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A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3

The JAKs protein family is composed of four isoforms, and JAK3 has been regarded as a druggable target for the development of drugs to treat various diseases, including hematologic tumors, cancer, and neuronal death. Therefore, the discovery of JAK3 inhibitors with novel scaffolds possesses the pote...

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Autores principales: Wei, Juying, Pan, Youlu, Shen, Zheyuan, Shen, Liteng, Xu, Lei, Yu, Wenjuan, Huang, Wenhai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598672/
https://www.ncbi.nlm.nih.gov/pubmed/37886358
http://dx.doi.org/10.3389/fmed.2023.1182227
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author Wei, Juying
Pan, Youlu
Shen, Zheyuan
Shen, Liteng
Xu, Lei
Yu, Wenjuan
Huang, Wenhai
author_facet Wei, Juying
Pan, Youlu
Shen, Zheyuan
Shen, Liteng
Xu, Lei
Yu, Wenjuan
Huang, Wenhai
author_sort Wei, Juying
collection PubMed
description The JAKs protein family is composed of four isoforms, and JAK3 has been regarded as a druggable target for the development of drugs to treat various diseases, including hematologic tumors, cancer, and neuronal death. Therefore, the discovery of JAK3 inhibitors with novel scaffolds possesses the potential to provide additional options for drug development. This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. These techniques were used to identify inhibitors of JAK3 with a novel sketch from a specific “In-house” database. Using molecular docking with varying precision, MM/GBSA, geometric deep learning scoring, and manual selection, 10 compounds were obtained for subsequent biological evaluation. One of these 10 compounds, compound 8, was found to have inhibitory potency against JAK3 and the MOLM-16 cell line, providing a valuable lead compound for further development of JAK3 inhibitors. To gain a better understanding of the interaction between compound 8 and JAK3, molecular dynamics (MD) simulations were conducted to provide more details on the binding conformation of compound 8 with JAK3 to guide the subsequent structure optimization. In this article, we achieved compound 8 with a novel sketch possessing inhibitory bioactivity against JAK3, and it would provide an acceptable “hit” for further structure optimization and modification to develop JAK3 inhibitors.
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spelling pubmed-105986722023-10-26 A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3 Wei, Juying Pan, Youlu Shen, Zheyuan Shen, Liteng Xu, Lei Yu, Wenjuan Huang, Wenhai Front Med (Lausanne) Medicine The JAKs protein family is composed of four isoforms, and JAK3 has been regarded as a druggable target for the development of drugs to treat various diseases, including hematologic tumors, cancer, and neuronal death. Therefore, the discovery of JAK3 inhibitors with novel scaffolds possesses the potential to provide additional options for drug development. This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. These techniques were used to identify inhibitors of JAK3 with a novel sketch from a specific “In-house” database. Using molecular docking with varying precision, MM/GBSA, geometric deep learning scoring, and manual selection, 10 compounds were obtained for subsequent biological evaluation. One of these 10 compounds, compound 8, was found to have inhibitory potency against JAK3 and the MOLM-16 cell line, providing a valuable lead compound for further development of JAK3 inhibitors. To gain a better understanding of the interaction between compound 8 and JAK3, molecular dynamics (MD) simulations were conducted to provide more details on the binding conformation of compound 8 with JAK3 to guide the subsequent structure optimization. In this article, we achieved compound 8 with a novel sketch possessing inhibitory bioactivity against JAK3, and it would provide an acceptable “hit” for further structure optimization and modification to develop JAK3 inhibitors. Frontiers Media S.A. 2023-10-10 /pmc/articles/PMC10598672/ /pubmed/37886358 http://dx.doi.org/10.3389/fmed.2023.1182227 Text en Copyright © 2023 Wei, Pan, Shen, Shen, Xu, Yu and Huang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Wei, Juying
Pan, Youlu
Shen, Zheyuan
Shen, Liteng
Xu, Lei
Yu, Wenjuan
Huang, Wenhai
A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3
title A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3
title_full A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3
title_fullStr A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3
title_full_unstemmed A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3
title_short A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3
title_sort hybrid energy-based and ai-based screening approach for the discovery of novel inhibitors of jak3
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598672/
https://www.ncbi.nlm.nih.gov/pubmed/37886358
http://dx.doi.org/10.3389/fmed.2023.1182227
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