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PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions
Protein-DNA interactions play important roles in regulations of many vital cellular processes, including transcription, translation, DNA replication and recombination. Sequence variants occurring in these DNA binding proteins that alter protein-DNA interactions may cause significant perturbations or...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303081/ https://www.ncbi.nlm.nih.gov/pubmed/30533007 http://dx.doi.org/10.1371/journal.pcbi.1006615 |
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author | Zhang, Ning Chen, Yuting Zhao, Feiyang Yang, Qing Simonetti, Franco L. Li, Minghui |
author_facet | Zhang, Ning Chen, Yuting Zhao, Feiyang Yang, Qing Simonetti, Franco L. Li, Minghui |
author_sort | Zhang, Ning |
collection | PubMed |
description | Protein-DNA interactions play important roles in regulations of many vital cellular processes, including transcription, translation, DNA replication and recombination. Sequence variants occurring in these DNA binding proteins that alter protein-DNA interactions may cause significant perturbations or complete abolishment of function, potentially leading to diseases. Developing a mechanistic understanding of impacts of variants on protein-DNA interactions becomes a persistent need. To address this need we introduce a new computational method PremPDI that predicts the effect of single missense mutation in the protein on the protein-DNA interaction and calculates the quantitative binding affinity change. The PremPDI method is based on molecular mechanics force fields and fast side-chain optimization algorithms with parameters optimized on experimental sets of 219 mutations from 49 protein-DNA complexes. PremPDI yields a very good agreement between predicted and experimental values with Pearson correlation coefficient of 0.71 and root-mean-square error of 0.86 kcal mol(-1). The PremPDI server could map mutations on a structural protein-DNA complex, calculate the associated changes in binding affinity, determine the deleterious effect of a mutation, and produce a mutant structural model for download. PremPDI can be applied to many tasks, such as determination of potential damaging mutations in cancer and other diseases. PremPDI is available at http://lilab.jysw.suda.edu.cn/research/PremPDI/. |
format | Online Article Text |
id | pubmed-6303081 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63030812019-01-08 PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions Zhang, Ning Chen, Yuting Zhao, Feiyang Yang, Qing Simonetti, Franco L. Li, Minghui PLoS Comput Biol Research Article Protein-DNA interactions play important roles in regulations of many vital cellular processes, including transcription, translation, DNA replication and recombination. Sequence variants occurring in these DNA binding proteins that alter protein-DNA interactions may cause significant perturbations or complete abolishment of function, potentially leading to diseases. Developing a mechanistic understanding of impacts of variants on protein-DNA interactions becomes a persistent need. To address this need we introduce a new computational method PremPDI that predicts the effect of single missense mutation in the protein on the protein-DNA interaction and calculates the quantitative binding affinity change. The PremPDI method is based on molecular mechanics force fields and fast side-chain optimization algorithms with parameters optimized on experimental sets of 219 mutations from 49 protein-DNA complexes. PremPDI yields a very good agreement between predicted and experimental values with Pearson correlation coefficient of 0.71 and root-mean-square error of 0.86 kcal mol(-1). The PremPDI server could map mutations on a structural protein-DNA complex, calculate the associated changes in binding affinity, determine the deleterious effect of a mutation, and produce a mutant structural model for download. PremPDI can be applied to many tasks, such as determination of potential damaging mutations in cancer and other diseases. PremPDI is available at http://lilab.jysw.suda.edu.cn/research/PremPDI/. Public Library of Science 2018-12-11 /pmc/articles/PMC6303081/ /pubmed/30533007 http://dx.doi.org/10.1371/journal.pcbi.1006615 Text en © 2018 Zhang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zhang, Ning Chen, Yuting Zhao, Feiyang Yang, Qing Simonetti, Franco L. Li, Minghui PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions |
title | PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions |
title_full | PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions |
title_fullStr | PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions |
title_full_unstemmed | PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions |
title_short | PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions |
title_sort | prempdi estimates and interprets the effects of missense mutations on protein-dna interactions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303081/ https://www.ncbi.nlm.nih.gov/pubmed/30533007 http://dx.doi.org/10.1371/journal.pcbi.1006615 |
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