Identification of 1, 4-Dihydrothieno[3′, 2′:5, 6]thiopyrano[4, 3-c]pyrazole Derivatives as Human 5-Lipo-oxygenase Inhibitors

Update on thiopyran-fused heterocycle synthesis (2013-2024)

Thiopyrans and their fused derivatives have significant synthetic relevance owing to their biological importance and occurrence in natural products. The current article provides an overview of synthetic strategies employed for the construction of thiopyran-fused heterocycles. In particular, this article discusses synthetic methods for the fusion of thiopyran with heterocycles such as indole, quinoline, pyrimidine, pyridine, thiophene, chromene, oxazole, pyrazole, pyran and furan and covers the literature from 2013 to 2024. The most common precursors for thiopyrano[2,3-b]indoles, thiopyranoquinolines and thiopyranothiazoles are indoline-2-thione, 2-mercaptoquinoline-3-carbaldehyde and thiazolidinone, respectively, and various reactions involving these are described in detail here. Asymmetric syntheses of thiopyranoindoles achieved using chiral catalysts based on thiourea, proline and metal complexes are also included. The biological activity associated with some compounds is also discussed.

Role of sulphur-heterocycles in medicinal chemistry: An update

From many decades, S-heterocycles have maintained their status as an important part and core of FDA approved drugs and medicinally active compounds. With exhaustive exploration of nitrogen heterocycles in medicinal chemistry, researchers have shifted their interest towards other heterocycles, especially, S-heterocycles. Thus several attempts have been made to synthesize a variety of new sulphur containing compounds with high medicinal value and low toxicity profile, in comparison to previous N-heterocycles. Till today, S-heterocycle containing compounds have been largely reported as anticancer, antidiabetic, antimicrobial, antihypertension, antivral, antinflammatory etc. In this review, the authors have tried to provide a critical analysis of synthesis and medicinal attributes of sulphur containing heterocycles such as thiirane, thiophene, thiazole, thiopyran, thiazolidine etc reported within last five years to emphasize the significance and usefulness of these S-heterocycles in the drug discovery process.

5-Lipoxygenase as a drug target: A review on trends in inhibitors structural design, SAR and mechanism based approach

The most common inflammatory disease of the airways is asthma among children affecting around 235 million people worldwide. 5-Lipoxygenase (5-LOX) is a crucial enzyme which helps in the conversion of arachidonic acid (AA) to leukotrienes (LTs), the lipid mediators. It is associated with several inflammation related disorders such as asthma, allergy, and atherosclerosis. Therefore, it is considered as a promising target against inflammation and asthma. Currently, the only drug against 5-LOX which is available is Zileuton, while a few inhibitors are in clinical trial stages such as Atreleuton and Setileuton. So, there is a dire requirement in the area of progress of novel 5-LOX inhibitors which necessitates an understanding of their structure activity relationship and mode of action. In this review, novel 5-LOX inhibitors reported so far, their structural design, SAR and developmental strategies along with clinical updates are discussed over the last two decades.

Computer modeling in predicting the bioactivity of human 5-lipoxygenase inhibitors

5-Lipoxygenase (5-LOX) is a key enzyme in the inflammatory path. Inhibitors of 5-LOX are useful for the treatment of diseases like arthritis, cancer, and asthma. We have collected a dataset including 220 human 5-LOX inhibitors for classification. A self-organizing map (SOM), a support vector machine (SVM), and a multilayer perceptron (MLP) algorithm were used to build models with selected descriptors for classifying 5-LOX inhibitors into active and weakly active ones. MACCS fingerprints were used in this model building process. The accuracy (Q) and Matthews correlation coefficient (MCC) of the best SOM model (Model 1A) were 86.49% and 0.73 on the test set, respectively. The Q and MCC of the best SVM model (Model 2A) were 82.67% and 0.64 on the test set, respectively. The Q and MCC of the best MLP model (Model 3B) were 84.00% and 0.67 on the test set, respectively. In addition, 180 inhibitors with bioactivities measured by fluorescence method were further used for a quantitative prediction. Multiple linear regression (MLR) and SVM algorithms were used to build models to predict the [Formula: see text] values. The correlation coefficients (R) of the MLR model (Model Q1) and the SVM model (Model Q2) were 0.72 and 0.74 on the test set, respectively.