Dataset Information

Predictable cholesterol binding sites in GPCRs lack consensus motifs.

ABSTRACT: A rich diversity of transmembrane G protein-coupled receptors (GPCRs) are used by eukaryotes to sense physical and chemical signals. In humans alone, 800 GPCRs comprise the largest and most therapeutically targeted receptor class. Recent advances in GPCR structural biology have produced hundreds of GPCR structures solved by X-ray diffraction and increasingly, cryo-electron microscopy (cryo-EM). Many of these structures are stabilized by site-specific cholesterol binding, but it is unclear whether these interactions are a product of recurring cholesterol-binding motifs and if observed patterns of cholesterol binding differ by experimental technique. Here, we comprehensively analyze the location and composition of cholesterol binding sites in the current set of 473 human GPCR structural chains. Our findings establish that cholesterol binds similarly in cryo-EM and X-ray structures and show that 92% of cholesterol molecules on GPCR surfaces reside in predictable locations that lack discernable cholesterol-binding motifs.

SUBMITTER: Taghon GJ

PROVIDER: S-EPMC9162085 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predictable cholesterol binding sites in GPCRs lack consensus motifs.

Taghon Geoffrey J GJ Rowe Jacob B JB Kapolka Nicholas J NJ Isom Daniel G DG

Structure (London, England : 1993) 20210127 5

A rich diversity of transmembrane G protein-coupled receptors (GPCRs) are used by eukaryotes to sense physical and chemical signals. In humans alone, 800 GPCRs comprise the largest and most therapeutically targeted receptor class. Recent advances in GPCR structural biology have produced hundreds of GPCR structures solved by X-ray diffraction and increasingly, cryo-electron microscopy (cryo-EM). Many of these structures are stabilized by site-specific cholesterol binding, but it is unclear whethe ...[more]

PMID: 33508215

Similar Datasets

Project description:Recent genome-scale ChIP-chip studies of transcription factors have shown that a low percentage of experimentally determined binding sites contain the consensus motif for the immunoprecipitated factor. In most cases, differences between in vivo target sites that contain or lack a consensus motif have not been explored. We have previously shown that most sites to which E2F family members are bound in vivo do not contain E2F consensus motifs. The main purpose of this study was to develop an understanding of how E2F binding specificity is achieved in vivo. In particular, we have addressed how E2F family members are recruited to core promoter regions that lack a consensus motif and are excluded from other regions that contain a consensus motif. Using promoter and ENCODE arrays, we have shown that the predominant factors specifying whether E2F is recruited to an in vivo binding site are a) the site must be in a core promoter and b) the promoter region must be utilized as a promoter by the transcriptional machinery in that particular cell type. We have tested three models for recruitment of E2F to core promoters lacking a consensus site, including a) indirect recruitment, b) looping to the core promoter mediated by an E2F bound to a distal consensus motif, and c) assisted binding of E2F to a site that weakly resembles an E2F consensus motif within the core promoter. To test these models, we developed a new in vivo assay, termed eChIP, which allows analysis of transcription factor binding to isolated promoter fragments. Our findings suggest that in vivo a) the presence of a consensus motif is not sufficient to recruit E2Fs, b) E2Fs can bind to isolated regions that lack a consensus motif, and c) binding can require regions other than the best match to the E2F PWM in the core promoter. Keywords: E2F, ChIP-chip, transcription factor binding, consensus motifs 37 ChIP-chip arrays (of these, 14 array sets are biological duplicates). 22 samples are included in this series, the rest can be found in supplementary info to the following papers: Xu 2007, Jin 2006, Komashko 2008

Project description:BackgroundClassically, models of DNA-transcription factor binding sites (TFBSs) have been based on relatively few known instances and have treated them as sites of fixed length using position weight matrices (PWMs). Various extensions to this model have been proposed, most of which take account of dependencies between the bases in the binding sites. However, some transcription factors are known to exhibit some flexibility and bind to DNA in more than one possible physical configuration. In some cases this variation is known to affect the function of binding sites. With the increasing volume of ChIP-seq data available it is now possible to investigate models that incorporate this flexibility. Previous work on variable length models has been constrained by: a focus on specific zinc finger proteins in yeast using restrictive models; a reliance on hand-crafted models for just one transcription factor at a time; and a lack of evaluation on realistically sized data sets.ResultsWe re-analysed binding sites from the TRANSFAC database and found motivating examples where our new variable length model provides a better fit. We analysed several ChIP-seq data sets with a novel motif search algorithm and compared the results to one of the best standard PWM finders and a recently developed alternative method for finding motifs of variable structure. All the methods performed comparably in held-out cross validation tests. Known motifs of variable structure were recovered for p53, Stat5a and Stat5b. In addition our method recovered a novel generalised version of an existing PWM for Sp1 that allows for variable length binding. This motif improved classification performance.ConclusionsWe have presented a new gapped PWM model for variable length DNA binding sites that is not too restrictive nor over-parameterised. Our comparison with existing tools shows that on average it does not have better predictive accuracy than existing methods. However, it does provide more interpretable models of motifs of variable structure that are suitable for follow-up structural studies. To our knowledge, we are the first to apply variable length motif models to eukaryotic ChIP-seq data sets and consequently the first to show their value in this domain. The results include a novel motif for the ubiquitous transcription factor Sp1.

Dataset Information

Predictable cholesterol binding sites in GPCRs lack consensus motifs.

Publications

Predictable cholesterol binding sites in GPCRs lack consensus motifs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets