Novel Inhibitory Site Revealed by Mode of Action on the Metabotropic Glutamate 7 Receptor Venus Flytrap Domain.

Metabotropic glutamate (mGlu) receptors play a key role in modulating most synapses in the brain. The mGlu7 receptors inhibit presynaptic neurotransmitter release and offer therapeutic possibilities for post-traumatic stress disorders or epilepsy. Screening campaigns provided mGlu7-specific allosteric modulators as the inhibitor (Gee et al.

Discovery of Ligands for TRIM58, a Novel Tissue-Selective E3 Ligase.

Redirecting E3 ligases to neo-substrates, leading to their proteasomal disassembly, known as targeted protein degradation (TPD), has emerged as a promising alternative to traditional, occupancy-driven pharmacology. Although the field has expanded tremendously over the past years, the choice of E3 ligases remains limited, with an almost exclusive focus on CRBN and VHL. Here, we report the discovery of novel ligands to the PRY-SPRY domain of TRIM58, a RING ligase that is specifically expressed in erythroid precursor cells.

Rational Screening for Cooperativity in Small-Molecule Inducers of Protein-Protein Associations.

The hallmark of a molecular glue is its ability to induce cooperative protein-protein interactions, leading to the formation of a ternary complex, despite weaker binding toward one or both individual proteins. Notably, the extent of cooperativity distinguishes molecular glues from bifunctional compounds, which constitute a second class of inducers of protein-protein interactions. However, apart from serendipitous discovery, there have been limited rational screening strategies for the high cooperativity exhibited by molecular glues.

Discovery of a selective and biologically active low-molecular weight antagonist of human interleukin-1β.

Human interleukin-1β (hIL-1β) is a pro-inflammatory cytokine involved in many diseases. While hIL-1β directed antibodies have shown clinical benefit, an orally available low-molecular weight antagonist is still elusive, limiting the applications of hIL-1β-directed therapies. Here we describe the discovery of a low-molecular weight hIL-1β antagonist that blocks the interaction with the IL-1R1 receptor.

Inhibiting WNT secretion reduces high bone mass caused by Sost loss-of-function or gain-of-function mutations in Lrp5.

Proper regulation of Wnt signaling is critical for normal bone development and homeostasis. Mutations in several Wnt signaling components, which increase the activity of the pathway in the skeleton, cause high bone mass in human subjects and mouse models. Increased bone mass is often accompanied by severe headaches from increased intracranial pressure, which can lead to fatality and loss of vision or hearing due to the entrapment of cranial nerves.

Diversity-oriented synthesis encoded by deoxyoligonucleotides.

Diversity-oriented synthesis (DOS) is a powerful strategy to prepare molecules with underrepresented features in commercial screening collections, resulting in the elucidation of novel biological mechanisms. In parallel to the development of DOS, DNA-encoded libraries (DELs) have emerged as an effective, efficient screening strategy to identify protein binders. Despite recent advancements in this field, most DEL syntheses are limited by the presence of sensitive DNA-based constructs.

Leveraging Advanced In Silico Techniques in Early Drug Discovery: A Study of Potent Small-Molecule YAP-TEAD PPI Disruptors.

Disruption of the YAP-TEAD protein-protein interaction is an attractive therapeutic strategy in oncology to suppress tumor progression and cancer metastasis. YAP binds to TEAD at a large flat binding interface (∼3500 Å) devoid of a well-defined druggable pocket, so it has been difficult to design low-molecular-weight compounds to abrogate this protein-protein interaction directly. Recently, work by Furet and coworkers ( , DOI: 10.

Design and Biochemical Characterization of Peptidic Inhibitors of the Myb/p300 Interaction.

The Myb transcription factor is involved in the proliferation of hematopoietic cells, and deregulation of its expression can lead to cancers such as leukemia. Myb interacts with various proteins, including the histone acetyltransferases p300 and CBP. Myb binds to a small domain of p300, the KIX domain (p300), and inhibiting this interaction is a potential new drug discovery strategy in oncology.

