Mono- and multimeric PSMA-targeting small molecule-thorium-227 conjugates for optimized efficacy and biodistribution in preclinical models.

PURPOSE: PSMA (prostate-specific membrane antigen) is highly expressed on prostate cancer (PrCa) cells and extensively used as a homing target for PrCa treatment. Most prominently, PSMA-targeting conjugate PSMA-617, carrying a DOTA chelator and labeled with therapeutic radionuclides like beta-emitting lutetium-177 or alpha-emitting actinium-225, has shown clinical activity in PrCa patients. We sought to develop PSMA-targeting small molecule (SMOL) conjugates that show high uptake in PSMA-expressing tumors and fast clearance, and can easily be labeled with the alpha emitter thorium-227 (half-life 18.7 days). METHODS: A novel linker motif with improved competition against 3H-PSMA-617 on PSMA-expressing LNCaP cells was identified. A 2,3-hydroxypyridinone chelator modified with carboxyl groups (carboxy-HOPO) with increased hydrophilicity and robust labeling with thorium-227 was developed and allowed the synthesis of mono-, di-, tri-, and tetrameric conjugates. The resulting monomeric and multimeric PSMA SMOL-TTCs (targeted thorium conjugate) were evaluated for cellular binding, internalization, and antiproliferative activity. The in vivo antitumor efficacy of the PSMA SMOL-TTCs was determined in ST1273 and KUCaP-1 PrCa models in mice, and their biodistribution was assessed in cynomolgus monkeys, minipigs, and mice. RESULTS: The monomeric and multimeric PSMA SMOL conjugates were readily labeled with thorium-227 at room temperature and possessed high stability and good binding, internalization, and antiproliferative activity in vitro. In vivo, the monomeric, dimeric, and trimeric PSMA SMOL-TTCs showed fast clearance, potent antitumor efficacy, and high uptake and retention in prostate tumors in mice. No major uptake or retention in other organs was observed beyond kidneys. Low uptake of free thorium-227 into bone confirmed high complex stability in vivo. Salivary gland uptake remained inconclusive as mini pigs were devalidated as a relevant model and imaging controls failed in cynomolgus monkeys. CONCLUSION: Monomeric and multimeric PSMA SMOL-TTCs show high tumor uptake and fast clearance in preclinical models and warrant further therapeutic exploration.

Full Modification Control over Retrosynthetic Routes for Guided Optimization of Lead Structures.

Synthesizability is essential for compounds designed in silico. Regardless, synthetic accessibility is often considered only as an afterthought in the design and optimization process. In addition, the trend with modern computer-aided drug design methods is going toward full automation and away from the possibility of incorporating user knowledge. With this work, we present the second major release of our software tool, Synthesia, for synthesis-aware lead structure modification, where the user's expertise is now fully utilized. A provided retrosynthetic route is used as a pathway to guide structural modifications that introduce desired structural changes in the target compound. Moreover, the approach allows the user to define the exact position or component in the retrosynthetic route, which should be modified, further integrating the user's expert knowledge. This paper describes the functionality of Synthesia, its basic concepts, and several application scenarios ranging from simple examples to a comparison of the effects of the different exchange functions to an analysis of a set of bioisosteric linker structures, highlighting potential synthetically feasible replacements.

Galileo: Three-dimensional searching in large combinatorial fragment spaces on the example of pharmacophores.

Fragment spaces are an efficient way to model large chemical spaces using a handful of small fragments and a few connection rules. The development of Enamine's REAL Space has shown that large spaces of readily available compounds may be created this way. These are several orders of magnitude larger than previous libraries. So far, searching and navigating these spaces is mostly limited to topological approaches. A way to overcome this limitation is optimization via metaheuristics which can be combined with arbitrary scoring functions. Here we present Galileo, a novel Genetic Algorithm to sample fragment spaces. We showcase Galileo in combination with a novel pharmacophore mapping approach, called Phariety, enabling 3D searches in fragment spaces. We estimate the effectiveness of the approach with a small fragment space. Furthermore, we apply Galileo to two pharmacophore searches in the REAL Space, detecting hundreds of compounds fulfilling a HSP90 and a FXIa pharmacophore.

Prioritizing Small Sets of Molecules for Synthesis through in-silico Tools: A Comparison of Common Ranking Methods.

