Predicting coaxial helical stacking in RNA junctions

RNA junctions are important structural elements that form when three or more helices come together in space in the tertiary structures of RNA molecules. Determining their structural configuration is important for predicting RNA 3D structure. We introduce a computational method to predict, at the secondary structure level, the coaxial helical stacking arrangement in junctions, as well as classify the junction topology. Our approach uses a data mining approach known as random forests, which relies on a set of decision trees trained using length, sequence and other variables specified for any given junction. The resulting protocol predicts coaxial stacking within three- and four-way junctions with an accuracy of 81% and 77%, respectively; the accuracy increases to 83% and 87%, respectively, when knowledge from the junction family type is included. Coaxial stacking predictions for the five to ten-way junctions are less accurate (60%) due to sparse data available for training. Additionally, our application predicts the junction family with an accuracy of 85% for three-way junctions and 74% for four-way junctions. Comparisons with other methods, as well applications to unsolved RNAs, are also presented. The web server Junction-Explorer to predict junction topologies is freely available at: http://bioinformatics.njit.edu/junction

Dynamic Energy Landscapes of Riboswitches Help Interpret Conformational Rearrangements and Function

Riboswitches are RNAs that modulate gene expression by ligand-induced conformational changes. However, the way in which sequence dictates alternative folding pathways of gene regulation remains unclear. In this study, we compute energy landscapes, which describe the accessible secondary structures for a range of sequence lengths, to analyze the transcriptional process as a given sequence elongates to full length. In line with experimental evidence, we find that most riboswitch landscapes can be characterized by three broad classes as a function of sequence length in terms of the distribution and barrier type of the conformational clusters: low-barrier landscape with an ensemble of different conformations in equilibrium before encountering a substrate; barrier-free landscape in which a direct, dominant “downhill” pathway to the minimum free energy structure is apparent; and a barrier-dominated landscape with two isolated conformational states, each associated with a different biological function. Sharing concepts with the “new view” of protein folding energy landscapes, we term the three sequence ranges above as the sensing, downhill folding, and functional windows, respectively. We find that these energy landscape patterns are conserved in various riboswitch classes, though the order of the windows may vary. In fact, the order of the three windows suggests either kinetic or thermodynamic control of ligand binding. These findings help understand riboswitch structure/function relationships and open new avenues to riboswitch design

The new community rules: marketing on the social web

Blogs, networking sites, and other examples of the social web provide businesses with a largely untapped marketing channel for products and services. But how do you take advantage of them? With The New Community Rules, you''ll understand how social web technologies work, and learn the most practical and effective ways to reach people who frequent these sites. Written by an expert in social media and viral marketing, this book cuts through the hype and jargon to give you intelligent advice and strategies for positioning your business on the social web, with case studies that show how other

Collagenase Administration into Periodontal Ligament Reduces the Forces Required for Tooth Extraction in an Ex situ Porcine Jaw Model

Minimally invasive exodontia is among the long-sought-for development aims of safe dental medicine. In this paper, we aim, for the first time, to examine whether the enzymatic disruption of the periodontal ligament fibers reduces the force required for tooth extraction. To this end, recombinantly expressed clostridial collagenase G variant purified from Escherichia coli was injected into the periodontal ligament of mesial and distal roots of the first and second split porcine mandibular premolars. The vehicle solution was injected into the corresponding roots on the contralateral side. Following sixteen hours, the treated mandibles were mounted on a loading machine to measure the extraction force. In addition, the effect of the enzyme on the viability of different cell types was evaluated. An average reduction of 20% in the applied force (albeit with a large variability of 50 to 370 newton) was observed for the enzymatically treated roots, reaching up to 50% reduction in some cases. Importantly, the enzyme showed only a minor and transient effect on cellular viability, without any signs of toxicity. Using an innovative model enabling the analytical measurement of extraction forces, we show, for the first time, that the enzymatic disruption of periodontal ligament fibers substantially reduces the force required for tooth extraction. This novel technique brings us closer to atraumatic exodontia, potentially reducing intra- and post-operative complications and facilitating subsequent implant placement. The development of novel enzymes with enhanced activity may further simplify the tooth extraction process and present additional clinical relevance for the broad range of implications in the oral cavity