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FastGrow: on-the-fly growing and its application to DYRK1A
Fragment-based drug design is an established routine approach in both experimental and computational spheres. Growing fragment hits into viable ligands has increasingly shifted into the spotlight. FastGrow is an application based on a shape search algorithm that addresses this challenge at high spee...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512872/ https://www.ncbi.nlm.nih.gov/pubmed/35989379 http://dx.doi.org/10.1007/s10822-022-00469-y |
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author | Penner, Patrick Martiny, Virginie Bellmann, Louis Flachsenberg, Florian Gastreich, Marcus Theret, Isabelle Meyer, Christophe Rarey, Matthias |
author_facet | Penner, Patrick Martiny, Virginie Bellmann, Louis Flachsenberg, Florian Gastreich, Marcus Theret, Isabelle Meyer, Christophe Rarey, Matthias |
author_sort | Penner, Patrick |
collection | PubMed |
description | Fragment-based drug design is an established routine approach in both experimental and computational spheres. Growing fragment hits into viable ligands has increasingly shifted into the spotlight. FastGrow is an application based on a shape search algorithm that addresses this challenge at high speeds of a few milliseconds per fragment. It further features a pharmacophoric interaction description, ensemble flexibility, as well as geometry optimization to become a fully fledged structure-based modeling tool. All features were evaluated in detail on a previously reported collection of fragment growing scenarios extracted from crystallographic data. FastGrow was also shown to perform competitively versus established docking software. A case study on the DYRK1A kinase, using recently reported new chemotypes, illustrates FastGrow’s features in practice and its ability to identify active fragments. FastGrow is freely available to the public as a web server at https://fastgrow.plus/ and is part of the SeeSAR 3D software package. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10822-022-00469-y. |
format | Online Article Text |
id | pubmed-9512872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-95128722022-09-28 FastGrow: on-the-fly growing and its application to DYRK1A Penner, Patrick Martiny, Virginie Bellmann, Louis Flachsenberg, Florian Gastreich, Marcus Theret, Isabelle Meyer, Christophe Rarey, Matthias J Comput Aided Mol Des Article Fragment-based drug design is an established routine approach in both experimental and computational spheres. Growing fragment hits into viable ligands has increasingly shifted into the spotlight. FastGrow is an application based on a shape search algorithm that addresses this challenge at high speeds of a few milliseconds per fragment. It further features a pharmacophoric interaction description, ensemble flexibility, as well as geometry optimization to become a fully fledged structure-based modeling tool. All features were evaluated in detail on a previously reported collection of fragment growing scenarios extracted from crystallographic data. FastGrow was also shown to perform competitively versus established docking software. A case study on the DYRK1A kinase, using recently reported new chemotypes, illustrates FastGrow’s features in practice and its ability to identify active fragments. FastGrow is freely available to the public as a web server at https://fastgrow.plus/ and is part of the SeeSAR 3D software package. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10822-022-00469-y. Springer International Publishing 2022-08-22 2022 /pmc/articles/PMC9512872/ /pubmed/35989379 http://dx.doi.org/10.1007/s10822-022-00469-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Penner, Patrick Martiny, Virginie Bellmann, Louis Flachsenberg, Florian Gastreich, Marcus Theret, Isabelle Meyer, Christophe Rarey, Matthias FastGrow: on-the-fly growing and its application to DYRK1A |
title | FastGrow: on-the-fly growing and its application to DYRK1A |
title_full | FastGrow: on-the-fly growing and its application to DYRK1A |
title_fullStr | FastGrow: on-the-fly growing and its application to DYRK1A |
title_full_unstemmed | FastGrow: on-the-fly growing and its application to DYRK1A |
title_short | FastGrow: on-the-fly growing and its application to DYRK1A |
title_sort | fastgrow: on-the-fly growing and its application to dyrk1a |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512872/ https://www.ncbi.nlm.nih.gov/pubmed/35989379 http://dx.doi.org/10.1007/s10822-022-00469-y |
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