Prioritizing molecules for synthesis is a key role of computational methods within medicinal chemistry. Multiple tools exist for ranking molecules, from the cheap and popular molecular docking methods to more computationally expensive molecular-dynamics (MD)-based methods. It is often questioned whether the accuracy of the more rigorous methods justifies the higher computational cost and associated calculation time. Here, we compared the performance on ranking the binding of small molecules for seven scoring functions from five docking programs, one end-point method (MM/GBSA), and two MD-based free energy methods (PMX, FEP+). We investigated 16 pharmaceutically relevant targets with a total of 423 known binders. The performance of docking methods for ligand ranking was strongly system dependent. We observed that MD-based methods predominantly outperformed docking algorithms and MM/GBSA calculations. Based on our results, we recommend the application of MD-based free energy methods for prioritization of molecules for synthesis in lead optimization, whenever feasible.

Visualizing Generic Reaction Patterns.

Reaction schemes for organic molecules play a crucial role in modern in silico drug design processes. In contrast to the classical drawn reaction diagrams, computational chemists prefer SMARTS based line notations due to a substantially increased expressiveness and precision. They are used to search databases, calculate synthesizability, generate new molecules, or simulate novel reactions. Working with computer-readable representations of reaction schemes can be challenging due to the complexity of the features to be represented. Line representations of reaction schemes can often be cryptic, even to experienced users. To simplify the work with Reaction SMARTS for synthetic, computational, and medicinal chemists, we introduce a visualization technique for reaction schemes and provide a respective tool, called ReactionViewer. ReactionViewer is able to convert reaction schemes encoded as Reaction SMILES, Reaction SMARTS, or SMIRKS into a visual representation. The visualization technique is based on the concept of structure diagrams and follows IUPAC's "Compendium of Chemical Terminology" definition of chemical reaction equations for the reaction symbols. We demonstrate the applicability of the method using two data sets of organic synthesis reaction schemes taken from recent publications. We discuss various properties of the visualization and highlight its readability and interpretability.

Synthesis-Aware Generation of Structural Analogues.

In modern drug design, one of the main issues is the optimization of an initial lead structure toward a drug candidate by modifying specific properties in the desired direction. The synthetic feasibility of the target structure is often neglected during this process, resulting in structures with low or suboptimal synthetic accessibility. In this work, we present a novel approach for synthesis-aware lead optimization called Synthesia. In contrast to the traditional approaches, Synthesia integrates the preservation of the synthesizability of the target structure into the lead structure modification process. Synthesia is able to create structural diversity for a lead structure that matches user-defined molecular properties without losing the applicability of a particular synthetic pathway. The methodology is validated by demonstrating that Synthesia is capable of providing structural analogues of DrugBank compounds that meet generic modification goals and maintain their synthetic pathways. In addition, Synthesia is used to cluster compounds from two different patent structure series (CDK7, Daurismo) according to their compatibility with the same synthetic pathways, maximizing the synthetic efficiency and providing an initial estimation of the effort of synthesizing the entire series. Altogether, we demonstrate Synthesia's ability to modify compound properties while maintaining in silico synthesizability.

BAY-8400: A Novel Potent and Selective DNA-PK Inhibitor which Shows Synergistic Efficacy in Combination with Targeted Alpha Therapies.

Eukaryotes have evolved two major pathways to repair potentially lethal DNA double-strand breaks. Homologous recombination represents a precise, DNA-template-based mechanism available during the S and G2 cell cycle phase, whereas non-homologous end joining, which requires DNA-dependent protein kinase (DNA-PK), allows for fast, cell cycle-independent but less accurate DNA repair. Here, we report the discovery of BAY-8400, a novel selective inhibitor of DNA-PK. Starting from a triazoloquinoxaline, which had been identified as a hit from a screen for ataxia telangiectasia and Rad3-related protein (ATR) inhibitors with inhibitory activity against ATR, ATM, and DNA-PK, lead optimization efforts focusing on potency and selectivity led to the discovery of BAY-8400. In in vitro studies, BAY-8400 showed synergistic activity of DNA-PK inhibition with DNA damage-inducing targeted alpha therapy. Combination of PSMA-targeted thorium-227 conjugate BAY 2315497 treatment of human prostate tumor-bearing mice with BAY-8400 oral treatment increased antitumor efficacy, as compared to PSMA-targeted thorium-227 conjugate monotherapy.

Changing for the Better: Discovery of the Highly Potent and Selective CDK9 Inhibitor VIP152 Suitable for Once Weekly Intravenous Dosing for the Treatment of Cancer.

