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Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease
Currently, there are no therapies available to modify the disease progression of Huntington’s disease (HD). Recent clinical trial failures of antisense oligonucleotide candidates in HD have demonstrated the need for new therapeutic approaches. Here, we developed a novel in-silico fragment scanning a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668931/ https://www.ncbi.nlm.nih.gov/pubmed/36385140 http://dx.doi.org/10.1038/s41598-022-21900-2 |
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author | Galyan, Simon Marius Ewald, Collin Y. Jalencas, Xavier Masrani, Shyam Meral, Selin Mestres, Jordi |
author_facet | Galyan, Simon Marius Ewald, Collin Y. Jalencas, Xavier Masrani, Shyam Meral, Selin Mestres, Jordi |
author_sort | Galyan, Simon Marius |
collection | PubMed |
description | Currently, there are no therapies available to modify the disease progression of Huntington’s disease (HD). Recent clinical trial failures of antisense oligonucleotide candidates in HD have demonstrated the need for new therapeutic approaches. Here, we developed a novel in-silico fragment scanning approach across the surface of mutant huntingtin (mHTT) polyQ and predicted four hit compounds. Two rounds of compound analoging using a strategy of testing structurally similar compounds in an affinity assay rapidly identified GLYN122. In vitro, GLYN122 directly binds and reduces mHTT and induces autophagy in neurons. In vivo, our results confirm that GLYN122 can reduce mHTT in the cortex and striatum of the R/2 mouse model of Huntington’s disease and subsequently improve motor symptoms. Thus, the in-vivo pharmacology profile of GLYN122 is a potential new preclinical candidate for the treatment of HD. |
format | Online Article Text |
id | pubmed-9668931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96689312022-11-18 Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease Galyan, Simon Marius Ewald, Collin Y. Jalencas, Xavier Masrani, Shyam Meral, Selin Mestres, Jordi Sci Rep Article Currently, there are no therapies available to modify the disease progression of Huntington’s disease (HD). Recent clinical trial failures of antisense oligonucleotide candidates in HD have demonstrated the need for new therapeutic approaches. Here, we developed a novel in-silico fragment scanning approach across the surface of mutant huntingtin (mHTT) polyQ and predicted four hit compounds. Two rounds of compound analoging using a strategy of testing structurally similar compounds in an affinity assay rapidly identified GLYN122. In vitro, GLYN122 directly binds and reduces mHTT and induces autophagy in neurons. In vivo, our results confirm that GLYN122 can reduce mHTT in the cortex and striatum of the R/2 mouse model of Huntington’s disease and subsequently improve motor symptoms. Thus, the in-vivo pharmacology profile of GLYN122 is a potential new preclinical candidate for the treatment of HD. Nature Publishing Group UK 2022-11-16 /pmc/articles/PMC9668931/ /pubmed/36385140 http://dx.doi.org/10.1038/s41598-022-21900-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Galyan, Simon Marius Ewald, Collin Y. Jalencas, Xavier Masrani, Shyam Meral, Selin Mestres, Jordi Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease |
title | Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease |
title_full | Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease |
title_fullStr | Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease |
title_full_unstemmed | Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease |
title_short | Fragment-based virtual screening identifies a first-in-class preclinical drug candidate for Huntington’s disease |
title_sort | fragment-based virtual screening identifies a first-in-class preclinical drug candidate for huntington’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668931/ https://www.ncbi.nlm.nih.gov/pubmed/36385140 http://dx.doi.org/10.1038/s41598-022-21900-2 |
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