Enhancing Drug Discovery and Development through the Integration of Medicinal Chemistry, Chemical Biology, and Academia-Industry Partnerships: Insights from Roche's Endocannabinoid System Projects.

The endocannabinoid system (ECS) is a critical regulatory network composed of endogenous cannabinoids (eCBs), their synthesizing and degrading enzymes, and associated receptors. It is integral to maintaining homeostasis and orchestrating key functions within the central nervous and immune systems. Given its therapeutic significance, we have launched a series of drug discovery endeavors aimed at ECS targets, including peroxisome proliferator-activated receptors (PPARs), cannabinoid receptors types 1 (CB1R) and 2 (CB2R), and monoacylglycerol lipase (MAGL), addressing a wide array of medical needs. The pursuit of new therapeutic agents has been enhanced by the creation of specialized labeled chemical probes, which aid in target localization, mechanistic studies, assay development, and the establishment of biomarkers for target engagement. By fusing medicinal chemistry with chemical biology in a comprehensive, translational end-to-end drug discovery strategy, we have expedited the development of novel therapeutics. Additionally, this strategy promises to foster highly productive partnerships between industry and academia, as will be illustrated through various examples.

sp3 -Rich Heterocycle Synthesis on DNA: Application to DNA-Encoded Library Production.

DNA encoded library (DEL) synthesis represents a convenient means to produce, annotate and store large collections of compounds in a small volume. While DELs are well suited for drug discovery campaigns, the chemistry used in their production must be compatible with the DNA tag, which can limit compound class accessibility. As a result, most DELs are heavily populated with peptidomimetic and sp2 -rich molecules. Herein, we show that sp3 -rich mono- and bicyclic heterocycles can be made on DNA from ketochlorohydrin aldol products through a reductive amination and cyclization process. The resulting hydroxypyrrolidines possess structural features that are desirable for DELs and target a distinct region of pharmaceutically relevant chemical space.

Diligent Design Enables Antibody-ASO Conjugates with Optimal Pharmacokinetic Properties.

Antisense-oligonucleotides (ASOs) are a promising drug modality for the treatment of neurological disorders, but the currently established route of administration via intrathecal delivery is a major limitation to its broader clinical application. An attractive alternative is the conjugation of the ASO to an antibody that facilitates access to the central nervous system (CNS) after peripheral application and target engagement at the blood-brain barrier, followed by transcytosis. Here, we show that the diligent conjugate design of Brainshuttle-ASO conjugates is the key to generating promising delivery vehicles and thereby establishing design principles to create optimized molecules with drug-like properties. An innovative site-specific transglutaminase-based conjugation technology was chosen and optimized in a stepwise process to identify the best-suited conjugation site, tags, reaction conditions, and linker design. The overall conjugation performance was found to be specifically governed by the choice of buffer conditions and the structure of the linker. The combination of the peptide tags YRYRQ and RYESK was chosen, showing high conjugation fidelity. Elaborate conjugate analysis revealed that one leading differentiating factor was hydrophobicity. The increase of hydrophobicity by the ASO payload could be mitigated by the appropriate choice of conjugation site and the heavy chain position 297 proved to be the most optimal. Evaluating the properties of the linker suggested a short bicyclo[6.1.0]nonyne (BCN) unit as best suited with regards to conjugation performance and potency. Promising in vitro activity and in vivo pharmacokinetic behavior of optimized Brainshuttle-ASO conjugates, based on a microtubule-associated protein tau (MAPT) targeting oligonucleotide, suggest that such designs have the potential to serve as a blueprint for peripherally delivered ASO-based drugs for the CNS in the future.

Rapid 18 F- and 19 F-Difluoromethylation through Desulfurative Fluorination of Transient N-, O-, and C-Linked Dithioles.

The difluoromethyl group plays an important role in modern medicinal and agrochemistry. While several difluoromethylation reagents have been reported, these typically rely on difluoromethyl carbenes or anions, or target specific processes. Here, we describe a conceptually unique and general process for O-H, N-H and C-H difluoromethylation that involves the formation of a transient dithiole followed by facile desulfurative fluorination using silver(I) fluoride. We also introduce the 5,6-dimethoxy-1,3-benzodithiole (DMBDT) function, which undergoes sufficiently rapid desulfurative fluorination to additionally support 18 F-difluoromethylation. This new process is compatible with the wide range of functional groups typically encountered in medicinal chemistry campaigns, and the use of Ag18 F is demonstrated in the production of 18 F-labeled derivatives of testosterone, perphenazine, and melatonin, 58.0±2.2, 20.4±0.3 and 32.2±3.6 MBq µmol-1 , respectively. We expect that the DMBDT group and this 18 F/19 F-difluoromethylation process will inspire and support new efforts in medicinal chemistry, agrochemistry and radiotracer production.

