diffBUM-HMM: a robust statistical modeling approach for detecting RNA flexibility changes in high-throughput structure probing data

AbstractAdvancing RNA structural probing techniques with next-generation sequencing has generated demands for complementary computational tools to robustly extract RNA structural information amidst sampling noise and variability. We present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. diffBUM-HMM is widely compatible, accounting for sampling variation and sequence coverage biases, and displays higher sensitivity than existing methods while robust against false positives. Our analyses of datasets generated with a variety of RNA probing chemistries demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and RNA-binding protein binding sites.

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Differential BUM-HMM: a robust statistical modelling approach for detecting RNA flexibility changes in high-throughput structure probing data

10.1101/2020.07.30.229179 ◽

2020 ◽

Author(s):

Paolo Marangio ◽

Ka Ying Toby Law ◽

Guido Sanguinetti ◽

Sander Granneman

Keyword(s):

Protein Binding ◽

High Throughput ◽

Conformational Changes ◽

Binding Sites ◽

Rna Structure ◽

Structural Changes ◽

High Throughput Sequencing ◽

Structural Information ◽

Protein Binding Sites ◽

Structure Probing

Combining RNA structure probing with high-throughput sequencing technologies has greatly enhanced our ability to analyze RNA structure at transcriptome scale. However, the high level of noise and variability encountered in these data call for the development of computational tools that robustly extract RNA structural information. Here we present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. DiffBUM-HMM is compatible with a wide variety of high-throughput RNA structure probing data, taking into consideration biological variation, sequence coverage and sequence representation biases. We demonstrate that, compared to the existing approaches, diffBUM-HMM displays higher sensitivity while calling virtually no false positives. DiffBUM-HMM analysis of ex vivo and in vivo Xist SHAPE-MaP data detected many more RNA structural differences, involving mostly single-stranded nucleotides located at or near protein-binding sites. Collectively, our analyses demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and reinforce the notion that RNA structure probing is a very powerful tool for identifying protein-binding sites.

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FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing

Nature Methods ◽

10.1038/nmeth.1529 ◽

2010 ◽

Vol 7 (12) ◽

pp. 995-1001 ◽

Cited By ~ 219

Author(s):

Jason G Underwood ◽

Andrew V Uzilov ◽

Sol Katzman ◽

Courtney S Onodera ◽

Jacob E Mainzer ◽

...

Keyword(s):

High Throughput ◽

Rna Structure ◽

High Throughput Sequencing ◽

Structure Probing

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Protein-assisted RNA fragment docking (RnaX) for modeling RNA–protein interactions using ModelX

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1910999116 ◽

2019 ◽

Vol 116 (49) ◽

pp. 24568-24573 ◽

Cited By ~ 1

Author(s):

Javier Delgado Blanco ◽

Leandro G. Radusky ◽

Damiano Cianferoni ◽

Luis Serrano

Keyword(s):

Conformational Changes ◽

Protein Design ◽

Protein Interactions ◽

Rna Binding ◽

Structural Information ◽

Conformational Dynamics ◽

Computational Cost ◽

Regulation Of Transcription ◽

Sequence Specificity ◽

Protein Interfaces

RNA–protein interactions are crucial for such key biological processes as regulation of transcription, splicing, translation, and gene silencing, among many others. Knowing where an RNA molecule interacts with a target protein and/or engineering an RNA molecule to specifically bind to a protein could allow for rational interference with these cellular processes and the design of novel therapies. Here we present a robust RNA–protein fragment pair-based method, termed RnaX, to predict RNA-binding sites. This methodology, which is integrated into the ModelX tool suite (http://modelx.crg.es), takes advantage of the structural information present in all released RNA–protein complexes. This information is used to create an exhaustive database for docking and a statistical forcefield for fast discrimination of true backbone-compatible interactions. RnaX, together with the protein design forcefield FoldX, enables us to predict RNA–protein interfaces and, when sufficient crystallographic information is available, to reengineer the interface at the sequence-specificity level by mimicking those conformational changes that occur on protein and RNA mutagenesis. These results, obtained at just a fraction of the computational cost of methods that simulate conformational dynamics, open up perspectives for the engineering of RNA–protein interfaces.

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RNA structure framework: automated transcriptome-wide reconstruction of RNA secondary structures from high-throughput structure probing data

Bioinformatics ◽

10.1093/bioinformatics/btv571 ◽

2015 ◽

Vol 32 (3) ◽

pp. 459-461 ◽

Cited By ~ 10

Author(s):

Danny Incarnato ◽

Francesco Neri ◽

Francesca Anselmi ◽

Salvatore Oliviero

Keyword(s):

High Throughput ◽

Rna Structure ◽

Secondary Structures ◽

Rna Secondary Structures ◽

Structure Probing ◽

Structure Framework

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Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments

Nature Methods ◽

10.1038/nmeth.4068 ◽

2016 ◽

Vol 14 (1) ◽

pp. 83-89 ◽

Cited By ~ 17

Author(s):

Alina Selega ◽

Christel Sirocchi ◽

Ira Iosub ◽

Sander Granneman ◽

Guido Sanguinetti

Keyword(s):

Statistical Modeling ◽

High Throughput ◽

Rna Structure ◽

Structure Probing

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ssHMM: Extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data

10.1101/076034 ◽

2016 ◽

Cited By ~ 1

Author(s):

David Heller ◽

Martin Vingron ◽

Ralf Krestel ◽

Uwe Ohler ◽

Annalisa Marsico

Keyword(s):