Genetic models of cleavage-reduced and soluble TREM2 reveal distinct effects on myelination and microglia function in the cuprizone model.

Triggering receptor expressed on myeloid cells 2 (TREM2) is a cell-surface immunoreceptor expressed on microglia, osteoclasts, dendritic cells and macrophages. Heterozygous loss-of-function mutations in TREM2, including mutations enhancing shedding form the cell surface, have been associated with myelin/neuronal loss and neuroinflammation in neurodegenerative diseases, such as Alzheimer`s disease and Frontotemporal Dementia. Using the cuprizone model, we investigated the involvement of soluble and cleavage-reduced TREM2 on central myelination processes in cleavage-reduced (TREM2-IPD), soluble-only (TREM2-sol), knockout (TREM2-KO) and wild-type (WT) mice.

Impact of Siponimod on Enteric and Central Nervous System Pathology in Late-Stage Experimental Autoimmune Encephalomyelitis.

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS). Although immune modulation and suppression are effective during relapsing-remitting MS, secondary progressive MS (SPMS) requires neuroregenerative therapeutic options that act on the CNS. The sphingosine-1-phosphate receptor modulator siponimod is the only approved drug for SPMS.

Structure-activity relationship studies on divalent naphthalene diimide G quadruplex ligands with anticancer and antiparasitic activity.

Naphthalene diimide (NDI) is a central scaffold that has been commonly used in the design of G-quadruplex (G4) ligands. Previous work revealed notable anticancer activity of a disubstituted N-methylpiperazine propyl NDI G4 ligand. Here, we explored structure-activity relationship studies around ligand bis-N,Ń-2,7-(3-(4-methylpiperazin-1-yl)propyl)-1,4,5,8-naphthalenetetracarboxylic diimide, maintaining the central NDI core whilst modifying the spacer and the nature of the cationic groups.

Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural Networks.

Assessing whether compounds penetrate the brain can become critical in drug discovery, either to prevent adverse events or to reach the biological target. Generally, pre-clinical in vivo studies measuring the ratio of brain and blood concentrations () are required to estimate the brain penetration potential of a new drug entity. In this work, we developed machine learning models to predict in vivo compound brain penetration (as Log) from chemical structure.

Demonstrating Benefit-Risk Profiles of Novel Therapeutic Strategies in Kidney Transplantation: Opportunities and Challenges of Real-World Evidence.

While great progress has been made in transplantation medicine, long-term graft failure and serious side effects still pose a challenge in kidney transplantation. Effective and safe long-term treatments are needed. Therefore, evidence of the lasting benefit-risk of novel therapies is required.

Identification of NVP-CLR457 as an Orally Bioavailable Non-CNS-Penetrant pan-Class IA Phosphoinositol-3-Kinase Inhibitor.

Balanced pan-class I phosphoinositide 3-kinase inhibition as an approach to cancer treatment offers the prospect of treating a broad range of tumor types and/or a way to achieve greater efficacy with a single inhibitor. Taking buparlisib as the starting point, the balanced pan-class I PI3K inhibitor (NVP-CLR457) was identified with what was considered to be a best-in-class profile. Key to the optimization to achieve this profile was eliminating a microtubule stabilizing off-target activity, balancing the pan-class I PI3K inhibition profile, minimizing CNS penetration, and developing an amorphous solid dispersion formulation.

Structure-Based Optimization of a Fragment-like TLR8 Binding Screening Hit to an Efficacious TLR7/8 Antagonist.

Inappropriate activation of TLR7 and TLR8 is linked to several autoimmune diseases, such as lupus erythematosus. Here we report on the efficient structure-based optimization of the inhibition of TLR8, starting from a co-crystal structure of a small screening hit. Further optimization of the physicochemical properties for cellular potency and expansion of the structure-activity relationship for dual potency finally resulted in a highly potent TLR7/8 antagonist with demonstrated efficacy after oral dosing.

Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery.

