Cargando…

Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target

The recent successes of AlphaFold and RoseTTAFold have demonstrated the value of AI methods in highly accurate protein structure prediction. Despite these advances, the role of these methods in the context of small-molecule drug discovery still needs to be thoroughly explored. In this study, we eval...

Descripción completa

Detalles Bibliográficos
Autores principales: Yin, Jian, Lei, Junkun, Yu, Jialin, Cui, Weiren, Satz, Alexander L., Zhou, Yifan, Feng, Hua, Deng, Jason, Su, Wenji, Kuai, Letian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9505260/
https://www.ncbi.nlm.nih.gov/pubmed/36144532
http://dx.doi.org/10.3390/molecules27185797
_version_ 1784796427819417600
author Yin, Jian
Lei, Junkun
Yu, Jialin
Cui, Weiren
Satz, Alexander L.
Zhou, Yifan
Feng, Hua
Deng, Jason
Su, Wenji
Kuai, Letian
author_facet Yin, Jian
Lei, Junkun
Yu, Jialin
Cui, Weiren
Satz, Alexander L.
Zhou, Yifan
Feng, Hua
Deng, Jason
Su, Wenji
Kuai, Letian
author_sort Yin, Jian
collection PubMed
description The recent successes of AlphaFold and RoseTTAFold have demonstrated the value of AI methods in highly accurate protein structure prediction. Despite these advances, the role of these methods in the context of small-molecule drug discovery still needs to be thoroughly explored. In this study, we evaluated whether the AI-based models can reliably reproduce the three-dimensional structures of protein–ligand complexes. The structure we chose was NLRP3, a challenging protein target in terms of obtaining a three-dimensional model both experimentally and computationally. The conformation of the binding pockets generated by the AI models was carefully characterized and compared with experimental structures. Further molecular docking results indicated that AI-predicted protein structures combined with molecular dynamics simulations offers a promising approach in small-molecule drug discovery.
format Online
Article
Text
id pubmed-9505260
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-95052602022-09-24 Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target Yin, Jian Lei, Junkun Yu, Jialin Cui, Weiren Satz, Alexander L. Zhou, Yifan Feng, Hua Deng, Jason Su, Wenji Kuai, Letian Molecules Article The recent successes of AlphaFold and RoseTTAFold have demonstrated the value of AI methods in highly accurate protein structure prediction. Despite these advances, the role of these methods in the context of small-molecule drug discovery still needs to be thoroughly explored. In this study, we evaluated whether the AI-based models can reliably reproduce the three-dimensional structures of protein–ligand complexes. The structure we chose was NLRP3, a challenging protein target in terms of obtaining a three-dimensional model both experimentally and computationally. The conformation of the binding pockets generated by the AI models was carefully characterized and compared with experimental structures. Further molecular docking results indicated that AI-predicted protein structures combined with molecular dynamics simulations offers a promising approach in small-molecule drug discovery. MDPI 2022-09-07 /pmc/articles/PMC9505260/ /pubmed/36144532 http://dx.doi.org/10.3390/molecules27185797 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
Yin, Jian
Lei, Junkun
Yu, Jialin
Cui, Weiren
Satz, Alexander L.
Zhou, Yifan
Feng, Hua
Deng, Jason
Su, Wenji
Kuai, Letian
Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target
title Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target
title_full Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target
title_fullStr Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target
title_full_unstemmed Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target
title_short Assessment of AI-Based Protein Structure Prediction for the NLRP3 Target
title_sort assessment of ai-based protein structure prediction for the nlrp3 target
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9505260/
https://www.ncbi.nlm.nih.gov/pubmed/36144532
http://dx.doi.org/10.3390/molecules27185797
work_keys_str_mv AT yinjian assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT leijunkun assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT yujialin assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT cuiweiren assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT satzalexanderl assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT zhouyifan assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT fenghua assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT dengjason assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT suwenji assessmentofaibasedproteinstructurepredictionforthenlrp3target
AT kuailetian assessmentofaibasedproteinstructurepredictionforthenlrp3target