Drug Discovery Programs Research Articles

The development of a novel high-throughput membrane potential assay and a solid-supported membrane (SSM)-based electrophysiological assay to study the pharmacological inhibition of GLUT9/SLC2A9 isoforms in a drug discovery program

GLUT9/SLC2A9 is a urate transporter and takes a fundamental role in the maintenance of normal serum urate levels. GLUT9 is the sole transporter of reabsorbed urate from renal epithelial cells to blood, thus making it an ideal pharmacological target for the development of urate-lowering drugs. None of the three currently available assays for studying GLUT9 pharmacological inhibition can support a high throughput drug discovery screening campaign. In this manuscript we present two novel assay technologies which can be used in a drug discovery screening cascade for GLUT9: a GLUT9 membrane potential assay for primary screening; and a solid-supported membrane (SSM)-based supported electrophysiological assay for secondary screening.

3,3-Difluorooxetane-A Versatile Functional Group for Bioisosteric Replacements in Drug Discovery.

Functional group (FG) is one of the cornerstone concepts in organic chemistry and related areas. The wide spread of bioisosterism ideas in medicinal chemistry and beyond caused a striking rise in demand for novel FGs with a defined impact on the developed compound properties. In this work, the evaluation of the 3,3-difluorooxetane unit (3,3-diFox) as a functional group for bioisosteric replacements is disclosed. A comprehensive experimental study (including multigram building block synthesis, quantification of steric and electronic properties, measurements of pKa, LogP, chemical stability, and biological evaluation of the 3,3-diFox-derived bioisostere of a drug candidate) revealed a prominent behavior of the 3,3-diFox fragment as a versatile substituent for early drug discovery programs.

Selective Deuteration and Tritiation of Pharmaceutically Relevant Sulfoximines.

Pharmaceutical-aligned research endeavors continue to diversify, including via the installation of new chemical functionality and non-classical bioisosteres within drug design. With this, an equally high demand emerges for the direct installation of isotopic substituents into these scaffolds within drug discovery programmes, as isotopologues are essential for the elucidation of the biological efficacy and metabolic fate of the active pharmaceutical ingredient (API). The sulfoximine functional group has recently become established as a high-value unit in this context; however, general and effective methods for the synthesis of deuterium (2H, D) and tritium (3H, T) labelled analogues have remained elusive. Herein, we disclose the design and development of the first iridium-catalyzed sulfoximine-directed hydrogen isotope exchange (HIE) systems that permit the site-selective integration of a distinguishing atomic label at aromatic C(sp2)-H and more challenging C(sp3)-H moieties. Moreover, we exemplify the broad applicability of these methods within a spectrum of molecular settings, as well as in the late-stage generation of isotopically-enriched complex bioactive architectures.

Selective Deuteration and Tritiation of Pharmaceutically Relevant Sulfoximines

Pharmaceutical‐aligned research endeavors continue to diversify, including via the installation of new chemical functionality and non‐classical bioisosteres within drug design. With this, an equally high demand emerges for the direct installation of isotopic substituents into these scaffolds within drug discovery programmes, as isotopologues are essential for the elucidation of the biological efficacy and metabolic fate of the active pharmaceutical ingredient (API). The sulfoximine functional group has recently become established as a high‐value unit in this context; however, general and effective methods for the synthesis of deuterium (2H, D) and tritium (3H, T) labelled analogues have remained elusive. Herein, we disclose the design and development of the first iridium‐catalyzed sulfoximine‐directed hydrogen isotope exchange (HIE) systems that permit the site‐selective integration of a distinguishing atomic label at aromatic C(sp2)–H and more challenging C(sp3)–H moieties. Moreover, we exemplify the broad applicability of these methods within a spectrum of molecular settings, as well as in the late‐stage generation of isotopically‐enriched complex bioactive architectures.

