Abstract

Alternative splicing is an important mechanism that enhances protein functional diversity. To date, our understanding of alternative splicing variants has been based on mRNA transcript data, but due to the difficulty in predicting protein structures, protein tertiary structures have been largely unexplored. However, with the release of AlphaFold, which predicts three-dimensional models of proteins, this challenge is rapidly being overcome. Here, we present a dataset of 315 predicted structures of abnormal isoforms in 18 uveal melanoma patients based on second- and third-generation transcriptome-sequencing data. This information comprises a high-quality set of structural data on recurrent aberrant isoforms that can be used in multiple types of studies, from those aimed at revealing potential therapeutic targets to those aimed at recognizing of cancer neoantigens at the atomic level.

Details

Title
Structure prediction of novel isoforms from uveal melanoma by AlphaFold
Author
Zhang, Zhe 1 ; Li, Chen 2 ; Li, Qian 1 ; Su, Xiaoming 2 ; Li, Jiayi 3 ; Zhu, Lili 4 ; Lin, Xinhua (James) 2 ; Shen, Jianfeng 1   VIAFID ORCID Logo 

1  Shanghai Jiao Tong University School of Medicine, Department of Ophthalmology, Ninth People’s Hospital, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293); Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293); Shanghai Jiao Tong University, Institute of Translational Medicine, National Facility for Translational Medicine, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293) 
2  Shanghai Jiao Tong University, High Performance Computing Center, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293) 
3  Shanghai Jiao Tong University, State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293) 
4  Shanghai Jiao Tong University School of Medicine, Songjiang Research Institute and Songjiang Hospital, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293) 
Pages
513
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-023-02429-z
ProQuest document ID
2845977500
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.