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The rules governing sequence-specific DNA-protein recognition are under a long-standing debate regarding the prevalence of base versus shape readout mechanisms to explain sequence specificity and of the conformational selection versus induced fit binding paradigms to explain binding-related conformational changes in DNA. Using a combination of atomistic simulations on a subset of representative sequences and mesoscopic simulations at the protein-DNA interactome level, we demonstrate the prevalence of the shape readout model in determining sequence-specificity and of the conformational selection paradigm in defining the general mechanism for binding-related conformational changes in DNA. Our results suggest that the DNA uses a double mechanism to adapt its structure to the protein: it moves along the easiest deformation modes to approach the bioactive conformation, while final adjustments require localized rearrangements at the base-pair step and backbone level. Our study highlights the large impact of B-DNA dynamics in modulating DNA-protein binding.
Pubmed ID: 31325439
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Web application for predicting transcription factors which bind a specific DNA site or motif, as well as DNA motifs or sites likely to be recognized by a specific DNA-binding protein. footprintDB also lists several databases and repositories relevant to DNA transcription.
View all literature mentionsSoftware toolkit for the comparative assessment of genome reconstructions from metagenome benchmark datasets. It provides performance metrics, results rankings, and comparative visualizations for assessing multiple programs or parameter effects.
View all literature mentionsSoftware suite that works by themselves, and with Amber20 itself. Can be used to carry out complete molecular dynamics simulations, with either explicit water or generalized Born solvent models.
View all literature mentionsSoftwar R package for comparative analysis of protein structures. Used to process, organize and explore protein structure, sequence and dynamics data. Used to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. Enables statistical and graphical power of R environment to work with biological sequence and structural data.
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