Discovery of GNE-502 as an orally bioavailable and potent degrader for estrogen receptor positive breast cancer.

Fulvestrant is an FDA-approved drug with a dual mechanism of action (MOA), acting as a full antagonist and degrader of the estrogen receptor protein. A significant limitation of fulvestrant is the dosing regimen required for efficacy. Due to its high lipophilicity and poor pharmacokinetic profile, fulvestrant needs to be administered through intramuscular injections which leads to injection site soreness. This route of administration also limits the dose and target occupancy in patients. We envisioned a best-in-class molecule that would function with the same dual MOA as fulvestrant, but with improved physicochemical properties and would be orally bioavailable. Herein we report our progress toward that goal, resulting in a new lead GNE-502 which addressed some of the liabilities of our previously reported lead molecule GNE-149.

Mechanism-specific assay design facilitates the discovery of Nav1.7-selective inhibitors.

Many ion channels, including Nav1.7, Cav1.3, and Kv1.3, are linked to human pathologies and are important therapeutic targets. To develop efficacious and safe drugs, subtype-selective modulation is essential, but has been extremely difficult to achieve. We postulate that this challenge is caused by the poor assay design, and investigate the Nav1.7 membrane potential assay, one of the most extensively employed screening assays in modern drug discovery. The assay uses veratridine to activate channels, and compounds are identified based on the inhibition of veratridine-evoked activities. We show that this assay is biased toward nonselective pore blockers and fails to detect the most potent, selective voltage-sensing domain 4 (VSD4) blockers, including PF-05089771 (PF-771) and GX-936. By eliminating a key binding site for pore blockers and replacing veratridine with a VSD-4 binding activator, we directed the assay toward non-pore-blocking mechanisms and discovered Nav1.7-selective chemical scaffolds. Hence, we address a major hurdle in Nav1.7 drug discovery, and this mechanistic approach to assay design is applicable to Cav3.1, Kv1.3, and many other ion channels to facilitate drug discovery.

Discovery of a C-8 hydroxychromene as a potent degrader of estrogen receptor alpha with improved rat oral exposure over GDC-0927.

Phenolic groups are responsible for the high clearance and low oral bioavailability of the estrogen receptor alpha (ERα) clinical candidate GDC-0927. An exhaustive search for a backup molecule with improved pharmacokinetic (PK) properties identified several metabolically stable analogs, although in general at the expense of the desired potency and degradation efficiency. C-8 hydroxychromene 30 is the first example of a phenol-containing chromene that not only maintained excellent potency but also exhibited 10-fold higher oral exposure in rats. The improved in vivo clearance in rat was hypothesized to be the result of C-8 hydroxy group being sterically protected from glucuronide conjugation. The excellent potency underscores the possibility of replacing the presumed indispensable phenolic group at C-6 or C-7 of the chromene core. Co-crystal structures were obtained to highlight the change in key interactions and rationalize the retained potency.

Unexpected equivalent potency of a constrained chromene enantiomeric pair rationalized by co-crystal structures in complex with estrogen receptor alpha.

Despite tremendous progress made in the understanding of the ERα signaling pathway and the approval of many therapeutic agents, ER+ breast cancer continues to be a leading cause of cancer death in women. We set out to discover compounds with a dual mechanism of action in which they not only compete with estradiol for binding with ERα, but also can induce the degradation of the ERα protein itself. We were attracted to the constrained chromenes containing a tetracyclic benzopyranobenzoxepine scaffold, which were reported as potent selective estrogen receptor modulators (SERMs). Incorporation of a fluoromethyl azetidine side chain yielded highly potent and efficacious selective estrogen receptor degraders (SERDs), such as 16aa and surprisingly, also its enantiomeric pair 16ab. Co-crystal structures of the enantiomeric pair 16aa and 16ab in complex with ERα revealed default (mimics the A-D rings of endogenous ligand estradiol) and core-flipped binding modes, rationalizing the equivalent potency observed for these enantiomers in the ERα degradation and MCF-7 anti-proliferation assays.

cis-Selective synthesis of 1,3-disubstituted tetrahydro-ß-carbolines from N-sulfonyl N,S-acetals.

Nucleophilic addition of Grignard reagents to tetrahydro-ß-carboline (THC) N-sulfonyl N,S-acetal generates exclusively cis-1,3-disubstituted THCs with a unique 1,3-diaxial conformation. The stereochemical relationship of the 1,3-substituents was confirmed by 2-dimensional NMR spectroscopy and X-ray crystallography. The mechanism of the reaction is proposed based on crystal structures and molecular orbital calculations.

