Structure of p53 binding to the BAX response element reveals DNA unwinding and compression to accommodate base-pair insertion

Chen, Yongheng; Zhang, Xiaojun; Machado, Ana Carolina Dantas; Ding, Yuan Chun; Chen, Zhuchu; Qin, Peter Z.; Rohs, Remo; Chen, Lin

doi:10.1093/nar/gkt584

Cited by 71 publications

(108 citation statements)

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“…Consequently, our best refinement had a SD of 5°for the priors on psi and rot and left the tilt angle unrestrained. The resulting map, at an estimated resolution of ∼15 Å, shows the same domain architecture as the known crystal structure of the DBD of p53 bound to dsDNA (35) and shows additional densities in both the front and the back of the complex (Fig. 3E).…”

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confidence: 54%

“…Its domain organization consists of an intrinsically disordered N-terminal transactivation domain, a proline-rich region, a structured DNAbinding domain (DBD), a tetramerization domain connected via a flexible linker, and an intrinsically disordered C-terminal regulatory domain (25). The structures of the DBD and the tetramerization domain of human p53 have been solved by X-ray crystallography and NMR (26)(27)(28)(29)(30)(31)(32)(33), as have tetrameric complexes of the DBD with fragments of DNA (34,35). The structures of full-length and truncated mutants of human p53 bound to DNA have been analyzed by negative-stain EM and small-angle X-ray diffraction (36,37), and the DBDs have the same symmetry as found in the crystallographic studies.…”

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confidence: 99%

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Design of a molecular support for cryo-EM structure determination

Martin

Bharat

Joerger

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Despite the recent rapid progress in cryo-electron microscopy (cryo-EM), there still exist ample opportunities for improvement in sample preparation. Macromolecular complexes may disassociate or adopt nonrandom orientations against the extended air-water interface that exists for a short time before the sample is frozen. We designed a hollow support structure using 3D DNA origami to protect complexes from the detrimental effects of cryo-EM sample preparation. For a first proof-of-principle, we concentrated on the transcription factor p53, which binds to specific DNA sequences on double-stranded DNA. The support structures spontaneously form monolayers of preoriented particles in a thin film of water, and offer advantages in particle picking and sorting. By controlling the position of the binding sequence on a single helix that spans the hollow support structure, we also sought to control the orientation of individual p53 complexes. Although the latter did not yet yield the desired results, the support structures did provide partial information about the relative orientations of individual p53 complexes. We used this information to calculate a tomographic 3D reconstruction, and refined this structure to a final resolution of ∼15 Å. This structure settles an ongoing debate about the symmetry of the p53 tetramer bound to DNA.cryo-EM | DNA-origami | single particle analysis | structural biology | p53 C ryo-electron microscopy (cryo-EM) structure determination of biological macromolecules is undergoing rapid progress. With the advent of efficient direct electron detectors and the development of powerful algorithms for image processing, numerous structures to near-atomic resolution have been reported in the past few years (1, 2). In cryo-EM single-particle analysis, solutions of purified protein and/or nucleic acid complexes are typically applied to a thin, amorphous carbon film with micrometer-sized holes in it that is held in place by a metal grid. Excess liquid is then blotted away with filter paper, and the sample is rapidly plunged in liquid ethane (3,4). This procedure ideally results in the formation of a film of vitreous ice that is only slightly thicker than the macromolecular complex of interest. Keeping the frozen sample at liquid nitrogen temperatures allows its insertion into the high vacuum of a transmission electron microscope and limits the effects of radiation damage by the electrons that are used for imaging (5). Images taken through the holes of the carbon film ideally contain 2D projections of many, assumedly identical copies of the macromolecular complex of interest, which are often called particles. Projections from different viewing directions can then be combined in a 3D reconstruction of the scattering potential of the molecule (6). If the resulting map approaches a resolution of 3 Å, it allows building an atomic model of the molecules, from which useful information about their function may be derived.A major hurdle in single-particle analysis is the need to recover the relative viewing angles...

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confidence: 54%

mentioning

confidence: 99%

Design of a molecular support for cryo-EM structure determination

Martin

Bharat

Joerger

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Four distinct shape featuresMinor Groove Width (MGW), Propeller Twist (ProT), Roll, and Helix Twist (HelT)-had been shown to be important for protein−DNA recognition in specific cases (22,(26)(27)(28). However, to date, a systematic and comprehensive survey of the value of shape-based models of DNA recognition has been lacking.…”

Section: Significancementioning

confidence: 99%

Quantitative modeling of transcription factor binding specificities using DNA shape

Zhou

Shen

Yang

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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DNA binding specificities of transcription factors (TFs) are a key component of gene regulatory processes. Underlying mechanisms that explain the highly specific binding of TFs to their genomic target sites are poorly understood. A better understanding of TF−DNA binding requires the ability to quantitatively model TF binding to accessible DNA as its basic step, before additional in vivo components can be considered. Traditionally, these models were built based on nucleotide sequence. Here, we integrated 3D DNA shape information derived with a high-throughput approach into the modeling of TF binding specificities. Using support vector regression, we trained quantitative models of TF binding specificity based on protein binding microarray (PBM) data for 68 mammalian TFs. The evaluation of our models included crossvalidation on specific PBM array designs, testing across different PBM array designs, and using PBM-trained models to predict relative binding affinities derived from in vitro selection combined with deep sequencing (SELEX-seq). Our results showed that shapeaugmented models compared favorably to sequence-based models. Although both k-mer and DNA shape features can encode interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space. In addition, analyzing the feature weights of DNA shape-augmented models uncovered TF family-specific structural readout mechanisms that were not revealed by the DNA sequence. As such, this work combines knowledge from structural biology and genomics, and suggests a new path toward understanding TF binding and genome function.protein−DNA recognition | statistical machine learning | support vector regression | protein binding microarray | DNA structure

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“…Indices of first and last p53 residues included in each structure are provided. In order (b-k), the PDB IDs of the models shown are: 1ycr, 2k8f, 2l14, 2ly4, 2b3g, 4hje, 1jsp, 1dt7, 2h2f, and 1h26 [113,115,116,[118][119][120][121][122][123][124].…”

Section: P53 Transcription Activation Domain (Tad)mentioning

confidence: 99%

Intrinsically Disordered Proteins: Where Computation Meets Experiment

2014

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Proteins are heteropolymers that play important roles in virtually every biological reaction. While many proteins have well-defined three-dimensional structures that are inextricably coupled to their function, intrinsically disordered proteins (IDPs) do not have a well-defined structure, and it is this lack of structure that facilitates their function. As many IDPs are involved in essential cellular processes, various diseases have been linked to their malfunction, thereby making them important drug targets. In this review we discuss methods for studying IDPs and provide examples of how computational methods can improve our understanding of IDPs. We focus on two intensely studied IDPs that have been implicated in very different pathologic pathways. The first, p53, has been linked to over 50% of human cancers, and the second, Amyloid-β (Aβ), forms neurotoxic aggregates in the brains of patients with Alzheimer's disease. We use these representative proteins to illustrate some of the challenges associated with studying IDPs and demonstrate how computational tools can be fruitfully applied to arrive at a more comprehensive understanding of these fascinating heteropolymers. OPEN ACCESSPolymers 2014, 6 2685

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Structure of p53 binding to the BAX response element reveals DNA unwinding and compression to accommodate base-pair insertion

Cited by 71 publications

References 42 publications

Design of a molecular support for cryo-EM structure determination

Design of a molecular support for cryo-EM structure determination

Quantitative modeling of transcription factor binding specificities using DNA shape

Intrinsically Disordered Proteins: Where Computation Meets Experiment

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