Dataset Information

New, Low-Molecular Weight Chemical Compounds Inhibiting Biological Activity of Interleukin 15.

ABSTRACT: Chronic overproduction of IL-15 contributes to the pathogenesis of numerous inflammatory and autoimmune disorders. Experimental methods used to reduce the cytokine activity show promise as potential therapeutic approaches to modify IL-15 signaling and alleviate the development and progression of IL-15-related diseases. We previously demonstrated that an efficient reduction of IL-15 activity can be obtained by selective blocking of the specific, high affinity subunit alpha of the IL-15 receptor (IL-15Rα) with small-molecule inhibitors. In this study, we determined the structure-activity relationship of currently known IL-15Rα inhibitors in order to define the critical structural features required for their activity. To validate our predictions, we designed, analyzed in silico, and assessed in vitro function of 16 new potential IL-15Rα inhibitors. All newly synthesized molecules were benzoic acid derivatives with favorable ADME properties and they efficiently reduced IL-15 dependent peripheral blood mononuclear cells (PBMCs) proliferation, as well as TNF-α and IL-17 secretion. The rational design of IL-15 inhibitors may propel the identification of potential lead molecules for the development of safe and effective therapeutic agents.

SUBMITTER: Krzeczynski P

PROVIDER: S-EPMC10005041 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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New, Low-Molecular Weight Chemical Compounds Inhibiting Biological Activity of Interleukin 15.

Krzeczyński Piotr P Dutkiewicz Małgorzata M Zegrocka-Stendel Oliwia O Trzaskowski Bartosz B Koziak Katarzyna K

Molecules (Basel, Switzerland) 20230301 5

Chronic overproduction of IL-15 contributes to the pathogenesis of numerous inflammatory and autoimmune disorders. Experimental methods used to reduce the cytokine activity show promise as potential therapeutic approaches to modify IL-15 signaling and alleviate the development and progression of IL-15-related diseases. We previously demonstrated that an efficient reduction of IL-15 activity can be obtained by selective blocking of the specific, high affinity subunit alpha of the IL-15 receptor ( ...[more]

PMID: 36903533

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Project description:Given a compound, how can we effectively predict its biological function? It is a fundamentally important problem because the information thus obtained may benefit the understanding of many basic biological processes and provide useful clues for drug design. In this study, based on the information of chemical-chemical interactions, a novel method was developed that can be used to identify which of the following eleven metabolic pathway classes a query compound may be involved with: (1) Carbohydrate Metabolism, (2) Energy Metabolism, (3) Lipid Metabolism, (4) Nucleotide Metabolism, (5) Amino Acid Metabolism, (6) Metabolism of Other Amino Acids, (7) Glycan Biosynthesis and Metabolism, (8) Metabolism of Cofactors and Vitamins, (9) Metabolism of Terpenoids and Polyketides, (10) Biosynthesis of Other Secondary Metabolites, (11) Xenobiotics Biodegradation and Metabolism. It was observed that the overall success rate obtained by the method via the 5-fold cross-validation test on a benchmark dataset consisting of 3,137 compounds was 77.97%, which is much higher than 10.45%, the corresponding success rate obtained by the random guesses. Besides, to deal with the situation that some compounds may be involved with more than one metabolic pathway class, the method presented here is featured by the capacity able to provide a series of potential metabolic pathway classes ranked according to the descending order of their likelihood for each of the query compounds concerned. Furthermore, our method was also applied to predict 5,549 compounds whose metabolic pathway classes are unknown. Interestingly, the results thus obtained are quite consistent with the deductions from the reports by other investigators. It is anticipated that, with the continuous increase of the chemical-chemical interaction data, the current method will be further enhanced in its power and accuracy, so as to become a useful complementary vehicle in annotating uncharacterized compounds for their biological functions.

Dataset Information

New, Low-Molecular Weight Chemical Compounds Inhibiting Biological Activity of Interleukin 15.

Publications

New, Low-Molecular Weight Chemical Compounds Inhibiting Biological Activity of Interleukin 15.

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