Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences

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作者
Munazah Andrabi
Andrew Paul Hutchins
Diego Miranda-Saavedra
Hidetoshi Kono
Ruth Nussinov
Kenji Mizuguchi
Shandar Ahmad
机构
[1] National Institutes of Biomedical Innovation Health and Nutrition,Department of Biology
[2] Southern University of Science and Technology of China,World Premier International (WPI) Immunology Frontier Research Center (IFReC)
[3] Osaka University,Centro de Biología Molecular Severo Ochoa
[4] CSIC/Universidad Autónoma de Madrid,Department of Computer Science
[5] University of Oxford Wolfson Building,Molecular Modeling and Simulation (MMS) Group
[6] National Institutes for Quantum and Radiological Science and Technology,National Cancer Institute, Cancer and Inflammation Program
[7] Leidos Biomedical Research,Department of Biochemistry and Human Genetics
[8] Inc. Frederick,School of Computational and Integrative Sciences
[9] Sackler School of Medicine,Faculty of Biology,Medicine and Health, Michael Smith Building
[10] Tel Aviv University,undefined
[11] Jawaharlal Nehru University,undefined
[12] The University of Manchester,undefined
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摘要
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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