A compound-target pairs dataset: differences between drugs, clinical candidates and other bioactive compounds

Providing a better understanding of what makes a compound a successful drug candidate is crucial for reducing the high attrition rates in drug discovery. Analyses of the differences between active compounds, clinical candidates and drugs require high-quality datasets. However, most datasets of drug discovery programs are not openly available. This work introduces a dataset of compound-target pairs extracted from the open-source bioactivity database ChEMBL (release 32). Compound-target pairs in the dataset either have at least one measured activity or are part of the manually curated set of known interactions in ChEMBL. Known interactions between drugs or clinical candidates and targets are specifically annotated to facilitate analyses of differences between drugs, clinical candidates, and other active compounds. In total, the dataset comprises 614,594 compound-target pairs, 5,109 (3,932) of which are known interactions between drugs (clinical candidates) and targets. The extraction is performed in an automated manner and fully reproducible. We are providing not only the datasets but also the code to rerun the analyses with other ChEMBL releases.

Case Studies on the use of Microsampling for Nonclinical Studies in Pharmaceutical Drug Discovery and Development.

The implementation of microsampling approaches for use in nonclinical discovery and development pharmaceutical studies can have a major impact on improving animal ethics through the use of fewer animals and less invasive procedures for the collection of toxicokinetic and pharmacokinetic samples. In addition, the approach offers the opportunity for obtaining improved quality of data for these studies. This can include the determination of additional timepoints and endpoints, and the ability to obtain exposure data from the same animals utilized to measure other study endpoints. This manuscript presents a number of cases where a variety of microsampling approaches have been successfully implemented by a number of organizations and serves as a guide for those considering the use of microsampling approaches as part of their drug discovery and development programs, as the adoption of these approaches are not yet universal.

Quantitative systems toxicology modeling in pharmaceutical research and development: An industry-wide survey and selected case study examples.

Quantitative systems toxicology (QST) models are increasingly being applied for predicting and understanding toxicity liabilities in pharmaceutical research and development. A European Federation of Pharmaceutical Industries and Associations (EFPIA)-wide survey was completed by 15 companies. The results provide insights into the current use of QST models across the industry. 73% of responding companies with more than 10,000 employees utilize QST models. The most applied QST models are for liver, cardiac electrophysiology, and bone marrow/hematology. Responders indicated particular interest in QST models for the central nervous system (CNS), kidney, lung, and skin. QST models are used to support decisions in both preclinical and clinical stages of pharmaceutical development. The survey suggests high demand for QST models and resource limitations were indicated as a common obstacle to broader use and impact. Increased investment in QST resources and training may accelerate application and impact. Case studies of QST model use in decision-making within EFPIA companies are also discussed. This article aims to (i) share industry experience and learnings from applying QST models to inform decision-making in drug discovery and development programs, and (ii) share approaches taken during QST model development and validation and compare these with recommendations for modeling best practices and frameworks proposed in the literature. Discussion of QST-specific applications in relation to these modeling frameworks is relevant in the context of the recently proposed International Council for Harmonization (ICH) M15 guideline on general principles for Model-Informed Drug Development (MIDD).

Synthesis of 2‐Substituted Bicyclo[2.1.1]Hexan‐1‐ols via SmI2‐Mediated Reductive Cyclization Reactions

AbstractThe replacement of benzene rings with saturated bioisosteric counterparts is a key priority in drug discovery programs, and disubstituted bicyclo[2.1.1]hexanes have been recognized as flexible molecular scaffolds that could act as ortho‐substituted benzene bioisosteres. In this study, we outline the synthesis of a wide range of 2‐substituted bicyclo[2.1.1]hexan‐1‐ols, which have the potential to emulate ortho‐phenolic derivatives, via SmI2‐mediated reductive cyclization reactions. The synthetic utility of this methodology was exemplified by the preparation of several saturated analogs of pharmaceutically relevant compounds.

14 (PB402): Xcellomics: powering rapid translation of HTS outputs to AI-driven drug discovery programmes

14 (PB402): Xcellomics: powering rapid translation of HTS outputs to AI-driven drug discovery programmes

Arylation of 2‐Chloro‐3‐(4,6‐Diaryl‐1,3,5‐Triazin‐2‐yl) Quinolines: Formal Synthesis of 3‐(4,6‐Diaryl‐1,3,5‐Triazin‐2‐yl)‐2‐Substituted Quinolines by Suzuki–Miyaura Reaction

ABSTRACTWe have described herein a simple and formal two‐step synthesis of 3‐(4,6‐diaryl‐1,3,5‐triazin‐2‐yl)‐2‐aryl quinolines from 2‐chloro‐3‐(4,6‐diaryl‐1,3,5‐triazin‐2‐yl) quinolines and boronic acids under the Suzuki–Miyaura conditions. This protocol provides the C‐2 arylation of 2‐chloro‐3‐(4,6‐diaryl‐1,3,5‐triazin‐2‐yl) quinolines under the mild reaction conditions. These newly formed chemo‐types may be useful in drug discovery programs or in material chemistry.