Investigations into mRNA Lipid Nanoparticles Shelf-Life Stability under Nonfrozen Conditions.

mRNA LNPs can experience a decline in activity over short periods (ranging from weeks to months). As a result, they require frozen storage and transportation conditions to maintain their full functionality when utilized. Currently approved commercially available mRNA LNP vaccines also necessitate frozen storage and supply chain management. Overcoming this significant inconvenience in the future is crucial to reducing unnecessary costs and challenges associated with storage and transport. In this study, our objective was to illuminate the potential time frame for nonfrozen storage and transportation conditions of mRNA LNPs without compromising their activity. To achieve this goal, we conducted a stability assessment and an in vitro cell culture delivery study involving five mRNA LNPs. These LNPs were constructed by using a standard formulation similar to that employed in the three commercially available LNP formulations. Among these formulations, we selected five structurally diverse ionizable lipids─C12-200, CKK-E12, MC3, SM-102, and lipid 23─from the existing literature. We incorporated these lipids into a standard LNP formulation, keeping all other components identical. The LNPs, carrying mRNA payloads, were synthesized by using microfluidic mixing technology. We evaluated the shelf life stability of these LNPs over a span of 9 weeks at temperatures of 2-8, 25, and 40 °C, utilizing an array of analytical techniques. Our findings indicated minimal impact on the hydrodynamic diameter, zeta potential, encapsulation efficiency, and polydispersity of all LNPs across the various temperatures over the studied period. The RiboGreen assay analysis of LNPs showed consistent mRNA contents over several weeks at various nonfrozen storage temperatures, leading to the incorrect assumption of intact and functional LNPs. This misunderstanding was rectified by the significant differences observed in EGFP protein expression in an in vitro cell culture (using HEK293 cells) across the five LNPs. Specifically, only LNP 1 (C12-200) and LNP 4 (SM-102) exhibited high levels of EGFP expression at the start (T0), with over 90% of HEK293 cells transfected and mean fluorescence intensity (MFI) levels exceeding 1. Interestingly, LNP 1 (C12-200) maintained largely unchanged levels of in vitro activity over 11 weeks when stored at both 2-8 and 25 °C. In contrast, LNP 4 (SM-102) retained its functionality when stored at 2-8 °C over 11 weeks but experienced a gradual decline of in vitro activity when stored at room temperature over the same period. Importantly, we observed distinct LNP architectures for the five formulations through cryo-EM imaging. This highlights the necessity for a deeper comprehension of structure-activity relationships within these complex nanoparticle structures. Enhancing our understanding in this regard is vital for overcoming storage and stability limitations, ultimately facilitating the broader application of this technology beyond vaccines.

Modulation of Pharmacologically Relevant Properties of Piperidine Derivatives by Functional Groups in an Equatorial or Axial ß-Position to the Amino Group.

Thirteen epimeric pairs of 5-substituted N-piperonyl-3-phenylpiperidine derivatives were synthesized in order to explore the stereospecific modulation of basicity, lipophilicity, aqueous solubility, and membrane permeation by functional groups in equatorial or axial positions beta to the amine unit. While this comprehensive data set provides enhanced insight into multiple factors that affect basicity and lipophilicity, it fills an important knowledge gap, providing a frame of reference for the property-based design of bioactive compounds. Impacts on amine basicity are very pronounced for the ß-equatorial functional groups and parallel basicity-lowering effects known for acyclic amine derivatives. For ß-axial functional groups, the basicity-lowering effects are generally decreased, with the nitrile group as the only exception. Basicity and lipophilicity modulations observed for ß-axial functional groups are quite diverse and rationalized in terms of intramolecular hydrogen bonding, dipolar interactions, and special solvation effects. Aqueous solubility and (artificial) membrane permeability are discussed with reference to lipophilicity.

Paracrine crosstalk between intestinal L- and D-cells controls secretion of glucagon-like peptide-1 in mice.