The support vector machine (SVM) algorithm is one of the most widely used machine learning (ML) methods for predicting active compounds and molecular properties. In chemoinformatics and drug discovery, SVM has been a state-of-the-art ML approach for more than a decade. A unique attribute of SVM is that it operates in feature spaces of increasing dimensionality.

Discovery of a novel 2-aminopyrazine-3-carboxamide as a potent and selective inhibitor of Activin Receptor-Like Kinase-2 (ALK2) for the treatment of fibrodysplasia ossificans progressiva.

Inhibition of mutant activin A type-1 receptor ACVR1 (ALK2) signaling by small-molecule drugs is a promising therapeutic approach to treat fibrodysplasia ossificans progressiva (FOP), an ultra-rare disease leading to progressive soft tissue heterotopic ossification with no curative treatment available to date. Here, we describe the synthesis and in vitro characterization of a novel series of 2-aminopyrazine-3-carboxamides that led to the discovery of Compound 23 showing excellent biochemical and cellular potency, selectivity over other BMP and TGFβ signaling receptor kinases, and a favorable in vitro ADME profile.

A kinase inhibitor which specifically targets the ABL myristate pocket (STAMP), but unlike asciminib crosses the blood-brain barrier.

The ubiquitously expressed ABL1 and ABL2 protein kinases play many important roles in cell function. Although they have been implicated in neuron development, maintenance and signaling, there are no good tool compounds to evaluate the effects of ABL kinase inhibition in the brain. Asciminib is a recently approved drug that specifically and potently inhibits the tyrosine kinase activity of ABL1, ABL2 and that of the chimeric BCR-ABL1 oncoprotein which causes chronic myeloid leukemia.

Impact of Artificial Intelligence on Compound Discovery, Design, and Synthesis.

As in other areas, artificial intelligence (AI) is heavily promoted in different scientific fields, including chemistry. Although chemistry traditionally tends to be a conservative field and slower than others to adapt new concepts, AI is increasingly being investigated across chemical disciplines. In medicinal chemistry, supported by computer-aided drug design and cheminformatics, computational methods have long been employed to aid in the search for and optimization of active compounds.

Perspectives and Opportunities in Medicinal Chemistry: A View from the Novartis Institute for BioMedical Research in Basel, Switzerland.

An opinion on changes and opportunities for the pharmaceutical industry in Switzerland, as seen from the Global Discovery Chemistry platform of the Novartis Institutes for BioMedical Research in Basel.

Explainable Machine Learning for Property Predictions in Compound Optimization.

The prediction of compound properties from chemical structure is a main task for machine learning (ML) in medicinal chemistry. ML is often applied to large data sets in applications such as compound screening, virtual library enumeration, or generative chemistry. Albeit desirable, a detailed understanding of ML model decisions is typically not required in these cases.

Splitting chemical structure data sets for federated privacy-preserving machine learning.

With the increase in applications of machine learning methods in drug design and related fields, the challenge of designing sound test sets becomes more and more prominent. The goal of this challenge is to have a realistic split of chemical structures (compounds) between training, validation and test set such that the performance on the test set is meaningful to infer the performance in a prospective application. This challenge is by its own very interesting and relevant, but is even more complex in a federated machine learning approach where multiple partners jointly train a model under privacy-preserving conditions where chemical structures must not be shared between the different participating parties.

Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models.

Machine learning models predicting the bioactivity of chemical compounds belong nowadays to the standard tools of cheminformaticians and computational medicinal chemists. Multi-task and federated learning are promising machine learning approaches that allow privacy-preserving usage of large amounts of data from diverse sources, which is crucial for achieving good generalization and high-performance results. Using large, real world data sets from six pharmaceutical companies, here we investigate different strategies for averaging weighted task loss functions to train multi-task bioactivity classification models.

Fostering Research Synergies between Chemists in Swiss Academia and at Novartis.

We present a short overview of the way Novartis chemists interact and collaborate with the academic chemistry community in Switzerland. This article exemplifies a number of collaborations, and illustrates opportunities to foster research synergies between academic and industrial researchers. It also describes established programs available to academic groups, providing them access to Novartis resources and expertise.