Benzothiazole derivatives in the design of antitumor agents.

Benzothiazoles are a class of heterocycles with multiple applications as anticancer, antibiotic, antiviral, and anti-inflammatory agents. Benzothiazole is a privileged scaffold in drug discovery programs for modulating a variety of biological functions. This review focuses on the design and synthesis of new benzothiazole derivatives targeting hypoxic tumors. Cancer is a major health problem, being among the leading causes of death. Tumor-hypoxicareas promote proliferation, malignancy, and resistance to drug treatment, leading to the dysregulation of key signaling pathways that involve drug targets such as vascular endothelial growth factor, epidermal growth factor receptor, hepatocyte growth factor receptor, dual-specificity protein kinase, cyclin-dependent protein kinases, casein kinase2, Rho-related coil formation protein kinase, tunica interna endothelial cell kinase, cyclooxygenase-2, adenosine kinase, lysophosphatidic acid acyltransferases, stearoyl-CoA desaturase, peroxisome proliferator-activated receptors, thioredoxin, heat shock proteins, and carbonic anhydrase IX/XII. In turn, they regulate angiogenesis, proliferation, differentiation, and cell survival, controlling the cell cycle, inflammation, the immune system, and metabolic alterations. A wide diversity of benzothiazoles were reported over the last years to interfere with various proteins involved in tumorigenesis and, more specifically, in hypoxic tumors. Many hypoxic targets are overexpressed as a result of the hypoxia-inducible factor activation cascade and may not be present in normal tissues, providing a potential strategy for selectively targeting hypoxic cancers.

Inhibitor of the non-structural protein 2 protease shows promising efficacy in mouse models of chikungunya

Chikungunya virus (CHIKV) is responsible for the most endemic alphavirus infections called Chikungunya. The endemicity of Chikungunya has increased over the past two decades, and it is a pathogen with pandemic potential. There is currently no approved direct-acting antiviral to treat the disease. As part of our antiviral drug discovery program focused on alphaviruses and the non-structural protein 2 protease, we discovered that J12 and J13 can inhibit CHIKV nsP2 protease and block the replication of CHIKV in cell cultures. Both compounds are metabolically stable to human liver microsomal and S9 enzymes. J13 has excellent oral bioavailability in pharmacokinetics studies in mice and ameliorated Chikungunya symptoms in preliminary efficacy studies in mice. J13 exhibited an excellent safety profile in in vitro safety pharmacology and off-target screening assays, making J13 and its analogs good candidates for drug development against Chikungunya.

High-Throughput Assay for Predicting Diarrhea Risk Using a 2D Human Intestinal Stem Cell-Derived Model.

Gastrointestinal toxicities (GITs) are the most prevalent adverse events (AE) reported in clinical trials, often resulting in dose-limitations that reduce drug efficacy and delay development and treatment optimization. Preclinical animal models do not accurately replicate human GI physiology, leaving few options for early detection of GI side effects prior to human studies. Development of an accurate model that predicts GIT earlier in drug discovery programs would better support successful clinical trial outcomes. Chemotherapeutics, which exhibit high rates of clinical GIT, frequently target mitotic cells. Therefore, we hypothesized that a model utilizing proliferative cell populations derived from human intestinal crypts would predict the occurrence of clinical GITs with high accuracy. Here, we describe the development of a multiparametric assay utilizing the RepliGut® Planar system, an intestinal stem cell-derived platform cultured in an accessible high throughput Transwell™ format. This assay addresses key physiological elements of GIT by assessing cell proliferation (EdU incorporation), cell abundance (DAPI quantification), and barrier function (TEER). Using this approach, we demonstrate that primary proliferative cell populations reproducibly respond to marketed chemotherapeutics at physiologic concentrations. To determine the ability of this model to predict clinical diarrhea risk, we evaluated a set of 30 drugs with known clinical diarrhea incidence in three human donors, comparing results to known plasma drug concentrations. This resulted in highly accurate predictions of diarrhea potential for each endpoint (balanced accuracy of 91% for DAPI, 90% for EdU, 88% for TEER) with minimal variation across human donors. In vitro toxicity screening using primary proliferative cells may enable improved safety evaluations, reducing the risk of AEs in clinical trials and ultimately lead to safer and more effective treatments for patients.

