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PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions.
- Source :
-
PLoS Computational Biology . 12/11/2018, Vol. 14 Issue 12, p1-15. 15p. 1 Diagram, 3 Charts, 2 Graphs. - Publication Year :
- 2018
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Abstract
- 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 . [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 14
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 133487075
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1006615