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Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery

Infectious diseases are still a major problem worldwide. This includes microbial infections, with a constant increase in resistance to the current anti-infectives employed. Toll-like receptors (TLRs) perform a fundamental role in pathogen recognition and activation of the innate immune response. Pro...

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Autores principales: Merk, Helena, Amran-Gealia, Tehila, Finkelmeier, Doris, Kohl, Christina, Pichota, Isabelle, Stern, Noa, Rupp, Steffen, Goldblum, Amiram, Burger-Kentischer, Anke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8876567/
https://www.ncbi.nlm.nih.gov/pubmed/35208698
http://dx.doi.org/10.3390/microorganisms10020243
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author Merk, Helena
Amran-Gealia, Tehila
Finkelmeier, Doris
Kohl, Christina
Pichota, Isabelle
Stern, Noa
Rupp, Steffen
Goldblum, Amiram
Burger-Kentischer, Anke
author_facet Merk, Helena
Amran-Gealia, Tehila
Finkelmeier, Doris
Kohl, Christina
Pichota, Isabelle
Stern, Noa
Rupp, Steffen
Goldblum, Amiram
Burger-Kentischer, Anke
author_sort Merk, Helena
collection PubMed
description Infectious diseases are still a major problem worldwide. This includes microbial infections, with a constant increase in resistance to the current anti-infectives employed. Toll-like receptors (TLRs) perform a fundamental role in pathogen recognition and activation of the innate immune response. Promising new approaches to combat infections and inflammatory diseases involve modulation of the host immune system via TLR4. TLR4 and its co-receptors MD2 and CD14 are required for immune response to fungal and bacterial infection by recognition of microbial cell wall components, making it a prime target for drug development. To evaluate the efficacy of anti-infective compounds early on, we have developed a series of human-based immune responsive infection models, including immune responsive 3D-skin infection models for modeling fungal infections. By using computational methods: pharmacophore modeling and molecular docking, we identified a set of 46 potential modulators of TLR4, which were screened in several tests systems of increasing complexity, including immune responsive 3D-skin infection models. We could show a strong suppression of cytokine and chemokine response induced by lipopolysacharide (LPS) and Candida albicans for individual compounds. The development of human-based immune responsive assays provides a more accurate and reliable basis for development of new anti-inflammatory or immune-modulating drugs.
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spelling pubmed-88765672022-02-26 Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery Merk, Helena Amran-Gealia, Tehila Finkelmeier, Doris Kohl, Christina Pichota, Isabelle Stern, Noa Rupp, Steffen Goldblum, Amiram Burger-Kentischer, Anke Microorganisms Article Infectious diseases are still a major problem worldwide. This includes microbial infections, with a constant increase in resistance to the current anti-infectives employed. Toll-like receptors (TLRs) perform a fundamental role in pathogen recognition and activation of the innate immune response. Promising new approaches to combat infections and inflammatory diseases involve modulation of the host immune system via TLR4. TLR4 and its co-receptors MD2 and CD14 are required for immune response to fungal and bacterial infection by recognition of microbial cell wall components, making it a prime target for drug development. To evaluate the efficacy of anti-infective compounds early on, we have developed a series of human-based immune responsive infection models, including immune responsive 3D-skin infection models for modeling fungal infections. By using computational methods: pharmacophore modeling and molecular docking, we identified a set of 46 potential modulators of TLR4, which were screened in several tests systems of increasing complexity, including immune responsive 3D-skin infection models. We could show a strong suppression of cytokine and chemokine response induced by lipopolysacharide (LPS) and Candida albicans for individual compounds. The development of human-based immune responsive assays provides a more accurate and reliable basis for development of new anti-inflammatory or immune-modulating drugs. MDPI 2022-01-22 /pmc/articles/PMC8876567/ /pubmed/35208698 http://dx.doi.org/10.3390/microorganisms10020243 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Merk, Helena
Amran-Gealia, Tehila
Finkelmeier, Doris
Kohl, Christina
Pichota, Isabelle
Stern, Noa
Rupp, Steffen
Goldblum, Amiram
Burger-Kentischer, Anke
Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery
title Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery
title_full Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery
title_fullStr Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery
title_full_unstemmed Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery
title_short Human-Based Immune Responsive In Vitro Infection Models for Validation of Novel TLR4 Antagonists Identified by Computational Discovery
title_sort human-based immune responsive in vitro infection models for validation of novel tlr4 antagonists identified by computational discovery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8876567/
https://www.ncbi.nlm.nih.gov/pubmed/35208698
http://dx.doi.org/10.3390/microorganisms10020243
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