problems that the pyridopyrimidine core lead series did not have. The pyridopyrimidine series was further optimized to arrive at risdiplam, the first small molecule approved treatment for SMA that increases the inclusion of exon 7 during SMN2 pre-mRNA splicing.
N
Et
N
N
Me
SMN2 protein EC
Lead series:
Me
N
N
O
SMN-C3
Me
N
N
O
r-2
Me
N
Me
N
N
N
Me
N
Me
Phase I clinical trials
N
HN
Paused for renal toxicity in cynomolgus monkeys
Me
N
N
: 30 nM
1.5 x
: 84 nM
1.5 x
Me
N
N
O
RG7800
N
N
O
Risdiplam
Et
N
N
Me
N
N
N
Me
N
Me
Me
N
Me
N
N
O
N
O
O
O
r-1
: 0.22 µM
1.5 x
: > 10 µM
1.5 x
N
N
Me
SMN2 splicing EC
SMN protein EC
Me
N
N
Et
SMN2 splicing EC
SMN2 protein EC
- Ames positive
- Instability in plasma
O
SMN-C1
1.5 x
O
SMN-C2
- Phototoxicity
: 25 nM
1.5 x
: 120 nM
Me
N
Me
N
N
O
: 10 nM SMN2 splicing EC
1.5 x
: 44 nM
1.5 x
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identied as orally bioavailable and all three analogs modied SMN2 splicing in SMA patient-derived cells [142]. However, SMN-C1 and SMN-C2 exhibited Ames toxicity (genotoxicity), phototoxicity, and chemical instability in plasma and aqueous buers. Further optimization of these series resulted in either potent compounds that still exhibited Ames toxicity or compounds that were ineective in the in vitro SMN2 minigene reporter assay. Pyridopyrimidone core-containing compounds SMN-C3 and R-2 were free of the phototoxicity and plasma stability issues that halted progression of the SMN-C1 and ‘C2 series. Further optimization of the series brought forth candidate RG7800, which was tested in Phase I clinical trials for spinal SMA. However, due to observed renal toxicity in cynomolgus monkeys, researchers paused further clinical trials involving RG7800. From RG7800, Ratni and co-workers further optimized the series to improve selectivity vs. o-target genes as measured through transcriptome-wide RNA-seq using type 1 SMA patient broblasts [143] and improved on-target potency, thus allowing clinicians to lower the ecacious dose in patients.
4.6.3 Branaplam Lead Generation
Like risdiplam, researchers at Novartis performed an HTS to identify small-molecule modulators that increase the SMN2 exon 7 inclusion using an NSC34 motor neuron cell line expressing an SMN2 minigene reporter [144]. Primary hits were conrmed, and among those hits identied was pyridazine B-1 (Figure 4.12) which possessed SMN EC50of 600 nM (2.5 fold expression), but also suered from high in vivo clearance, low brain exposure, and potent hERG inhibition [120a].
Cheung and co-authors improved the SMN Elisa potency (SMN Δ7 mouse
myoblast assay) by replacing the benzothiophene with an ortho-phenol. Further,
S
SMN Elisa EC50: 600 nM, 2.5 fold
hERG IC50: 600 nM
S
SMN Elisa EC50: 1.1 µM, 2.4 fold
mouse CL: 100 ml/min/kg
hERG IC
Poor CNS exposure
Figure 4.12 Initial pyridazine hit B-1 and derivative B-2 were targeted as the lead series resulting in the discovery of branaplam.
N
N
N
B-1
N
B-2
50
H N
Me Me
Me N
Me Me
= 110 nM
NH
NH
Me
Me
Me
Me
Me
O
N
N
N HN
SMN Elisa EC50: 20 nM, 2.6 fold
oral BAV (mouse): 18%
OH
Branaplam
hERG IC50: 6 µM
NH
Me Me
Me
80 4 Screening and Lead Generation Techniques for RNA Binders
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Me
Me
N
HO
Me
O
Me
HO
O
O
Ph
O
Me
Me
O
HO
O
HO
N
Ph
O
Me
Me
N
O
Me
(–)-Rocaglamide A
Cell IC50: 20 nM
Poor physicochemical properties
Poor metabolic stability
Zotatifin
Cell IC50: 11 nM
>20 mg/ml aqueous solubility
CL (rat): 48 ml/min/kg
CN
Figure 4.13 Rocaglamide natural product lead series (represented by (—)-rocaglamide A) was optimized to zotatifin (eFT226), an inhibitor of RNA helicase eIF4A, currently in clinical trials for cancer and SARS-CoV-2.
researchers at Novartis reduced hERG inhibition by adding electron withdrawing polar groups on the western aromatic side of the molecule. Lastly, changing the N-methylamine linker (cf. compound B-2, Figure 4.12) to an oxygen led to branaplam, which exhibited improved brain exposure and ecacy in the SMN Δ7 mouse model. Currently, clinical trials with branaplam as treatments for both SMA and Huntington’s Disease are paused.
4.6.4 Zotatifin Lead Generation
(—)-Rocaglamide A and congeners, a class of natural products that inhibits protein synthesis by forming a stable ternary complex with polypurine-rich messenger RNAs and eIF4A [123b], have been shown to be potent antiproliferative and antivi­ral agents [145]. Researchers at eFFECTOR Therapeutics chose the rocaglamide scaold as a lead series to further optimize resulting in the discovery of zotatin, the rst eIF4A inhibitor tested in human clinical trials (Figure 4.13) [122]. To optimize rocaglamide A, Ernst and co-authors focused on improving the poor solubility and metabolic stability by exploring new ways to decrease the lipophilicity of the molecule. Ultimately, the molecule was made to be more polar and soluble through changing the western dimethoxy phenyl to dimethoxy pyridine and converting the amide to a basic N,N-dimethyl amine. Further, the p-methoxyphenyl was changed to a p-cyanophenyl to simultaneously improve potency and lower lipophilicity, which has been previously explored by other research groups [146]. Zotatin is currently in Phase II clinical trials for breast cancer and SARS-CoV-2.
4.7 Concluding Thoughts and Outlook
In this chapter, we outlined knowledge-based and agnostic screening approaches for the identication of RNA binders, including both virtual screening methods and high-throughput screening methods. Further, we have shown methods used to
References 81
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assess binding anity, binding site(s) of an RNA ligand, target engagement, and functional activity – all of which are necessary in generating lead RNA binders to progress for lead optimization and eventually clinical development. The future of RNA drug discovery is promising as we continue to develop methods for generating and optimizing RNA binders.
Acknowledgments
We would like to thank Joel Dufour, Scott Gorman, Sarah Mahoney, Anthony Mon­tibello, Herschel Mukherjee, Scott Rusin, and Yaqiang Wang for their suggestions and edits on various parts of the manuscript. We also want to thank Craig Blain, Nick Marsh, Lee Roberts, and Erik Spek for their review of the manuscript and sug­gested edits. Lastly, we would like to thank Nick Marsh and Lee Roberts for their guidance in organizing the manuscript.
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