Coarse-grained simulations of RNA and DNA duplexes

Although RNAs play many cellular functions little is known about the dynamics and thermodynamics of these molecules. In principle, all-atom molecular dynamics simulations can investigate these issues, but with current computer facilities, these simulations have been limited to small RNAs and to short times. HiRe-RNA, a recently proposed high-resolution coarse-grained for RNA that captures many geometric details such as base pairing and stacking, is able to fold RNA molecules to near-native structures in a short computational time. So far it had been applied to simple hairpins, and here we present its application to duplexes of a couple dozen nucleotides and show how with our model and with Replica Exchange Molecular Dynamics (REMD) we can easily predict the correct double helix from a completely random configuration and study the dissociation curve. To show the versatility of our model, we present an application to a double stranded DNA molecule as well. A reconstruction algorithm allows us to obtain full atom structures from the coarse-grained model. Through atomistic Molecular Dynamics (MD) we can compare the dynamics starting from a representative structure of a low temperature replica or from the experimental structure, and show how the two are statistically identical, highlighting the validity of a coarse-grained approach for structured RNAs and DNAs.Comment: 28 pages, 11 figure

Ab initio RNA folding

RNA molecules are essential cellular machines performing a wide variety of functions for which a specific three-dimensional structure is required. Over the last several years, experimental determination of RNA structures through X-ray crystallography and NMR seems to have reached a plateau in the number of structures resolved each year, but as more and more RNA sequences are being discovered, need for structure prediction tools to complement experimental data is strong. Theoretical approaches to RNA folding have been developed since the late nineties when the first algorithms for secondary structure prediction appeared. Over the last 10 years a number of prediction methods for 3D structures have been developed, first based on bioinformatics and data-mining, and more recently based on a coarse-grained physical representation of the systems. In this review we are going to present the challenges of RNA structure prediction and the main ideas behind bioinformatic approaches and physics-based approaches. We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in folding. Through examples from different models, we will point out the strengths of physics-based approaches, which are able not only to predict equilibrium structures, but also to investigate dynamical and thermodynamical behavior, and the open challenges to include more key interactions ruling RNA folding.Comment: 28 pages, 18 figure

Linking Gas-Phase and Solution-Phase Protein Unfolding via Mobile Proton Simulations

Native mass spectrometry coupled to ion mobility (IM-MS) combined with collisional activation (CA) of ions in the gas phase (in vacuo) is an important method for the study of protein unfolding. It has advantages over classical biophysical and structural techniques as it can be used to analyze small volumes of low-concentration heterogeneous mixtures while maintaining solution-like behavior and does not require labeling with fluorescent or other probes. It is unclear, however, whether the unfolding observed during collision activation experiments mirrors solution-phase unfolding. To bridge the gap between in vacuo and in-solution behavior, we use unbiased molecular dynamics (MD) to create in silico models of in vacuo unfolding of a well-studied protein, the N-terminal domain of ribosomal L9 (NTL9) protein. We utilize a mobile proton algorithm (MPA) to create 100 thermally unfolded and coulombically unfolded in silico models for observed charge states of NTL9. The unfolding behavior in silico replicates the behavior in-solution and is in line with the in vacuo observations; however, the theoretical collision cross section (CCS) of the in silico models was lower compared to that of the in vacuo data, which may reflect reduced sampling