Selective inhibition of exclusively transcription-regulating positive transcription elongation factor b/CDK9 is a promising new approach in cancer therapy. Starting from atuveciclib, the first selective CDK9 inhibitor to enter clinical development, lead optimization efforts aimed at identifying intravenously (iv) applicable CDK9 inhibitors with an improved therapeutic index led to the discovery of the highly potent and selective clinical candidate VIP152. The evaluation of various scaffold hops was instrumental in the identification of VIP152, which is characterized by the underexplored benzyl sulfoximine group. VIP152 exhibited the best preclinical overall profile in vitro and in vivo, including high efficacy and good tolerability in xenograft models in mice and rats upon once weekly iv administration. VIP152 has entered clinical trials for the treatment of cancer with promising longterm, durable monotherapy activity in double-hit diffuse large B-cell lymphoma patients.

The potent AMPK inhibitor BAY-3827 shows strong efficacy in androgen-dependent prostate cancer models.

PURPOSE: 5' adenosine monophosphate-activated kinase (AMPK) is an essential regulator of cellular energy homeostasis and has been associated with different pathologies, including cancer. Precisely defining the biological role of AMPK necessitates the availability of a potent and selective inhibitor. METHODS: High-throughput screening and chemical optimization were performed to identify a novel AMPK inhibitor. Cell proliferation and mechanistic assays, as well as gene expression analysis and chromatin immunoprecipitation were used to investigate the cellular impact as well as the crosstalk between lipid metabolism and androgen signaling in prostate cancer models. Also, fatty acid turnover was determined by examining lipid droplet formation. RESULTS: We identified BAY-3827 as a novel and potent AMPK inhibitor with additional activity against ribosomal 6 kinase (RSK) family members. It displays strong anti-proliferative effects in androgen-dependent prostate cancer cell lines. Analysis of genes involved in AMPK signaling revealed that the expression of those encoding 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), fatty acid synthase (FASN) and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 2 (PFKFB2), all of which are involved in lipid metabolism, was strongly upregulated by androgen in responsive models. Chromatin immunoprecipitation DNA-sequencing (ChIP-seq) analysis identified several androgen receptor (AR) binding peaks in the HMGCR and PFKFB2 genes. BAY-3827 strongly down-regulated the expression of lipase E (LIPE), cAMP-dependent protein kinase type II-beta regulatory subunit (PRKAR2B) and serine-threonine kinase AKT3 in responsive prostate cancer cell lines. Also, the expression of members of the carnitine palmitoyl-transferase 1 (CPT1) family was inhibited by BAY-3827, and this was paralleled by impaired lipid flux. CONCLUSIONS: The availability of the potent inhibitor BAY-3827 will contribute to a better understanding of the role of AMPK signaling in cancer, especially in prostate cancer.

Damage Incorporated: Discovery of the Potent, Highly Selective, Orally Available ATR Inhibitor BAY 1895344 with Favorable Pharmacokinetic Properties and Promising Efficacy in Monotherapy and in Combination Treatments in Preclinical Tumor Models.

The ATR kinase plays a key role in the DNA damage response by activating essential signaling pathways of DNA damage repair, especially in response to replication stress. Because DNA damage and replication stress are major sources of genomic instability, selective ATR inhibition has been recognized as a promising new approach in cancer therapy. We now report the identification and preclinical evaluation of the novel, clinical ATR inhibitor BAY 1895344. Starting from quinoline 2 with weak ATR inhibitory activity, lead optimization efforts focusing on potency, selectivity, and oral bioavailability led to the discovery of the potent, highly selective, orally available ATR inhibitor BAY 1895344, which exhibited strong monotherapy efficacy in cancer xenograft models that carry certain DNA damage repair deficiencies. Moreover, combination treatment of BAY 1895344 with certain DNA damage inducing chemotherapy resulted in synergistic antitumor activity. BAY 1895344 is currently under clinical investigation in patients with advanced solid tumors and lymphomas (NCT03188965).

Treating Cancer by Spindle Assembly Checkpoint Abrogation: Discovery of Two Clinical Candidates, BAY 1161909 and BAY 1217389, Targeting MPS1 Kinase.

Inhibition of monopolar spindle 1 (MPS1) kinase represents a novel approach to cancer treatment: instead of arresting the cell cycle in tumor cells, cells are driven into mitosis irrespective of DNA damage and unattached/misattached chromosomes, resulting in aneuploidy and cell death. Starting points for our optimization efforts with the goal to identify MPS1 inhibitors were two HTS hits from the distinct chemical series "triazolopyridines" and "imidazopyrazines". The major initial issue of the triazolopyridine series was the moderate potency of the HTS hits. The imidazopyrazine series displayed more than 10-fold higher potencies; however, in the early project phase, this series suffered from poor metabolic stability. Here, we outline the evolution of the two hit series to clinical candidates BAY 1161909 and BAY 1217389 and reveal how both clinical candidates bind to the ATP site of MPS1 kinase, while addressing different pockets utilizing different binding interactions, along with their synthesis and preclinical characterization in selected in vivo efficacy models.