Pharmacophore Identification and Structure-Activity Relationship Analysis of a Series of Substituted Azaindoles as Inhibitors of Trypanosoma brucei.

Human African trypanosomiasis is among the World Health Organization's designated neglected tropical diseases. Repurposing strategies are often employed in academic drug discovery programs due to financial limitations, and in this instance, we used human kinase inhibitor chemotypes to identify substituted 4-aminoazaindoles, exemplified by 1. Structure-activity and structure-property relationship analysis, informed by cheminformatics, identified 4s as a potent inhibitor of Trypanosoma brucei growth. While 4s appeared to be fast acting and cidal in the in vitro assays, it failed to cure a murine model of infection. Preliminary efforts to identify the potential mechanism of action of the series pointed to arginine kinase, though, as we demonstrate, this does not appear to be the sole target of our compounds. This comprehensive approach to drug discovery, encompassing cheminformatics, structure-potency and structure-property analysis, and pharmacophore identification, highlights our multipronged efforts to identify novel lead compounds for this deadly disease.

The ‘ABC’ of split-nanoluciferase HIF heterodimerization bioassays: Applications, Benefits & Considerations

Hypoxia-inducible factors (HIF) are interesting targets for multiple therapeutic indications. While HIF activation is desired for the treatment of anemia-related and ischemic diseases, HIF inhibition is of tremendous interest to anti-cancer drug development. Different signaling events within the HIF pathway are being targeted by drug discovery programs, with a special interest in HIF-selective (possibly also HIF1/2 isoform-selective) compounds. In this study, we applied recently developed cell-based split-nanoluciferase HIF heterodimerization assays to study the effects of compounds, targeting HIF activity by various mechanisms of action. This study shows that the application of similar or diverse assay protocols allows to detect various influences on HIF heterodimerization as a key signaling event in the oxygen sensing pathway: increased HIF heterodimerization (roxadustat, MG-132), decreased HIF heterodimerization (PX-478, ibuprofen) and direct (HIF isoform-selective) heterodimerization inhibiting effects (PT-2385). Changes in treatment time and in the assay protocol allowed to assess direct and indirect effects on HIFα-HIFβ heterodimerization. In addition to the evaluation of applications of these new bioassays regarding pharmacological characterizations, benefits and considerations are discussed related to the use of cellular, luminescent-based bioassays. Briefly, benefits include the bidirectional nature of the biological readout, the upstream mechanism of detection, the differentiation between HIF1 and HIF2 effects and the simulation of various conditions. Specific and general considerations include cell-based, technical and disease/drug-related aspects (e.g., non-specific effects, color interference). In summary, the versatility of these bioassays offers benefits in widespread applications regarding drug discovery and pharmacological characterization of various therapeutics, applying either the same or optimized experimental protocols.

Genetic factors associated with reasons for clinical trial stoppage

Many drug discovery projects are started but few progress fully through clinical trials to approval. Previous work has shown that human genetics support for the therapeutic hypothesis increases the chance of trial progression. Here, we applied natural language processing to classify the free-text reasons for 28,561 clinical trials that stopped before their endpoints were met. We then evaluated these classes in light of the underlying evidence for the therapeutic hypothesis and target properties. We found that trials are more likely to stop because of a lack of efficacy in the absence of strong genetic evidence from human populations or genetically modified animal models. Furthermore, certain trials are more likely to stop for safety reasons if the drug target gene is highly constrained in human populations and if the gene is broadly expressed across tissues. These results support the growing use of human genetics to evaluate targets for drug discovery programs.