DPP-4 inhibitors, used for treatment of type 2 diabetes, act by increasing the concentrations of intact glucagon-like peptide-1 (GLP-1), but at the same time, they inhibit secretion of GLP-1, perhaps by a negative feedback mechanism. We hypothesized that GLP-1 secretion is feedback regulated by somatostatin (SS) from neighboring D-cells, and blocking this feedback circuit results in increased GLP-1 secretion. We used a wide range of experimental techniques, including gene expression analysis, immunohistochemical approaches, and the perfused mouse intestine to characterize the paracrine circuit controlling GLP-1 and SS. We show that 1) antagonizing the SS receptor (SSTr) 2 and SSTr5 led to increased GLP-1 and SS secretion in the mouse, 2) SS exhibits strong tonic inhibition of GLP-1 secretion preferentially through SSTr5, and 3) the secretion of S was GLP-1 receptor dependent. We conclude that SS is a tonic inhibitor of GLP-1 secretion, and interventions in the somatostain-GLP-1 paracrine loop lead to increased GLP-1 secretion.

A Convenient Synthesis of Difluoroalkyl Ethers from Thionoesters Using Silver(I) Fluoride.

Herein we report the mild and rapid fluorodesulfurization of thionoesters using only silver(I) fluoride. This reaction demonstrates excellent functional group tolerance and complements existing strategies for difluoroalkyl ether synthesis, which rely on toxic and often dangerous reagents that demonstrate limited functional group compatibility. We additionally report the translation of this finding to the production of 18 F-labelled difluoroalkyl ethers using fluoride-derived [18 F]AgF. This new process should enable the synthesis of a wide range of difluoroalkyl ethers with applications in medicinal and materials chemistry, and radiotracer production.

Site-Selective, Late-Stage C-H 18 F-Fluorination on Unprotected Peptides for Positron Emission Tomography Imaging.

Peptides are often ideal ligands for diagnostic molecular imaging due to their ease of synthesis and tuneable targeting properties. However, labelling unmodified peptides with 18 F for positron emission tomography (PET) imaging presents a number of challenges. Here we show the combination of photoactivated sodium decatungstate and [18 F]-N-fluorobenzenesulfonimide effects site-selective 18 F-fluorination at the branched position in leucine residues in unprotected and unaltered peptides. This streamlined process provides a means to directly convert native peptides into PET imaging agents under mild aqueous conditions, enabling rapid discovery and development of peptide-based molecular imaging tools.

18F-Fluorination of Unactivated C-H Bonds in Branched Aliphatic Amino Acids: Direct Synthesis of Oncological Positron Emission Tomography Imaging Agents.

A mild and selective photocatalytic C-H 18F-fluorination reaction has been developed that provides direct access to 18F-fluorinated amino acids. The biodistribution and uptake of three 18F-labeled leucine analogues via LAT1 mediated transport in several cancer cell lines is reported. Positron emission tomography imaging of mice bearing PC3 (prostate) or U87 (glioma) xenografts using 5-[18F]-fluorohomoleucine showed high tumor uptake and excellent tumor visualization, highlighting the utility of this strategy for rapid tracer discovery for oncology.

Intramolecular Inverse Electron-Demand [4 + 2] Cycloadditions of Ynamides with Pyrimidines: Scope and Density Functional Theory Insights.

4-Aminopyridines are valuable scaffolds for the chemical industry in general, from life sciences to catalysis. We report herein a collection of structurally diverse polycyclic fused and spiro-4-aminopyridines that are prepared in only three steps from commercially available pyrimidines. The key step of this short sequence is a [4 + 2]/retro-[4 + 2] cycloaddition between a pyrimidine and an ynamide, which constitutes the first examples of ynamides behaving as electron-rich dienophiles in [4 + 2] cycloaddition reactions. In addition, running the ihDA/rDA reaction in continuous mode in superheated toluene, to overcome the limited scalability of MW reactions, results in a notable production increase compared to batch mode. Finally, density functional theory investigations shed light on the energetic and geometric requirements of the different steps of the ihDA/rDA sequence.

Synthesis of annulated pyridines as inhibitors of aldosterone synthase (CYP11B2).

A series of cyclopenta[c]pyridine aldosterone synthase (AS) inhibitors were conveniently accessed using batch or continuous flow Kondrat'eva reactions. Preparation of the analogous cyclohexa[c]pyridines led to the identification of a potent and more selective AS inhibitor. The structure-activity-relationship (SAR) in this new series was rationalized using binding mode models in the crystal structure of AS.