WEBnm@ v2.0: Web server and services for comparing protein flexibility

Background: Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics–function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins. Results: We have developed an automated tool for comparative NMA of a set of pre-aligned protein structures. The user can submit a sequence alignment in the FASTA format and the corresponding coordinate files in the Protein Data Bank (PDB) format. The computed normalised squared atomic fluctuations and atomic deformation energies of the submitted structures can be easily compared on graphs provided by the web user interface. The web server provides pairwise comparison of the dynamics of all proteins included in the submitted set using two measures: the Root Mean Squared Inner Product and the Bhattacharyya Coefficient. The Comparative Analysis has been implemented on our web server for NMA, WEBnm@, which also provides recently upgraded functionality for NMA of single protein structures. This includes new visualisations of protein motion, visualisation of inter-residue correlations and the analysis of conformational change using the overlap analysis. In addition, programmatic access to WEBnm@ is now available through a SOAP-based web service. Webnm@ is available at http://apps.cbu.uib.no/webnma. Conclusion: WEBnm@ v2.0 is an online tool offering unique capability for comparative NMA on multiple protein structures. Along with a convenient web interface, powerful computing resources, and several methods for mode analyses, WEBnm@ facilitates the assessment of protein flexibility within protein families and superfamilies. These analyses can give a good view of how the structures move and how the flexibility is conserved over the different structures.publishedVersio

TEMPy2: a Python library with improved 3D electron microscopy density-fitting and validation workflows

Structural determination of molecular complexes by cryo-EM requires large, often complex processing of the image data that are initially obtained. Here, TEMPy2, an update of the TEMPy package to process, optimize and assess cryo-EM maps and the structures fitted to them, is described. New optimization routines, comprehensive automated checks and workflows to perform these tasks are described

Evaluation of Acquisition Modes for Semi-Quantitative Analysis by Targeted and Untargeted Mass Spectrometry

RATIONALE: Analyte quantitation by mass spectrometry underpins a diverse range of scientific endeavors. The fast growing field of mass spectrometer development has resulted in several targeted and untargeted acquisition modes suitable for these applications. By characterizing the acquisition methods available on an ion mobility (IM) enabled orthogonal acceleration time-of-flight (oa-ToF) instrument, the optimum modes for analyte semi-quantitation can be deduced. METHODS: Serial dilutions of commercial metabolite, peptide, or crosslinked peptide analytes were prepared in matrices of human urine or E. coli digest. Each analyte dilution was introduced into an IM separation enabled oa-ToF mass spectrometer by reversed phase liquid chromatography and electrospray ionization. Data were acquired for each sample in duplicate using nine different acquisition modes, including four IM enabled acquisitions modes, available on the mass spectrometer. RESULTS: Five (metabolite) or seven (peptide/crosslinked peptide) point calibration curves were prepared for analytes across each of the acquisition modes. A non-linear response was observed at high concentrations for some modes, attributed to saturation effects. Two correction methods, one MS1 isotope-correction and one MS2 ion intensity-correction, were applied to address this observation, resulting in an up to two-fold increase in dynamic range. By averaging the semi-quantitative results across analyte classes, two parameters, linear dynamic range (LDR) and lower limit of quantitation (LLOQ), were determined to evaluate each mode. CONCLUSION: Comparison of the acquisition modes revealed that data independent acquisition and parallel reaction monitoring methods are most robust for semi-quantitation when considering achievable LDR and LLOQ. IM enabled modes exhibited sensitivity increases, but a simultaneous reduction in dynamic range which required correction methods to recover. These findings will assist users in identifying the optimum acquisition mode for their analyte quantitation needs, supporting a diverse range of applications and providing guidance for future acquisition mode developments

Research data supporting "Multifunctional Energy Landscape for a DNA G-Quadruplex: An Evolved Molecular Switch"

Multifunctional Energy Landscape for a DNA G-Quadruplex: An Evolved Molecular SwitchThis record will be updated with publication details.This work was supported by the EPSRC [grant number EP/I001352/1]

Cryo-EM targets in CASP14.

Structures of seven CASP14 targets were determined using cryo-electron microscopy (cryo-EM) technique with resolution between 2.1 and 3.8 Å. We provide an evaluation of the submitted models versus the experimental data (cryo-EM density maps) and experimental reference structures built into the maps. The accuracy of models is measured in terms of coordinate-to-density and coordinate-to-coordinate fit. A-posteriori refinement of the most accurate models in their corresponding cryo-EM density resulted in structures that are close to the reference structure, including some regions with better fit to the density. Regions that were found to be less refineable correlate well with regions of high diversity between the CASP models and low goodness-of-fit to density in the reference structure