Light-activated chemical probing of nucleobase solvent accessibility inside cells

Feng, Chao; Chan, Dalen; Joseph, Joby; Muuronen, Mikko; Coldren, William H.; Dai, Nan; Corrêa, Ivan R.; Furche, Filipp; Hadad, Christopher M.; Spitale, Robert C.

doi:10.1038/nchembio.2548

Cited by 54 publications

(78 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using LASER-derived C8-SASA as the target data, we then reweighted the conformational pool. To estimate C8-SASA from LASER reactivity data, we fit LASER reactivity data (5) to FreeSASAcomputed C8-SASAs for +SAM crystal structure (PDBID: 2GIS) to obtain a linear function that maps LASER reactivity to C8-SASA (21). The fit was then used to estimate C8-SASA for the -SAM and +SAM states from available -SAM and +SAM LASER reactivity data, respectively (5).…”

Section: Constructing Ensemble Of the Sam Riboswitchmentioning

confidence: 99%

“…Because the sites that are most "reactive" tend to be solvent-exposed, the reactivities obtained from these experiments provide an indirect "read-out" of the local solvent accessibility across the ensemble of structures populated by the RNA. The ensemble-averaged reactivities derived from light-activated structural examination of RNA (LASER) experiments, in particular, have been shown to correlate strongly with solvent accessible surface area (SASA) of the C8 atom in purine residues (5), suggesting that they might be useful for constructing such ensembles. Using SASA data derived from highly accessible measurements is advantageous as it provides a fast and efficient route to access structural ensembles that can be used to infer functionally relevant environmental responses in RNA, and to yield individual conformers for the structure-guided design of therapeutics.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Structural Ensembles of Ribonucleic Acids From Solvent Accessibility Data: Application to the S-Adenosylmethionine (SAM)-Responsive Riboswitch

Xie

Frank

2020

Preprint

View full text Add to dashboard Cite

Riboswitches are regulatory ribonucleic acid (RNA) elements that act as ligand-dependent conformational switches. In the apo form, the aptamer domain, the region of a riboswitch that binds to its cognate ligand, is dynamic, thus requiring an ensemble-representation of its structure. Analysis of such ensembles can provide molecular insights into the sensing mechanism and capabilities of riboswitches. Here, as a proof-of-concept, we constructed a pair of atomistic ensembles of the well-studied S-adenosylmethionine (SAM)responsive riboswitch in the absence (-SAM) and presence (+SAM) of SAM. To achieve this, we first generated a large conformational pool and then reweighted conformers in the pool using solvent accessible surface area (SASA) data derived from recently reported light-activated structural examination of RNA (LASER) reactivities, measured in the -SAM and +SAM states of the riboswitch. The di↵erences in the resulting -SAM and +SAM ensembles are consistent with a SAM-dependent reshaping of the free landscape of the riboswitch. Interestingly, within the -SAM ensemble, we identified a conformer that harbors a hidden binding pocket, which was discovered using ensemble docking. The method we have applied to the SAM riboswitch is general, and could, therefore, be used to construct atomistic ensembles for other riboswitches, and more broadly, other classes of structured RNAs.

show abstract

Section: Constructing Ensemble Of the Sam Riboswitchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structural Ensembles of Ribonucleic Acids From Solvent Accessibility Data: Application to the S-Adenosylmethionine (SAM)-Responsive Riboswitch

Xie

Frank

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…46 There is also a wide palette of cell-permeable probes that can be used to interrogate RNA folding in living cells, yielding information on how RNA structure changes in response to various environmental stimuli. 11,12,47 The probe selection is followed with chemical adduct detection, which involves processing modified RNA samples and then performing reverse transcription (RT) to record probe modifications as either truncations (RTstop) or mutations (RT-mutate) in the resultant cDNA sequences. SHAPE and mutational profiling (SHAPE-MaP) is an example of RTmutate methods that have recently been applied in living cells to resolve the secondary structure of lncRNAs with emerging roles in human diseases.…”

Section: Assessing Rna Potential As a Drug Target By Biochemical Probingmentioning

confidence: 99%

“…58,59 The novel chemical probing methodology, namely Light Activated Structural Examination of RNA (LASER), informs on RNA solvent accessibility, and as such provides an additional layer of structural information, particularly in RNA-ligand complexes. 60 LASER uses a light-generated nicotinoyl nitreniumion (NAz) 47 to form covalent adducts with the C8 position of adenosine and guanosine, which can be quantified by either RT-stop or RT-mutate deep-sequencing. The authors verified the applicability of the method for ligand binding detection by probing the binding of an antimicrobial peptide on rRNA.…”

Section: Assessing Rna Potential As a Drug Target By Biochemical Probingmentioning