Water molecules in protein-ligand interfaces. Evaluation of software tools and SAR comparison.

Targeting the interaction with or displacement of the 'right' water molecule can significantly increase inhibitor potency in structure-guided drug design. Multiple computational approaches exist to predict which waters should be targeted for displacement to achieve the largest gain in potency. However, the relative success of different methods remains underexplored. Here, we present a comparison of the ability of five water prediction programs (3D-RISM, SZMAP, WaterFLAP, WaterRank, and WaterMap) to predict crystallographic water locations, calculate their binding free energies, and to relate differences in these energies to observed changes in potency. The structural cohort included nine Bruton's Tyrosine Kinase (BTK) structures, and nine bromodomain structures. Each program accurately predicted the locations of most crystallographic water molecules. However, the predicted binding free energies correlated poorly with the observed changes in inhibitor potency when solvent atoms were displaced by chemical changes in closely related compounds.

From a novel HTS hit to potent, selective, and orally bioavailable KDM5 inhibitors.

A high-throughput screening (HTS) of the Genentech/Roche library identified a novel, uncharged scaffold as a KDM5A inhibitor. Lacking insight into the binding mode, initial attempts to improve inhibitor potency failed to improve potency, and synthesis of analogs was further hampered by the presence of a C-C bond between the pyrrolidine and pyridine. Replacing this with a C-N bond significantly simplified synthesis, yielding pyrazole analog 35, of which we obtained a co-crystal structure with KDM5A. Using structure-based design approach, we identified 50 with improved biochemical, cell potency and reduced MW and lower lipophilicity (LogD) compared with the original hit. Furthermore, 50 showed lower clearance than 9 in mice. In combination with its remarkably low plasma protein binding (PPB) in mice (40%), oral dosing of 50 at 5mg/kg resulted in unbound Cmax ∼2-fold of its cell potency (PC9 H3K4Me3 0.96µM), meeting our criteria for an in vivo tool compound from a new scaffold.

Enabling drug discovery project decisions with integrated computational chemistry and informatics.

Computational chemistry/informatics scientists and software engineers in Genentech Small Molecule Drug Discovery collaborate with experimental scientists in a therapeutic project-centric environment. Our mission is to enable and improve pre-clinical drug discovery design and decisions. Our goal is to deliver timely data, analysis, and modeling to our therapeutic project teams using best-in-class software tools. We describe our strategy, the organization of our group, and our approaches to reach this goal. We conclude with a summary of the interdisciplinary skills required for computational scientists and recommendations for their training.

Lead optimization of a pyrazolo[1,5-a]pyrimidin-7(4H)-one scaffold to identify potent, selective and orally bioavailable KDM5 inhibitors suitable for in vivo biological studies.

Starting with a lead [1,5-a]pyrimidin-7(4H)-one-containing molecule (1), we generated potent, selective and orally bioavailable KDM5 inhibitors. Using structure- and property-based approaches, we designed 48 with improved cell potency (PC9 H3K4Me3 EC50=0.34µM). Furthermore, 48 maintained suitable physiochemical properties and displayed an excellent pharmacokinetic (PK) profile in mice. When dosed orally in mice at 50mg/kg twice a day (BID), 48 showed an unbound maximal plasma concentration (Cmax) >15-fold over its cell EC50, thereby providing a robust chemical probe for studying KDM5 biological functions in vivo.

Design and evaluation of 1,7-naphthyridones as novel KDM5 inhibitors.

Features from a high throughput screening (HTS) hit and a previously reported scaffold were combined to generate 1,7-naphthyridones as novel KDM5 enzyme inhibitors with nanomolar potencies. These molecules exhibited high selectivity over the related KDM4C and KDM2B isoforms. An X-ray co-crystal structure of a representative molecule bound to KDM5A showed that these inhibitors are competitive with the co-substrate (2-oxoglutarate or 2-OG).

Discovery of highly potent and selective Bruton's tyrosine kinase inhibitors: Pyridazinone analogs with improved metabolic stability.

BTK inhibitor GDC-0834 (1) was found to be rapidly metabolized in human studies, resulting in a suspension of clinical trials. The primary route of metabolism was through cleavage of the acyclic amide bond connecting the terminal tetrahydrobenzothiophene with the central linker aryl ring. SAR studies were focused on reducing metabolic cleavage of this amide, and resulted in the identification of several central aryl linker substituents that conferred improved stability. The most promising substituted aryl linkers were then incorporated into an optimized pyridazinone scaffold, resulting in the identification of lead analog 23, possessing improved potency, metabolic stability and preclinical properties.

Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge.

Small molecule distribution coefficients between immiscible nonaqueuous and aqueous phases-such as cyclohexane and water-measure the degree to which small molecules prefer one phase over another at a given pH. As distribution coefficients capture both thermodynamic effects (the free energy of transfer between phases) and chemical effects (protonation state and tautomer effects in aqueous solution), they provide an exacting test of the thermodynamic and chemical accuracy of physical models without the long correlation times inherent to the prediction of more complex properties of relevance to drug discovery, such as protein-ligand binding affinities. For the SAMPL5 challenge, we carried out a blind prediction exercise in which participants were tasked with the prediction of distribution coefficients to assess its potential as a new route for the evaluation and systematic improvement of predictive physical models. These measurements are typically performed for octanol-water, but we opted to utilize cyclohexane for the nonpolar phase. Cyclohexane was suggested to avoid issues with the high water content and persistent heterogeneous structure of water-saturated octanol phases, since it has greatly reduced water content and a homogeneous liquid structure. Using a modified shake-flask LC-MS/MS protocol, we collected cyclohexane/water distribution coefficients for a set of 53 druglike compounds at pH 7.4. These measurements were used as the basis for the SAMPL5 Distribution Coefficient Challenge, where 18 research groups predicted these measurements before the experimental values reported here were released. In this work, we describe the experimental protocol we utilized for measurement of cyclohexane-water distribution coefficients, report the measured data, propose a new bootstrap-based data analysis procedure to incorporate multiple sources of experimental error, and provide insights to help guide future iterations of this valuable exercise in predictive modeling.

Potent and selective Bruton's tyrosine kinase inhibitors: discovery of GDC-0834.

SAR studies focused on improving the pharmacokinetic (PK) properties of the previously reported potent and selective Btk inhibitor CGI-1746 (1) resulted in the clinical candidate GDC-0834 (2), which retained the potency and selectivity of CGI-1746, but with much improved PK in preclinical animal models. Structure based design efforts drove this work as modifications to 1 were investigated at both the solvent exposed region as well as 'H3 binding pocket'. However, in vitro metabolic evaluation of 2 revealed a non CYP-mediated metabolic process that was more prevalent in human than preclinical species (mouse, rat, dog, cyno), leading to a high-level of uncertainly in predicting human pharmacokinetics. Due to its promising potency, selectivity, and preclinical efficacy, a single dose IND was filed and 2 was taken in to a single dose phase I trial in healthy volunteers to quickly evaluate the human pharmacokinetics. In human, 2 was found to be highly labile at the exo-cyclic amide bond that links the tetrahydrobenzothiophene moiety to the central aniline ring, resulting in insufficient parent drug exposure. This information informed the back-up program and discovery of improved inhibitors.

A probabilistic method to report predictions from a human liver microsomes stability QSAR model: a practical tool for drug discovery.

Using data from the in vitro liver microsomes metabolic stability assay, we have developed QSAR models to predict in vitro human clearance. Models were trained using in house high-throughput assay data reported as the predicted human hepatic clearance by liver microsomes or pCLh. Machine learning regression methods were used to generate the models. Model output for a given molecule was reported as its probability of being metabolically stable, thus allowing for synthesis prioritization based on this prediction. Use of probability, instead of the regression value or categories, has been found to be an efficient way for both reporting and assessing predictions. Model performance is evaluated using prospective validation. These models have been integrated into a number of desktop tools, and the models are routinely used to prioritize the synthesis of compounds. We discuss two therapeutic projects at Genentech that exemplify the benefits of a probabilistic approach in applying the models. A three-year retrospective analysis of measured liver microsomes stability data on all registered compounds at Genentech reveals that the use of these models has resulted in an improved metabolic stability profile of synthesized compounds.

An integrated suite of modeling tools that empower scientists in structure- and property-based drug design.

Structure- and property-based drug design is an integral part of modern drug discovery, enabling the design of compounds aimed at improving potency and selectivity. However, building molecules using desktop modeling tools can easily lead to poor designs that appear to form many favorable interactions with the protein's active site. Although a proposed molecule looks good on screen and appears to fit into the protein site X-ray crystal structure or pharmacophore model, doing so might require a high-energy small molecule conformation, which would likely be inactive. To help scientists make better design decisions, we have built integrated, easy-to-use, interactive software tools to perform docking experiments, de novo design, shape and pharmacophore based database searches, small molecule conformational analysis and molecular property calculations. Using a combination of these tools helps scientists in assessing the likelihood that a designed molecule will be active and have desirable drug metabolism and pharmacokinetic properties. Small molecule discovery success requires project teams to rapidly design and synthesize potent molecules with good ADME properties. Empowering scientists to evaluate ideas quickly and make better design decisions with easy-to-access and easy-to-understand software on their desktop is now a key part of our discovery process.

Histone deacetylase (HDAC) inhibitor kinetic rate constants correlate with cellular histone acetylation but not transcription and cell viability.

Histone deacetylases (HDACs) are critical in the control of gene expression, and dysregulation of their activity has been implicated in a broad range of diseases, including cancer, cardiovascular, and neurological diseases. HDAC inhibitors (HDACi) employing different zinc chelating functionalities such as hydroxamic acids and benzamides have shown promising results in cancer therapy. Although it has also been suggested that HDACi with increased isozyme selectivity and potency may broaden their clinical utility and minimize side effects, the translation of this idea to the clinic remains to be investigated. Moreover, a detailed understanding of how HDACi with different pharmacological properties affect biological functions in vitro and in vivo is still missing. Here, we show that a panel of benzamide-containing HDACi are slow tight-binding inhibitors with long residence times unlike the hydroxamate-containing HDACi vorinostat and trichostatin-A. Characterization of changes in H2BK5 and H4K14 acetylation following HDACi treatment in the neuroblastoma cell line SH-SY5Y revealed that the timing and magnitude of histone acetylation mirrored both the association and dissociation kinetic rates of the inhibitors. In contrast, cell viability and microarray gene expression analysis indicated that cell death induction and changes in transcriptional regulation do not correlate with the dissociation kinetic rates of the HDACi. Therefore, our study suggests that determining how the selective and kinetic inhibition properties of HDACi affect cell function will help to evaluate their therapeutic utility.

Discovery and optimization of indazoles as potent and selective interleukin-2 inducible T cell kinase (ITK) inhibitors.

There is evidence that small molecule inhibitors of the non-receptor tyrosine kinase ITK, a component of the T-cell receptor signaling cascade, could represent a novel asthma therapeutic class. Moreover, given the expected chronic dosing regimen of any asthma treatment, highly selective as well as potent inhibitors would be strongly preferred in any potential therapeutic. Here we report hit-to-lead optimization of a series of indazoles that demonstrate sub-nanomolar inhibitory potency against ITK with strong cellular activity and good kinase selectivity. We also elucidate the binding mode of these inhibitors by solving the X-ray crystal structures of the complexes.

Design, synthesis and structure-activity relationships of a novel class of sulfonylpyridine inhibitors of Interleukin-2 inducible T-cell kinase (ITK).

Starting from benzylpyrimidine 2, molecular modeling and X-ray crystallography were used to design highly potent inhibitors of Interleukin-2 inducible T-cell kinase (ITK). Sulfonylpyridine 4i showed sub-nanomolar affinity against ITK, was selective versus Lck and its activity in the Jurkat cell-based assay was greatly improved over 2.

Physicochemical and DMPK in silico models: facilitating their use by medicinal chemists.

It is known that the developability of drugs is related to their physicochemical and DMPK properties. Given the time and expense involved in discovering and developing new drugs, maximizing the chance of success by calculating properties ahead of chemical synthesis and testing, and only acting on those candidates whose properties fall into a desired range, would seem to make sense. This paper provides an overview of calculable physicochemical and DMPK properties, an assessment of their relative difficulty of their calculation and accuracy, and available software. Methods companies have employed to communicate results will be discussed, including the use of composite scoring functions and ranking schemes. Calculations do no good if chemists will not use them to prioritize synthesis decisions. Strategies are presented for facilitating model usage. An approach adopted at Genentech for presenting results that involves the close coupling of property calculations with 3D structure based drug design is described.

A hit to lead discovery of novel N-methylated imidazolo-, pyrrolo-, and pyrazolo-pyrimidines as potent and selective mTOR inhibitors.

A series of N-7-methyl-imidazolopyrimidine inhibitors of the mTOR kinase have been designed and prepared, based on the hypothesis that the N-7-methyl substituent on imidazolopyrimidine would impart selectivity for mTOR over the related PI3Kα and δ kinases. The corresponding N-Me substituted pyrrolo[3,2-d]pyrimidines and pyrazolo[4,3-d]pyrimidines also show potent mTOR inhibition with selectivity toward both PI3α and δ kinases. The most potent compound synthesized is pyrazolo[4,3-d]pyrimidine 21c. Compound 21c shows a Ki of 2 nM against mTOR inhibition, remarkable selectivity (>2900×) over PI3 kinases, and excellent potency in cell-based assays.