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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8835787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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