confidence: 99%

Unveiling the druggable RNA targets and small molecule therapeutics

Sztuba-Solińska

Chávez-Calvillo

Cline

2019

Bioorganic & Medicinal Chemistry

View full text Add to dashboard Cite

Keywords:RNA structure and function RNA interactions Epitranscriptomics Small molecules RNA-based therapeutics RNA in disease Drug target A B S T R A C T The increasing appreciation for the crucial roles of RNAs in infectious and non-infectious human diseases makes them attractive therapeutic targets. Coding and non-coding RNAs frequently fold into complex conformations which, if effectively targeted, offer opportunities to therapeutically modulate numerous cellular processes, including those linked to undruggable protein targets. Despite the considerable skepticism as to whether RNAs can be targeted with small molecule therapeutics, overwhelming evidence suggests the challenges we are currently facing are not outside the realm of possibility. In this review, we highlight the most recent advances in molecular techniques that have sparked a revolution in understanding the RNA structure-to-function relationship. We bring attention to the application of these modern techniques to identify druggable RNA targets and to assess small molecule binding specificity. Finally, we discuss novel screening methodologies that support RNA drug discovery and present examples of therapeutically valuable RNA targets. RNA as a drug targetThe vast diversity of RNAs expanding beyond coding transcripts to several classes of ncRNAs that vary in length, biogenesis, polarity, and putative functions, increases the repertoire of druggable targets. 19,20 Here, specific RNA properties contribute to its attractive, yet challenging makeup as a target molecule. RNA can form complex three-dimensional structures through canonical Watson-Crick base pairing and complex tertiary interactions that are mediated by non-canonical bonds. Such structures can be as intricate and stable as those formed by proteins and can recognize small-molecule ligands, other nucleic acids, and/or proteins with high affinity and specificity. [21][22][23][24] At the same time, the highly dynamic conformation and repetitive character of its surface presents difficulties for drug design. 25,26 In addition, many putative small molecule-binding pockets in RNA are much more polar and solvent exposed than binding sites on proteins, complicating ligand design efforts. Compounding these issues, most target RNAs are expressed at low levels, with the exception of ribosomal (rRNA) and transfer (tRNA) RNAs, which constitute 80-90% and 10-15% of total cellular RNA, respectively. 27 Other abundant RNAs, such as messenger (mRNA), small nuclear (snRNA), and small nucleolar (snoRNA) are present at levels that are about 1-2 orders of magnitude lower than rRNA and tRNA. Certain small RNAs, such as micro (miRNA) and piwi (piRNAs) can be present at very high levels; however, this appears to be cell type dependent. One should keep in mind that if the RNA has catalytic activity or if it acts as a scaffold to regulate https://doi.

show abstract

“…104 Light-activated structural examination of RNA (LASER) is another novel experimental technique that provides solvent accessibility inside cells at the nucleotide level for medium-sized RNA molecules. 119 Also recently and already in the frontier between bioinformatics and modeling, different groups have used co-evolutionary data to bias CG models to establish 3D contacts, as in the case of NAST, or the newest 3dRNA from Xiao and collaborators. 120 Beyond the evident progress, CG RNA models still face many challenges.…”

Section: What Are We Losing and What Are We Gaining On Coarse Graininmentioning

confidence: 99%

Modeling, Simulations, and Bioinformatics at the Service of RNA Structure

Dans

Gallego

Balaceanu

et al. 2019

Chem

View full text Add to dashboard Cite

Although chemically close to DNA, RNA can adopt a wide range of structures from regular helices to complex globular conformations, showing a complexity similar to that of proteins. The determination of the structure of RNA molecules, crucial for functional understanding, is severely handicapped by their size and flexibility, which makes the systematic use of experimental approaches difficult. Simulation techniques are also suffering from very severe problems related to the accuracy of the methods and their ability to sample a large and complex conformational landscape. Here, we systematically review recent approaches created to reduce the shortcoming of the current generation of simulation methods-from highly accurate models able to deal with small systems to coarse-grained approaches that are less accurate but applicable to dealing with large models. WHAT HAVE WE LEARNED ABOUT RNA STRUCTURE FROM QM AND QM/MM METHODS?Physics teaches us that ab initio quantum mechanics (QM) can represent with high accuracy any biomolecular system, among them RNA. Unfortunately, because of their computational cost, the practical application of ab initio QM formalisms to large systems such as RNA is often impossible. In fact, even simpler QM methods such as those based on density functional theory (DFT) fail to treat systems larger than 10 2 atoms, several orders of magnitude less than the size required to study RNAs in solution. 1 Further simplifications of the basic QM formalism, such as those implicit in semiempirical (SE) methods, can extend the range of applicability of QM theory but at the expense of an expected loss of accuracy. 2 High-level QM and DFT calculations have had a central role in the development and validation of recent RNA force fields (FFs; see below). A recent example is the B97D3/AUG-CC-PVTZ study of the backbone and glycosidic torsions by Aytenfisu et al., 3 who highlighted systematic errors in current RNA FFs that might lead to incorrect molecular dynamics (MD) trajectories. Different conclusions were reached by the group led by Sponer, who again used DFT calculations as a reference, namely that the errors in current RNA FFs are related to imbalanced hydration and not to intrinsic errors in the classical gas phase Hamiltonian. 4 The same group recently studied 46 different backbone conformations of the UpU dinucleotide step (see Figure 1) by using a variety of QM methods from the state-of-the-art CCSD(T) to the latest-generation SE algorithms, 5 providing the community with an invaluable dataset for refinement of RNA FFs. Very recently our group used DFT/MM (density functional theory and molecular mechanics) calculations to fit some dihedrals directly for QM calculations in solution, opening a new approach to using DFT calculations in the refinement of RNA FF (see the next section). 6 The Bigger PictureRNAs are the ultimate frontier of structural biology. They are large and complex molecules that can adopt complex structures displaying a wide variety of functions from carriers of genetic information to regu...

show abstract

Light-activated chemical probing of nucleobase solvent accessibility inside cells

Cited by 54 publications

References 62 publications

Structural Ensembles of Ribonucleic Acids From Solvent Accessibility Data: Application to the S-Adenosylmethionine (SAM)-Responsive Riboswitch

Structural Ensembles of Ribonucleic Acids From Solvent Accessibility Data: Application to the S-Adenosylmethionine (SAM)-Responsive Riboswitch

Unveiling the druggable RNA targets and small molecule therapeutics

Modeling, Simulations, and Bioinformatics at the Service of RNA Structure

Contact Info

Product

Resources

About