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In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators

Understanding the mechanisms of modulators’ action on enzymes is crucial for optimizing and designing pharmaceutical substances. The acute inflammatory response, in particular, is regulated mainly by a disintegrin and metalloproteinase (ADAM) 17. ADAM17 processes several disease mediators such as TN...

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Autores principales: Bienstein, Marian, Minond, Dmitriy, Schwaneberg, Ulrich, Davari, Mehdi D., Yildiz, Daniela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8835787/
https://www.ncbi.nlm.nih.gov/pubmed/35163294
http://dx.doi.org/10.3390/ijms23031368
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author Bienstein, Marian
Minond, Dmitriy
Schwaneberg, Ulrich
Davari, Mehdi D.
Yildiz, Daniela
author_facet Bienstein, Marian
Minond, Dmitriy
Schwaneberg, Ulrich
Davari, Mehdi D.
Yildiz, Daniela
author_sort Bienstein, Marian
collection PubMed
description Understanding the mechanisms of modulators’ action on enzymes is crucial for optimizing and designing pharmaceutical substances. The acute inflammatory response, in particular, is regulated mainly by a disintegrin and metalloproteinase (ADAM) 17. ADAM17 processes several disease mediators such as TNFα and APP, releasing their soluble ectodomains (shedding). A malfunction of this process leads to a disturbed inflammatory response. Chemical protease inhibitors such as TAPI-1 were used in the past to inhibit ADAM17 proteolytic activity. However, due to ADAM17′s broad expression and activity profile, the development of active-site-directed ADAM17 inhibitor was discontinued. New ‘exosite’ (secondary substrate binding site) inhibitors with substrate selectivity raised the hope of a substrate-selective modulation as a promising approach for inflammatory disease therapy. This work aimed to develop a high-throughput screen for potential ADAM17 modulators as therapeutic drugs. By combining experimental and in silico methods (structural modeling and docking), we modeled the kinetics of ADAM17 inhibitor. The results explain ADAM17 inhibition mechanisms and give a methodology for studying selective inhibition towards the design of pharmaceutical substances with higher selectivity.
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spelling pubmed-88357872022-02-12 In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators Bienstein, Marian Minond, Dmitriy Schwaneberg, Ulrich Davari, Mehdi D. Yildiz, Daniela Int J Mol Sci Article Understanding the mechanisms of modulators’ action on enzymes is crucial for optimizing and designing pharmaceutical substances. The acute inflammatory response, in particular, is regulated mainly by a disintegrin and metalloproteinase (ADAM) 17. ADAM17 processes several disease mediators such as TNFα and APP, releasing their soluble ectodomains (shedding). A malfunction of this process leads to a disturbed inflammatory response. Chemical protease inhibitors such as TAPI-1 were used in the past to inhibit ADAM17 proteolytic activity. However, due to ADAM17′s broad expression and activity profile, the development of active-site-directed ADAM17 inhibitor was discontinued. New ‘exosite’ (secondary substrate binding site) inhibitors with substrate selectivity raised the hope of a substrate-selective modulation as a promising approach for inflammatory disease therapy. This work aimed to develop a high-throughput screen for potential ADAM17 modulators as therapeutic drugs. By combining experimental and in silico methods (structural modeling and docking), we modeled the kinetics of ADAM17 inhibitor. The results explain ADAM17 inhibition mechanisms and give a methodology for studying selective inhibition towards the design of pharmaceutical substances with higher selectivity. MDPI 2022-01-25 /pmc/articles/PMC8835787/ /pubmed/35163294 http://dx.doi.org/10.3390/ijms23031368 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
Bienstein, Marian
Minond, Dmitriy
Schwaneberg, Ulrich
Davari, Mehdi D.
Yildiz, Daniela
In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators
title In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators
title_full In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators
title_fullStr In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators
title_full_unstemmed In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators
title_short In Silico and Experimental ADAM17 Kinetic Modeling as Basis for Future Screening System for Modulators
title_sort in silico and experimental adam17 kinetic modeling as basis for future screening system for modulators
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8835787/
https://www.ncbi.nlm.nih.gov/pubmed/35163294
http://dx.doi.org/10.3390/ijms23031368
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