A Convenient Late-Stage Fluorination of Pyridylic C-H Bonds with N-Fluorobenzenesulfonimide.

Pyridine features prominently in pharmaceuticals and drug leads, and methods to selectively manipulate pyridine basicity or metabolic stability are highly sought after. A robust, metal-free direct fluorination of unactivated pyridylic C-H bonds was developed. This convenient reaction shows high functional-group tolerance and offers complimentary selectivity to existing C-H fluorination strategies. Importantly, this late-stage pyridylic C-H fluorination provides opportunities to rationally modulate the basicity, lipophilicity, and metabolic stability of alkylpyridine drugs.

A convenient photocatalytic fluorination of unactivated C-H bonds.

Fluorination reactions are essential to modern medicinal chemistry, thus providing a means to block site-selective metabolic degradation of drugs and access radiotracers for positron emission tomography imaging. Despite current sophistication in fluorination reagents and processes, the fluorination of unactivated CH bonds remains a significant challenge. Reported herein is a convenient and economic process for direct fluorination of unactivated CH bonds that exploits the hydrogen abstracting ability of a decatungstate photocatalyst in combination with the mild fluorine atom transfer reagent N-fluorobenzenesulfonimide. This operationally straightforward reaction provides direct access to a wide range of fluorinated organic molecules, including structurally complex natural products, acyl fluorides, and fluorinated amino acid derivatives.

Seamless integration of dose-response screening and flow chemistry: efficient generation of structure-activity relationship data of ß-secretase (BACE1) inhibitors.

Drug discovery is a multifaceted endeavor encompassing as its core element the generation of structure-activity relationship (SAR) data by repeated chemical synthesis and biological testing of tailored molecules. Herein, we report on the development of a flow-based biochemical assay and its seamless integration into a fully automated system comprising flow chemical synthesis, purification and in-line quantification of compound concentration. This novel synthesis-screening platform enables to obtain SAR data on b-secretase (BACE1) inhibitors at an unprecedented cycle time of only 1 h instead of several days. Full integration and automation of industrial processes have always led to productivity gains and cost reductions, and this work demonstrates how applying these concepts to SAR generation may lead to a more efficient drug discovery process.

Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry.

Suzuki cross-coupling reactions are considered a valuable tool for constructing carbon-carbon bonds in small molecule drug discovery. However, the synthesis of chemical matter often represents a time-consuming and labour-intensive bottleneck. We demonstrate how machine learning methods trained on high-throughput experimentation (HTE) data can be leveraged to enable fast reaction condition selection for novel coupling partners. We show that the trained models support chemists in determining suitable catalyst-solvent-base combinations for individual transformations including an evaluation of the need for HTE screening. We introduce an algorithm for designing 96-well plates optimized towards reaction yields and discuss the model performance of zero- and few-shot machine learning. The best-performing machine learning model achieved a three-category classification accuracy of 76.3% (±0.2%) and an F 1-score for a binary classification of 79.1% (±0.9%). Validation on eight reactions revealed a receiver operating characteristic (ROC) curve (AUC) value of 0.82 (±0.07) for few-shot machine learning. On the other hand, zero-shot machine learning models achieved a mean ROC-AUC value of 0.63 (±0.16). This study positively advocates the application of few-shot machine learning-guided reaction condition selection for HTE campaigns in medicinal chemistry and highlights practical applications as well as challenges associated with zero-shot machine learning.

Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning.

Late-stage functionalization is an economical approach to optimize the properties of drug candidates. However, the chemical complexity of drug molecules often makes late-stage diversification challenging. To address this problem, a late-stage functionalization platform based on geometric deep learning and high-throughput reaction screening was developed. Considering borylation as a critical step in late-stage functionalization, the computational model predicted reaction yields for diverse reaction conditions with a mean absolute error margin of 4-5%, while the reactivity of novel reactions with known and unknown substrates was classified with a balanced accuracy of 92% and 67%, respectively. The regioselectivity of the major products was accurately captured with a classifier F-score of 67%. When applied to 23 diverse commercial drug molecules, the platform successfully identified numerous opportunities for structural diversification. The influence of steric and electronic information on model performance was quantified, and a comprehensive simple user-friendly reaction format was introduced that proved to be a key enabler for seamlessly integrating deep learning and high-throughput experimentation for late-stage functionalization.

