ArticleScientific reports2017
Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Article
- Incorporating Sequence-Dependent DNA Shape and Dynamics into Transcriptome Data Analysis.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Article
- Dissecting and predicting different types of binding sites in nucleic acids based on structural information.Briefings in bioinformatics · 2022Article
- DNA-MBF1 study using molecular dynamics simulations : On the road to understanding the heat stress response in DNA-protein interactions in plants.European biophysics journal : EBJ · 2021Article
- MTTFsite: cross-cell type TF binding site prediction by using multi-task learning.Bioinformatics (Oxford, England) · 2019Article
- Comprehensive study of nuclear receptor DNA binding provides a revised framework for understanding receptor specificity.Nature communications · 2019Article
- NextPBM: a platform to study cell-specific transcription factor binding and cooperativity.Nucleic acids research · 2019Article
- Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding.Nucleic acids research · 2017Article
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Authors and funding
7 authors.
Funding
Abstract
DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.
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