Design, synthesis, docking and biological evaluation of 4-phenyl-thiazole derivatives as autotaxin (ATX) inhibitors

Recent research advances in ATX inhibitors: An overview of primary literature

The autoglobulin gene is the main enzyme for circulating LPA production and has lysophosphatidylcholine D activity, which catalyzes the production of lysophosphatidic acid and choline with lysophosphatidylcholine as substrate. A growing body of experimental evidence suggests that autoglobulin is involved in the pathogenesis of a variety of diseases. This review summarizes the different structural ATX inhibitors classified according to their binding mode to the ATX triple orientation site, and summarizes the conformational relationships and molecular docking of each type with ATX structure, hoping to contribute to the development of novel ATX inhibitors.

Design and Development of Autotaxin Inhibitors

Autotaxin (ATX) is the only enzyme of the ecto-nucleotide pyrophosphatase/phosphodiesterase (ENPP2) family with lysophospholipase D (lysoPLD) activity, which is mainly responsible for the hydrolysis of extracellular lysophosphatidylcholine (LPC) into lysophosphatidic acid (LPA). LPA can induce various responses, such as cell proliferation, migration, and cytokine production, through six G protein-coupled receptors (LPA1-6). This signaling pathway is associated with metabolic and inflammatory disorder, and inhibiting this pathway has a positive effect on the treatment of related diseases, while ATX, as an important role in the production of LPA, has been shown to be associated with the occurrence and metastasis of tumors, fibrosis and cardiovascular diseases. From mimics of ATX natural lipid substrates to the rational design of small molecule inhibitors, ATX inhibitors have made rapid progress in structural diversity and design over the past 20 years, and three drugs, GLPG1690, BBT-877, and BLD-0409, have entered clinical trials. In this paper, we will review the structure of ATX inhibitors from the perspective of the transformation of design ideas, discuss the advantages and disadvantages of each inhibitor type, and put forward prospects for the development of ATX inhibitors in the future.

Artificial Intelligence, Big Data and Machine Learning Approaches in Precision Medicine & Drug Discovery

Artificial Intelligence revolutionizes the drug development process that can quickly identify potential biologically active compounds from millions of candidate within a short period. The present review is an overview based on some applications of Machine Learning based tools, such as GOLD, Deep PVP, LIB SVM, etc. and the algorithms involved such as support vector machine (SVM), random forest (RF), decision tree and Artificial Neural Network (ANN), etc. at various stages of drug designing and development. These techniques can be employed in SNP discoveries, drug repurposing, ligand-based drug design (LBDD), Ligand-based Virtual Screening (LBVS) and Structure- based Virtual Screening (SBVS), Lead identification, quantitative structure-activity relationship (QSAR) modeling, and ADMET analysis. It is demonstrated that SVM exhibited better performance in indicating that the classification model will have great applications on human intestinal absorption (HIA) predictions. Successful cases have been reported which demonstrate the efficiency of SVM and RF models in identifying JFD00950 as a novel compound targeting against a colon cancer cell line, DLD-1, by inhibition of FEN1 cytotoxic and cleavage activity. Furthermore, a QSAR model was also used to predict flavonoid inhibitory effects on AR activity as a potent treatment for diabetes mellitus (DM), using ANN. Hence, in the era of big data, ML approaches have been evolved as a powerful and efficient way to deal with the huge amounts of generated data from modern drug discovery to model small-molecule drugs, gene biomarkers and identifying the novel drug targets for various diseases.

Idiopathic pulmonary fibrosis: Molecular mechanisms and potential treatment approaches

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive disease with high mortality that commonly occurs in middle-aged and older adults. IPF, characterized by a decline in lung function, often manifests as exertional dyspnea and cough. Symptoms result from a fibrotic process driven by alveolar epithelial cells that leads to increased migration, proliferation, and differentiation of lung fibroblasts. Ultimately, the differentiation of fibroblasts into myofibroblasts, which synthesize excessive amounts of extracellular matrix proteins, destroys the lung architecture. However, the factors that induce the fibrotic process are unclear. Diagnosis can be a difficult process; the gold standard for diagnosis is the multidisciplinary conference. Practical biomarkers are needed to improve diagnostic and prognostic accuracy. High-resolution computed tomography typically shows interstitial pneumonia with basal and peripheral honeycombing. Gas exchange and diffusion capacity are impaired. Treatments are limited, although the anti-fibrotic drugs pirfenidone and nintedanib can slow the progression of the disease. Lung transplantation is often contraindicated because of age and comorbidities, but it improves survival when successful. The incidence and prevalence of IPF has been increasing and there is an urgent need for improved therapies. This review covers the detailed cellular and molecular mechanisms underlying IPF progression as well as current treatments and cutting-edge research into new therapeutic targets.

Pharmacophoric Site Identification and Inhibitor Design for Autotaxin

Autotaxin (ATX) is a potential drug target that is associated with inflammatory diseases and various cancers. In our previous studies, we have designed several inhibitors targeting ATX using computational and experimental approaches. Here, we have analyzed topological water networks (TWNs) in the binding pocket of ATX. TWN analysis revealed a pharmacophoric site inside the pocket. We designed and synthesized compounds considering the identified pharmacophoric site. Furthermore, we performed biological experiments to determine their ATX inhibitory activities. High potency of the designed compounds supports the predictions of the TWN analysis.

Development and therapeutic potential of autotaxin small molecule inhibitors: From bench to advanced clinical trials

Several years after its isolation from melanoma cells, an increasing body of experimental evidence has established the involvement of Autotaxin (ATX) in the pathogenesis of several diseases. ATX, an extracellular enzyme responsible for the hydrolysis of lysophosphatidylcholine (LPC) into the bioactive lipid lysophosphatidic acid (LPA), is overexpressed in a variety of human metastatic cancers and is strongly implicated in chronic inflammation and liver toxicity, fibrotic diseases, and thrombosis. Accordingly, the ATX-LPA signaling pathway is considered a tractable target for therapeutic intervention substantiated by the multitude of research campaigns that have been successful in identifying ATX inhibitors by both academia and industry. Furthermore, from a therapeutic standpoint, the entry and the so far promising results of the first ATX inhibitor in advanced clinical trials against idiopathic pulmonary fibrosis (IPF) lends support to the viability of this approach, bringing it to the forefront of drug discovery efforts. The present review article aims to provide a comprehensive overview of the most important series of ATX inhibitors developed so far. Special weight is lent to the design, structure activity relationship and mode of binding studies carried out, leading to the identification of advanced leads. The most significant in vitro and in vivo pharmacological results of these advanced leads are also summarized. Lastly, the development of the first ATX inhibitor entered in clinical trials accompanied by its phase 1 and 2a clinical trial data is disclosed.