High Throughput ◽

Rna Structure ◽

Rna Binding ◽

Rna Binding Proteins ◽

Synthetic Data ◽

Sequence Motif ◽

Sequence Motifs ◽

Sequence Structure ◽

Rna Motif ◽

Post Transcriptional Regulation

AbstractRNA-binding proteins (RBPs) play important roles in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. To which extent RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders which produce informative motifs and simultaneously capture the relationship between primary sequence and different RNA secondary structures are missing. We developed ssHMM, an RNA motif finder that combines a hidden Markov model (HMM) with Gibbs sampling to learn the joint sequence and structure binding preferences of RBPs from high-throughput data, such as CLIP-Seq sequences, and visualizes them as a graph. Evaluations on synthetic data showed that ssHMM reliably recovers fuzzy sequence motifs in 80 to 100% of the cases. It produces motifs with higher information content than existing tools and is faster than other methods on large datasets. Examples of new sequence-structure motifs identified by ssHMM for uncharacterized RBPs are also discussed. ssHMM is freely available on Github at https://github.molgen.mpg.de/heller/ssHMM.

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Conformational dynamics of 1-deoxy-d-xylulose 5-phosphate synthase on ligand binding revealed by H/D exchange MS

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1619981114 ◽

2017 ◽

Vol 114 (35) ◽

pp. 9355-9360 ◽

Cited By ~ 21

Author(s):

Jieyu Zhou ◽

Luying Yang ◽

Alicia DeColli ◽

Caren Freel Meyers ◽

Natalia S. Nemeria ◽

...

Keyword(s):

Conformational Changes ◽

Bound States ◽

Structural Changes ◽

Conformational Dynamics ◽

Kinetic Mechanism ◽

Vitamin B ◽

Sequence Coverage ◽

Thiamin Diphosphate ◽

Key Enzyme ◽

Phosphate Synthase

The enzyme 1-deoxy-d-xylulose 5-phosphate synthase (DXPS) is a key enzyme in the methylerythritol 4-phosphate pathway and is a target for the development of antibiotics, herbicides, and antimalarial drugs. DXPS catalyzes the formation of 1-deoxy-d-xylulose 5-phosphate (DXP), a branch point metabolite in isoprenoid biosynthesis, and is also used in the biosynthesis of thiamin (vitamin B1) and pyridoxal (vitamin B6). Previously, we found that DXPS is unique among the superfamily of thiamin diphosphate (ThDP)-dependent enzymes in stabilizing the predecarboxylation intermediate, C2-alpha-lactyl-thiamin diphosphate (LThDP), which has subsequent decarboxylation that is triggered by d-glyceraldehyde 3-phosphate (GAP). Herein, we applied hydrogen–deuterium (H/D) exchange MS (HDX-MS) of full-length Escherichia coli DXPS to provide a snapshot of the conformational dynamics of this enzyme, leading to the following conclusions. (i) The high sequence coverage of DXPS allowed us to monitor structural changes throughout the entire enzyme, including two segments (spanning residues 183–238 and 292–317) not observed by X-ray crystallography. (ii) Three regions of DXPS (spanning residues 42–58, 183–199, and 278–298) near the active center displayed both EX1 (monomolecular) and EX2 (bimolecuar) H/D exchange (HDX) kinetic behavior in both ligand-free and ligand-bound states. All other peptides behaved according to the common EX2 kinetic mechanism. (iii) The observation of conformational changes on DXPS provides support for the role of conformational dynamics in the DXPS mechanism: The closed conformation of DXPS is critical for stabilization of LThDP, whereas addition of GAP converts DXPS to the open conformation that coincides with decarboxylation of LThDP and DXP release.

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Conformational dynamics of androgen receptors bound to agonists and antagonists

Scientific Reports ◽

10.1038/s41598-021-94707-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hyo Jin Gim ◽

Jiyong Park ◽

Michael E. Jung ◽

K. N. Houk

Keyword(s):

Conformational Changes ◽

Structural Changes ◽

Structural Integrity ◽

Structural Information ◽

Close Contact ◽

Conformational Dynamics ◽

Principal Component ◽

Binding Pocket ◽

Structural Basis ◽

Accelerated Molecular Dynamics

AbstractThe androgen receptor (AR) is critical in the progression of prostate cancer (PCa). Small molecule antagonists that bind to the ligand binding domain (LBD) of the AR have been successful in treating PCa. However, the structural basis by which the AR antagonists manifest their therapeutic efficacy remains unclear, due to the lack of detailed structural information of the AR bound to the antagonists. We have performed accelerated molecular dynamics (aMD) simulations of LBDs bound to a set of ligands including a natural substrate (dihydrotestosterone), an agonist (RU59063) and three antagonists (bicalutamide, enzalutamide and apalutamide) as well as in the absence of ligand (apo). We show that the binding of AR antagonists at the substrate binding pocket alter the dynamic fluctuations of H12, thereby disrupting the structural integrity of the agonistic conformation of AR. Two antagonists, enzalutamide and apalutamide, induce considerable structural changes to the agonist conformation of LBD, when bound close to H12 of AR LBD. When the antagonists bind to the pocket with different orientations having close contact with H11, no significant conformational changes were observed, suggesting the AR remains in the functionally activated (agonistic) state. The simulations on a drug resistance mutant F876L bound to enzalutamide demonstrated that the mutation stabilizes the agonistic conformation of AR LBD, which compromises the efficacy of the antagonists. Principal component analysis (PCA) of the structural fluctuations shows that the binding of enzalutamide and apalutamide induce conformational fluctuations in the AR, which are markedly different from those caused by the agonist as well as another antagonist, bicalutamide. These fluctuations could only be observed with the use of aMD.

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