Computationally Empowered Workflow Identifies Novel Covalent Allosteric Binders for KRASG12C.

Due to its frequent mutations in multiple lethal cancers, KRAS is one of the most-studied anticancer targets nowadays. Since the discovery of the druggable allosteric binding site containing a G12C mutation, KRASG12C has been the focus of attention in oncology research. We report here a computationally driven approach aimed at identifying novel and selective KRASG12C covalent inhibitors. The workflow involved initial enumeration of virtual molecules tailored for the KRAS allosteric binding site. Tools such as pharmacophore modeling, docking, and free-energy perturbations were deployed to prioritize the compounds with the best profiles. The synthesized naphthyridinone scaffold showed the ability to react with G12C and inhibit KRASG12C . Analogues were prepared to establish structure-activity relationships, while molecular dynamics simulations and crystallization of the inhibitor-KRASG12C complex highlighted an unprecedented binding mode.

Discovery of BAY-985, a Highly Selective TBK1/IKKε Inhibitor.

The serine/threonine kinase TBK1 (TANK-binding kinase 1) and its homologue IKKε are noncanonical members of the inhibitor of the nuclear factor κB (IκB) kinase family. These kinases play important roles in multiple cellular pathways and, in particular, in inflammation. Herein, we describe our investigations on a family of benzimidazoles and the identification of the potent and highly selective TBK1/IKKε inhibitor BAY-985. BAY-985 inhibits the cellular phosphorylation of interferon regulatory factor 3 and displays antiproliferative efficacy in the melanoma cell line SK-MEL-2 but showed only weak antitumor activity in the SK-MEL-2 human melanoma xenograft model.

Efficient multi-objective molecular optimization in a continuous latent space.

One of the main challenges in small molecule drug discovery is finding novel chemical compounds with desirable properties. In this work, we propose a novel method that combines in silico prediction of molecular properties such as biological activity or pharmacokinetics with an in silico optimization algorithm, namely Particle Swarm Optimization. Our method takes a starting compound as input and proposes new molecules with more desirable (predicted) properties. It navigates a machine-learned continuous representation of a drug-like chemical space guided by a defined objective function. The objective function combines multiple in silico prediction models, defined desirability ranges and substructure constraints. We demonstrate that our proposed method is able to consistently find more desirable molecules for the studied tasks in relatively short time. We hope that our method can support medicinal chemists in accelerating and improving the lead optimization process.

Discovery of potent SOS1 inhibitors that block RAS activation via disruption of the RAS-SOS1 interaction.

Since the late 1980s, mutations in the RAS genes have been recognized as major oncogenes with a high occurrence rate in human cancers. Such mutations reduce the ability of the small GTPase RAS to hydrolyze GTP, keeping this molecular switch in a constitutively active GTP-bound form that drives, unchecked, oncogenic downstream signaling. One strategy to reduce the levels of active RAS is to target guanine nucleotide exchange factors, which allow RAS to cycle from the inactive GDP-bound state to the active GTP-bound form. Here, we describe the identification of potent and cell-active small-molecule inhibitors which efficiently disrupt the interaction between KRAS and its exchange factor SOS1, a mode of action confirmed by a series of biophysical techniques. The binding sites, mode of action, and selectivity were elucidated using crystal structures of KRASG12C-SOS1, SOS1, and SOS2. By preventing formation of the KRAS-SOS1 complex, these inhibitors block reloading of KRAS with GTP, leading to antiproliferative activity. The final compound 23 (BAY-293) selectively inhibits the KRAS-SOS1 interaction with an IC50 of 21 nM and is a valuable chemical probe for future investigations.

Inhibition of BUB1 Kinase by BAY 1816032 Sensitizes Tumor Cells toward Taxanes, ATR, and PARP Inhibitors In Vitro and In Vivo.

