Measuring the dynamic surface accessibility of RNA with the small paramagnetic molecule TEMPOL

The surface accessibility of macromolecules plays a key role in modulating molecular recognition events. RNA is a complex and dynamic molecule involved in many aspects of gene expression. However, there are few experimental methods available to measure the accessible surface of RNA. Here, we investigate the accessible surface of RNA using NMR and the small paramagnetic molecule TEMPOL. We investigated two RNAs with known structures, one that is extremely stable and one that is dynamic. For helical regions, the TEMPOL probing data correlate well with the predicted RNA surface, and the method is able to distinguish subtle variations in atom depths, such as the relative accessibility of pyrimidine versus purine aromatic carbon atoms. Dynamic motions are also detected by TEMPOL probing, and the method accurately reports a previously characterized pH-dependent conformational transition involving formation of a protonated C–A pair and base flipping. Some loop regions are observed to exhibit anomalously high accessibility, reflective of motions that are not evident within the ensemble of NMR structures. We conclude that TEMPOL probing can provide valuable insights into the surface accessibility and dynamics of RNA, and can also be used as an independent means of validating RNA structure and dynamics in solution

NMR Studies on Structure and Dynamics of the Monomeric Derivative of BS-RNase: New Insights for 3D Domain Swapping

Three-dimensional domain swapping is a common phenomenon in pancreatic-like ribonucleases. In the aggregated state, these proteins acquire new biological functions, including selective cytotoxicity against tumour cells. RNase A is able to dislocate both N- and C-termini, but usually this process requires denaturing conditions. In contrast, bovine seminal ribonuclease (BS-RNase), which is a homo-dimeric protein sharing 80% of sequence identity with RNase A, occurs natively as a mixture of swapped and unswapped isoforms. The presence of two disulfides bridging the subunits, indeed, ensures a dimeric structure also to the unswapped molecule. In vitro, the two BS-RNase isoforms interconvert under physiological conditions. Since the tendency to swap is often related to the instability of the monomeric proteins, in these paper we have analysed in detail the stability in solution of the monomeric derivative of BS-RNase (mBS) by a combination of NMR studies and Molecular Dynamics Simulations. The refinement of NMR structure and relaxation data indicate a close similarity with RNase A, without any evidence of aggregation or partial opening. The high compactness of mBS structure is confirmed also by H/D exchange, urea denaturation, and TEMPOL mapping of the protein surface. The present extensive structural and dynamic investigation of (monomeric) mBS did not show any experimental evidence that could explain the known differences in swapping between BS-RNase and RNase A. Hence, we conclude that the swapping in BS-RNase must be influenced by the distinct features of the dimers, suggesting a prominent role for the interchain disulfide bridges

Prodepth: Predict Residue Depth by Support Vector Regression Approach from Protein Sequences Only

Residue depth (RD) is a solvent exposure measure that complements the information provided by conventional accessible surface area (ASA) and describes to what extent a residue is buried in the protein structure space. Previous studies have established that RD is correlated with several protein properties, such as protein stability, residue conservation and amino acid types. Accurate prediction of RD has many potentially important applications in the field of structural bioinformatics, for example, facilitating the identification of functionally important residues, or residues in the folding nucleus, or enzyme active sites from sequence information. In this work, we introduce an efficient approach that uses support vector regression to quantify the relationship between RD and protein sequence. We systematically investigated eight different sequence encoding schemes including both local and global sequence characteristics and examined their respective prediction performances. For the objective evaluation of our approach, we used 5-fold cross-validation to assess the prediction accuracies and showed that the overall best performance could be achieved with a correlation coefficient (CC) of 0.71 between the observed and predicted RD values and a root mean square error (RMSE) of 1.74, after incorporating the relevant multiple sequence features. The results suggest that residue depth could be reliably predicted solely from protein primary sequences: local sequence environments are the major determinants, while global sequence features could influence the prediction performance marginally. We highlight two examples as a comparison in order to illustrate the applicability of this approach. We also discuss the potential implications of this new structural parameter in the field of protein structure prediction and homology modeling. This method might prove to be a powerful tool for sequence analysis