RG7774 (Vicasinabin), an orally bioavailable cannabinoid receptor 2 (CB2R) agonist, decreases retinal vascular permeability, leukocyte adhesion, and ocular inflammation in animal models.

Introduction: Preclinical studies suggest that cannabinoid receptor type 2 (CB2R) activation has a therapeutic effect in animal models on chronic inflammation and vascular permeability, which are key pathological features of diabetic retinopathy (DR). A novel CB2R agonist, triazolopyrimidine RG7774, was generated through lead optimization of a high-throughput screening hit. The aim of this study was to characterize the pharmacology, absorption, distribution, metabolism, elimination, and toxicity (ADMET) profile of RG7774, and to explore its potential for managing the key pathological features associated with retinal disease in rodents. Methods: The in vitro pharmacology of RG7774 was investigated for CB2R binding and receptor activation using recombinant human and mouse CB2R expression in Chinese hamster ovary cells, and endogenous CB2R expression in human Jurkat cells, and rat and mouse spleen cells. The ADMET profile was evaluated and the effects of RG7774 on retinal permeability, leukocyte adhesion, and choroidal neovascularization (CNV) were investigated in rodent models of retinal disease. Pharmacokinetic (PK) parameters and the exposure-response relationship were characterized in healthy animals and in animals with laser-induced CNV. Results: RG7774 was found to be a potent (EC50: 2.8 nM and Ki: 51.3 nM), selective, and full CB2R agonist with no signs of cannabinoid receptor type 1 (CB1R) binding or activation. The ligand showed a favorable ADMET profile and exhibited systemic and ocular exposure after oral delivery. Functional potency in vitro translated from recombinant to endogenous expression systems. In vivo, orally administered RG7774 reduced retinal permeability and leukocyte adhesion in rodents with lipopolysaccharide (LPS)-induced uveitis and streptozotocin (STZ)-induced DR, and reduced lesion areas in rats with laser-induced CNV with an ED50 of 0.32 mg/kg. Anatomically, RG7774 reduced the migration of retinal microglia to retinal lesions. Discussion: RG7774 is a novel, highly selective, and orally bioavailable CB2R agonist, with an acceptable systemic and ocular PK profile, and beneficial effects on retinal vascular permeability, leukocyte adhesion, and ocular inflammation in rodent animal models. Results support the development of RG7774 as a potential treatment for retinal diseases with similar pathophysiologies as addressed by the animal models.

Discovery and optimisation of 1-hydroxyimino-3,3-diphenylpropanes, a new class of orally active GPBAR1 (TGR5) agonists.

A series of non-steroidal GPBAR1 (TGR5) agonists was developed from a hit in a high-throughput screening campaign. Lead identification efforts produced biphenyl-4-carboxylic acid derivative (R)-22, which displayed a robust secretion of PYY after oral administration in a degree that can be correlated with the unbound plasma concentration. Further optimisation work focusing on reduction of the lipophilicity provided the 1-phenylpiperidine-4-carboxylic acid derivative (R)-29 (RO5527239), which showed an improved secretion of PYY and GLP-1, translating into a significant reduction of postprandial blood glucose excursion in an oral glucose tolerance test in DIO mice.

Identifying opportunities for late-stage C-H alkylation with high-throughput experimentation and in silico reaction screening.

Enhancing the properties of advanced drug candidates is aided by the direct incorporation of specific chemical groups, avoiding the need to construct the entire compound from the ground up. Nevertheless, their chemical intricacy often poses challenges in predicting reactivity for C-H activation reactions and planning their synthesis. We adopted a reaction screening approach that combines high-throughput experimentation (HTE) at a nanomolar scale with computational graph neural networks (GNNs). This approach aims to identify suitable substrates for late-stage C-H alkylation using Minisci-type chemistry. GNNs were trained using experimentally generated reactions derived from in-house HTE and literature data. These trained models were then used to predict, in a forward-looking manner, the coupling of 3180 advanced heterocyclic building blocks with a diverse set of sp3-rich carboxylic acids. This predictive approach aimed to explore the substrate landscape for Minisci-type alkylations. Promising candidates were chosen, their production was scaled up, and they were subsequently isolated and characterized. This process led to the creation of 30 novel, functionally modified molecules that hold potential for further refinement. These results positively advocate the application of HTE-based machine learning to virtual reaction screening.