PURPOSE: The catalytic function of BUB1 is required for chromosome arm resolution and positioning of the chromosomal passenger complex for resolution of spindle attachment errors and plays only a minor role in spindle assembly checkpoint activation. Here, we present the identification and preclinical pharmacologic profile of the first BUB1 kinase inhibitor with good bioavailability. EXPERIMENTAL DESIGN: The Bayer compound library was screened for BUB1 kinase inhibitors and medicinal chemistry efforts to improve target affinity and physicochemical and pharmacokinetic parameters resulting in the identification of BAY 1816032 were performed. BAY 1816032 was characterized for kinase selectivity, inhibition of BUB1 signaling, and inhibition of tumor cell proliferation alone and in combination with taxanes, ATR, and PARP inhibitors. Effects on tumor growth in vivo were evaluated using human triple-negative breast xenograft models. RESULTS: The highly selective compound BAY 1816032 showed long target residence time and induced chromosome mis-segregation upon combination with low concentrations of paclitaxel. It was synergistic or additive in combination with paclitaxel or docetaxel, as well as with ATR or PARP inhibitors in cellular assays. Tumor xenograft studies demonstrated a strong and statistically significant reduction of tumor size and excellent tolerability upon combination of BAY 1816032 with paclitaxel or olaparib as compared with the respective monotherapies. CONCLUSIONS: Our findings suggest clinical proof-of-concept studies evaluating BAY 1816032 in combination with taxanes or PARP inhibitors to enhance their efficacy and potentially overcome resistance.

An approach towards enhancement of a screening library: The Next Generation Library Initiative (NGLI) at Bayer - against all odds?

Pharmaceutical companies often refer to 'screening their library' when performing high-throughput screening (HTS) on a corporate compound collection to identify lead structures for small-molecule drug discovery programs. Characteristics of such a library, including the size, chemical space covered, and physicochemical properties, often determine the success of a screening campaign. Therefore, strategies to maintain and enhance the overall quality of screening collections are crucial to stay competitive and to cope with the 'novelty erosion' that is observed gradually. The Next Generation Library Initiative (NGLI), the enhancement of Bayer's HTS collection by 500000 newly designed compounds within 5 years, is addressing exactly this challenge. Here, we describe this collaborative project, which involves all internal medicinal chemists in a crowd-sourcing approach, as well as selected external partners, to reach this ambitious goal.

Binding Kinetics Survey of the Drugged Kinome.

Target residence time is emerging as an important optimization parameter in drug discovery, yet target and off-target engagement dynamics have not been clearly linked to the clinical performance of drugs. Here we developed high-throughput binding kinetics assays to characterize the interactions of 270 protein kinase inhibitors with 40 clinically relevant targets. Analysis of the results revealed that on-rates are better correlated with affinity than off-rates and that the fraction of slowly dissociating drug-target complexes increases from early/preclinical to late stage and FDA-approved compounds, suggesting distinct contributions by each parameter to clinical success. Combining binding parameters with PK/ADME properties, we illustrate in silico and in cells how kinetic selectivity could be exploited as an optimization strategy. Furthermore, using bio- and chemoinformatics we uncovered structural features influencing rate constants. Our results underscore the value of binding kinetics information in rational drug design and provide a resource for future studies on this subject.

Computational Macrocyclization: From de†novo Macrocycle Generation to Binding Affinity Estimation.

Macrocycles play an increasing role in drug discovery, but their synthesis is often demanding. Computational tools that suggest macrocyclization based on a known binding mode and that estimate the binding affinity of these macrocycles could have a substantial impact on the medicinal chemistry design process. For both tasks, we established a workflow with high practical value. For five diverse pharmaceutical targets we show that the effect of macrocyclization on binding can be calculated robustly and accurately. Applying this method to macrocycles designed by LigMac, a search tool for de novo macrocyclization, our results suggest that we have a robust protocol in hand to design macrocycles and prioritize them prior to synthesis.

Identification of Atuveciclib (BAY†1143572), the First Highly Selective, Clinical PTEFb/CDK9 Inhibitor for the Treatment of Cancer.

Selective inhibition of exclusively transcription-regulating PTEFb/CDK9 is a promising new approach in cancer therapy. Starting from lead compound BAY-958, lead optimization efforts strictly focusing on kinase selectivity, physicochemical and DMPK properties finally led to the identification of the orally available clinical candidate atuveciclib (BAY 1143572). Structurally characterized by an unusual benzyl sulfoximine group, BAY 1143572 exhibited the best overall profile in vitro and in vivo, including high efficacy and good tolerability in xenograft models in mice and rats. BAY 1143572 is the first potent and highly selective PTEFb/CDK9 inhibitor to enter clinical trials for the treatment of cancer.