An efficient algorithm for de novo peptide sequencing

In this paper we propose a new algorithm for the de novo peptide sequencing problem. This problem reconstructs a peptide sequence from a given tandem mass spectra data containing n peaks. We first build a directed acyclic graph G=(V, E) in O(n log n) time, where v in V such that v is a spectrum mass ion or that with complementary mass. The solutions of this problem are then given by the paths in the graph between two designated vertices. Unlike previous approaches, the proposed algorithm does not use dynamic programming, and is built in a progressive fashion using a priority queue, thus obtaining an improvement over other methods

An Algorithm to analyze MS/MS spectra for de novo peptide sequencing

We propose a polynomial time algorithm to analyze MS/MS spectra for de novo peptide sequencing

Three-dimensional Computation of Atom Depth in Complex Molecular Structures

Motivation: For a complex molecular system the delineation of atom-atom contacts, exposed surface and binding sites represents a fundamental step to predict its interaction with solvent, ligands and other molecules. Recently, atom depth has been also considered as an additional structural descriptor to correlate protein structure with folding and functional properties. The distance between an atom and the nearest water molecule or the closest surface dot has been proposed as a measure of the atom depth, but, in both cases, the three-dimensional character of depth is largely lost. To calculate atom depths in a way that the molecular shape can be taken into account, a new approach is here proposed. Results: An algorithm has been developed to calculate intersections between the molecular volume and spheres centered on the atoms whose depth has to be quantified. Many proteins with different size and shape have been chosen to compare the results obtained from distance-based and volume– based depth calculations. From the wealth of experimental data available for hen egg white lysozyme, H/D exchange rates and TEMPOL induced paramagnetic perturbations have been analyzed both in terms of depth indexes and of atom distances to the solvent accessible surface. The algorithm here proposed yields better correlations between experimental data and atom depth, particularly for those atoms which are located near to the protein surface. Availability: Instructions to obtain source code and the executable program are available eithe

Adepth: new representation and its implications for atomic depths of macromolecules

We applied the signed distance function (SDF) for representing the depths of atoms in a macromolecule. The calculations of SDF values were performed on grid points in a rectangular box that accommodates the macromolecule. The depth for an atom inside the molecule was then obtained as a result of tri-linear interpolation of SDF values at the nearest grid points surrounding the atom. For testing the performance of present program Adepth, we have constructed an artificial molecule whose atomic depths are known as the gold standard for accuracy assessments. On average, our results showed that Adepth reached an accuracy of 1.6% at 0.5 Å of grid spacing, whereas the current reference server DEPTH reached 7.5%. The Adepth program provides both depth and height representations; it is capable of computing iso-surfaces for atomic depths and presenting graphical view of macromolecular shape at some distance away from the surface. Web interface is available at http://biodev.cea.fr/adepth

Quantifying the relationship of protein burying depth and sequence

Protein burying depth (BD) is a structural descriptor that is exploited not only to find whether a residue is exposed or buried, but also to determine how deep a residue is buried. The widely used solvent accessible surface area is mainly focusing on the study of protein surface residues, while protein BD can provide more detailed information about the arrangement of buried residues, which may be used to study protein deep level structure and the formation of protein folding nucleus. In this work, we analyse the relationship of protein BD and sequences, and describe it by nonlinear functions estimated by support vector machines. We examine the functions by crossvalidation tests and find strong correlation between residue BD and local sequence environment. By further taking account the size of the molecule where a residue is located, we find that the correlation coefficient between predicted and observed depths improves from 0.60 to 0.65. Moreover, nearly half of the deepest 10% residues in a protein sequence can be correctly predicted. Our study suggests that a residue's burying extent is able to be predicted, to some degree, by itself and its local neighbouring residues. The methods used to estimate the sequence-depth functions are expected to become more useful in the investigation of protein structures and folding mechanism