Pulmonary fibrosis occurs in a variety of clinical settings, constitutes a major cause of morbidity and mortality, and represents an enormous unmet medical need. However, the disease is heterogeneous, and the failure to accurately discern between forms of fibrosing lung diseases leads to inaccurate treatments. Pulmonary fibrosis occurring in the context of connective tissue diseases is often characterized by a distinct pattern of tissue pathology and may be amenable to immunosuppressive therapies. In contrast, idiopathic pulmonary fibrosis (IPF) is a progressive and lethal form of fibrosing lung disease that is recalcitrant to therapies that target the immune system. Although animal models of fibrosis imperfectly recapitulate IPF, they have yielded numerous targets for therapeutic intervention. Understanding the heterogeneity of these diseases and elucidating the final common pathways of fibrogenesis are critical for the development of efficacious therapies for severe fibrosing lung diseases.

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Pulmonary fibrosis: patterns and perpetrators

A Liver Full of JNK: Signaling in Regulation of Cell Function and Disease Pathogenesis, and Clinical Approaches

The JNKs are master protein kinases that regulate many physiological processes, including inflammatory responses, morphogenesis, cell proliferation, differentiation, survival and death. It is increasingly apparent that persistent activation of JNKs is involved in cancer development and progression. Therefore, JNKs represent attractive targets for therapeutic intervention with small molecule kinase inhibitors. However, evidence supportive of a tumour suppressor role for the JNK proteins has also been documented. Recent studies showed that the two major JNK proteins, JNK1 and JNK2, have distinct or even opposing functions in different types of cancer. As such, close consideration of which JNK proteins are beneficial targets and, more importantly, what effect small molecule inhibitors of JNKs have on physiological processes, are essential. A number of ATP-competitive and ATP-non-competitive JNK inhibitors have been developed, but have several limitations such as a lack of specificity and cellular toxicity. In this review, we summarize the accumulating evidence supporting a role for the JNK proteins in the pathogenesis of different solid and haematological malignancies, and discuss many challenges and scientific opportunities in the targeting of JNKs in cancer.

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JNK signalling in cancer: in need of new, smarter therapeutic targets

Recently, deep generative models have revealed itself as a promising way of performing de novo molecule design. However, previous research has focused mainly on generating SMILES strings instead of molecular graphs. Although available, current graph generative models are are often too general and computationally expensive. In this work, a new de novo molecular design framework is proposed based on a type of sequential graph generators that do not use atom level recurrent units. Compared with previous graph generative models, the proposed method is much more tuned for molecule generation and has been scaled up to cover significantly larger molecules in the ChEMBL database. It is shown that the graph-based model outperforms SMILES based models in a variety of metrics, especially in the rate of valid outputs. For the application of drug design tasks, conditional graph generative model is employed. This method offers highe flexibility and is suitable for generation based on multiple objectives. The results have demonstrated that this approach can be effectively applied to solve several drug design problems, including the generation of compounds containing a given scaffold, compounds with specific drug-likeness and synthetic accessibility requirements, as well as dual inhibitors against JNK3 and GSK-3β.

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Multi-objective de novo drug design with conditional graph generative model

Fibrosis, which leads to progressive loss of tissue function and eventual organ failure, has been estimated to contribute to ~45% of deaths in the developed world, and so new therapeutics to modulate fibrosis are urgently needed. Major advances in our understanding of the mechanisms underlying pathological fibrosis are supporting the search for such therapeutics, and the recent approval of two anti-fibrotic drugs for idiopathic pulmonary fibrosis has demonstrated the tractability of this area for drug discovery. This Review examines the pharmacology and structural information for small molecules being evaluated for lung, liver, kidney and skin fibrosis. In particular, we discuss the insights gained from the use of these pharmacological tools, and how these entities can inform, and probe, emerging insights into disease mechanisms, including the potential for future drug combinations.

Dissecting fibrosis: therapeutic insights from the small-molecule toolbox.

Discovery of CC-930, an orally active anti-fibrotic JNK inhibitor.

Background A rapid and comprehensive metabolic stability screen at the top of a drug discovery flow chart serves as an effective gate in eliminating low value compounds. This imparts a significant level of efficiency and saves valuable resources. While microsomes are amenable to high throughput automation and are cost effective, their enzymatic make-up is limited to that which is contained in endoplasmic reticulum, thereby informing only on Phase I metabolism. Lack of Phase II metabolism data can become a potential liability later in the process, adversely affecting discovery projects' timelines and budget. Hepatocytes offer a full complement of metabolic enzymes and retain their cellular compartments, better representing liver metabolic function. However, hepatocyte screens are relatively expensive, labor intensive, and not easily automatable. Liver S9 fractions include Phase I and II metabolic enzymes, are relatively inexpensive, easy to use, and amenable to automation, making them a more appropriate screening system. We compare the data from the three systems and present the results. Results Liver S9 and hepatocyte stability assays binned into the same category 70-84% of the time. Microsome and hepatocyte data were in agreement 73-82% of the time. The true rate for stability versus plasma clearance was 45% for hepatocytes and 43% for S9. Conclusion In our opinion, replacing liver microsome and hepatocyte assays with S9 assay for high throughput metabolic screening purposes provides the combined benefit of comprehensive and high quality data at a reasonable expense for drug discovery programs.

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Efficiency in Drug Discovery: Liver S9 Fraction Assay As a Screen for Metabolic Stability

Discovery and optimization of thieno[2,3-d]pyrimidines as B-Raf inhibitors.

With the goal of refining our discovery DMPK workflow, we conducted a retrospective analysis on internal Celgene compounds by calculating the physicochemical properties and gathering data from several assays including solubility, rat and human liver S9 stability, Caco-2 permeability, and rat intravenous (iv.) and oral pharmacokinetics. Our analysis identified plasma clearance to be most statistically relevant for prediction of oral exposure. In rat, compounds with rat S9 stability of ≥70% at 60 min and a plasma clearance of ≤43 ml/min/kg had the greatest chance of achieving oral exposures above 3 µM.h. Compounds with the dual advantage of plasma clearance ≤43 ml/min/kg and Caco-2 permeability ≥8 × 10–6 cm/s or efflux ratio ≤8 were highly likely to achieve those oral exposures. Implementation of these criteria leads to a significant increase in efficiency, good pharmacokinetic properties, cost savings and a reduction in the use of animals.

April Bai

Papers

Discovery of CC-930, an orally active anti-fibrotic JNK inhibitor.

Efficiency in Drug Discovery: Liver S9 Fraction Assay As a Screen for Metabolic Stability

Discovery and optimization of thieno[2,3-d]pyrimidines as B-Raf inhibitors.

Proposing advancement criteria for efficient DMPK triage of new chemical entities.