Innovation in clinical trials in brain health: Computerised assessment and remote clinical trials

Innovation in clinical trials in brain health: Computerised assessment and remote clinical trials New clinical trials in brain health require innovative methodologies for targeted recruitment and longitudinal assessment. Professor Anne Corbett outlines how her team’s PROTECT portfolio can overcome challenges in trials of cognitive health interventions, offering solutions for intelligent trial design. After decades of relative inactivity, there is currently a growing interest and investment in novel interventions for cognitive and mental health conditions. This is particularly true for trials in cognitive impairment and early dementia. This health area has previously been considered too high-risk and challenging, with failed trials and difficulty in recruiting target groups leading to widespread demotivation for trials in this area. However, a new generation of disease-modifying treatments for Alzheimer’s Disease is in the pipeline, with immunotherapy lecanemab receiving FDA approval in 2023 and donanemab currently under review. (1) These successes have reinvigorated development in Alzheimer’s and dementia drug discovery programmes, and larger numbers of trials are anticipated in the coming years.

Molecules targeting a novel homotrimer cavity of Spike protein attenuate replication of SARS-CoV-2

The SARS-CoV-2 Spike glycoprotein (S) utilizes a unique trimeric conformation to interact with the ACE2 receptor on host cells, making it a prime target for inhibitors that block viral entry. We have previously identified a novel proteinaceous cavity within the Spike protein homotrimer that could serve as a binding site for small molecules. However, it is not known whether these molecules would inhibit, stimulate, or have no effect on viral replication. To address this, we employed structural-based screening to identify small molecules that dock into the trimer cavity and assessed their impact on viral replication. Our findings show that a cohort of identified small molecules binding to the Spike trimer cavity effectively reduces the replication of various SARS-CoV-2 variants. These molecules exhibited inhibitory effects on B.1 (European original, D614G, EDB2) and B.1.617.2 (δ) variants, while showing moderate activity against the B.1.1.7 (α) variant. We further categorized these molecules into distinct groups based on their structural similarities. Our experiments demonstrated a dose-dependent viral replication inhibitory activity of these compounds, with some, like BCC0040453 exhibiting no adverse effects on cell viability even at high concentrations. Further investigation revealed that pre-incubating virions with compounds like BCC0031216 at different temperatures significantly inhibited viral replication, suggesting their specificity towards the S protein. Overall, our study highlights the inhibitory impact of a diverse set of chemical molecules on the biological activity of the Spike protein. These findings provide valuable insights into the role of the trimer cavity in the viral replication cycle and aid drug discovery programs aimed at targeting the coronavirus family.

G Protein-Coupled Receptor-Ligand Pose and Functional Class Prediction.

G protein-coupled receptor (GPCR) transmembrane protein family members play essential roles in physiology. Numerous pharmaceuticals target GPCRs, and many drug discovery programs utilize virtual screening (VS) against GPCR targets. Improvements in the accuracy of predicting new molecules that bind to and either activate or inhibit GPCR function would accelerate such drug discovery programs. This work addresses two significant research questions. First, do ligand interaction fingerprints provide a substantial advantage over automated methods of binding site selection for classical docking? Second, can the functional status of prospective screening candidates be predicted from ligand interaction fingerprints using a random forest classifier? Ligand interaction fingerprints were found to offer modest advantages in sampling accurate poses, but no substantial advantage in the final set of top-ranked poses after scoring, and, thus, were not used in the generation of the ligand-receptor complexes used to train and test the random forest classifier. A binary classifier which treated agonists, antagonists, and inverse agonists as active and all other ligands as inactive proved highly effective in ligand function prediction in an external test set of GPR31 and TAAR2 candidate ligands with a hit rate of 82.6% actual actives within the set of predicted actives.

Ongoing Implementation and Prospective Validation of Artificial Intelligence/Machine Learning Tools at an African Drug Discovery Center.

Artificial intelligence (AI) and machine learning (ML) are anticipated to accelerate drug discovery programs. Following our development of an end-to-end virtual screening cascade at the University of Cape Town (UCT) Holistic Drug Discovery and Development (H3D) Center, we report the ongoing implementation of open-source AI/ML tools for use in resource-constrained settings.