Cargando…

Prediction of protein stability changes upon single-point variant using 3D structure profile

Identifying protein thermodynamic stability changes upon single-point variants is crucial for studying mutation-induced alterations in protein biophysics, genomic variants, and mutation-related diseases. In the last decade, various computational methods have been developed to predict the effects of...

Descripción completa

Detalles Bibliográficos
Autores principales: Gong, Jianting, Wang, Juexin, Zong, Xizeng, Ma, Zhiqiang, Xu, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791599/
https://www.ncbi.nlm.nih.gov/pubmed/36582438
http://dx.doi.org/10.1016/j.csbj.2022.12.008
_version_ 1784859443254525952
author Gong, Jianting
Wang, Juexin
Zong, Xizeng
Ma, Zhiqiang
Xu, Dong
author_facet Gong, Jianting
Wang, Juexin
Zong, Xizeng
Ma, Zhiqiang
Xu, Dong
author_sort Gong, Jianting
collection PubMed
description Identifying protein thermodynamic stability changes upon single-point variants is crucial for studying mutation-induced alterations in protein biophysics, genomic variants, and mutation-related diseases. In the last decade, various computational methods have been developed to predict the effects of single-point variants, but the prediction accuracy is still far from satisfactory for practical applications. Herein, we review approaches and tools for predicting stability changes upon the single-point variant. Most of these methods require tertiary protein structure as input to achieve reliable predictions. However, the availability of protein structures limits the immediate application of these tools. To improve the performance of a computational prediction from a protein sequence without experimental structural information, we introduce a new computational framework: MU3DSP. This method assesses the effects of single-point variants on protein thermodynamic stability based on point mutated protein 3D structure profile. Given a protein sequence with a single variant as input, MU3DSP integrates both sequence-level features and averaged features of 3D structures obtained from sequence alignment to PDB to assess the change of thermodynamic stability induced by the substitution. MU3DSP outperforms existing methods on various benchmarks, making it a reliable tool to assess both somatic and germline substitution variants and assist in protein design. MU3DSP is available as an open-source tool at https://github.com/hurraygong/MU3DSP.
format Online
Article
Text
id pubmed-9791599
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Research Network of Computational and Structural Biotechnology
record_format MEDLINE/PubMed
spelling pubmed-97915992022-12-28 Prediction of protein stability changes upon single-point variant using 3D structure profile Gong, Jianting Wang, Juexin Zong, Xizeng Ma, Zhiqiang Xu, Dong Comput Struct Biotechnol J Research Article Identifying protein thermodynamic stability changes upon single-point variants is crucial for studying mutation-induced alterations in protein biophysics, genomic variants, and mutation-related diseases. In the last decade, various computational methods have been developed to predict the effects of single-point variants, but the prediction accuracy is still far from satisfactory for practical applications. Herein, we review approaches and tools for predicting stability changes upon the single-point variant. Most of these methods require tertiary protein structure as input to achieve reliable predictions. However, the availability of protein structures limits the immediate application of these tools. To improve the performance of a computational prediction from a protein sequence without experimental structural information, we introduce a new computational framework: MU3DSP. This method assesses the effects of single-point variants on protein thermodynamic stability based on point mutated protein 3D structure profile. Given a protein sequence with a single variant as input, MU3DSP integrates both sequence-level features and averaged features of 3D structures obtained from sequence alignment to PDB to assess the change of thermodynamic stability induced by the substitution. MU3DSP outperforms existing methods on various benchmarks, making it a reliable tool to assess both somatic and germline substitution variants and assist in protein design. MU3DSP is available as an open-source tool at https://github.com/hurraygong/MU3DSP. Research Network of Computational and Structural Biotechnology 2022-12-08 /pmc/articles/PMC9791599/ /pubmed/36582438 http://dx.doi.org/10.1016/j.csbj.2022.12.008 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Gong, Jianting
Wang, Juexin
Zong, Xizeng
Ma, Zhiqiang
Xu, Dong
Prediction of protein stability changes upon single-point variant using 3D structure profile
title Prediction of protein stability changes upon single-point variant using 3D structure profile
title_full Prediction of protein stability changes upon single-point variant using 3D structure profile
title_fullStr Prediction of protein stability changes upon single-point variant using 3D structure profile
title_full_unstemmed Prediction of protein stability changes upon single-point variant using 3D structure profile
title_short Prediction of protein stability changes upon single-point variant using 3D structure profile
title_sort prediction of protein stability changes upon single-point variant using 3d structure profile
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791599/
https://www.ncbi.nlm.nih.gov/pubmed/36582438
http://dx.doi.org/10.1016/j.csbj.2022.12.008
work_keys_str_mv AT gongjianting predictionofproteinstabilitychangesuponsinglepointvariantusing3dstructureprofile
AT wangjuexin predictionofproteinstabilitychangesuponsinglepointvariantusing3dstructureprofile
AT zongxizeng predictionofproteinstabilitychangesuponsinglepointvariantusing3dstructureprofile
AT mazhiqiang predictionofproteinstabilitychangesuponsinglepointvariantusing3dstructureprofile
AT xudong predictionofproteinstabilitychangesuponsinglepointvariantusing3dstructureprofile