A structural view of microRNA-target recognition

It is well established that the correct identification of the messenger RNA targeted by a given microRNA (miRNA) is a difficult problem, and that available methods all suffer from low specificity. We hypothesize that the correct identification of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process. Therefore, we developed a strategy named MiREN for building and scoring three-dimensional models of the ternary complex formed by AGO, a miRNA and 22 nt of a target mRNA that putatively interacts with it. We show here that MiREN can be used to assess the likelihood that an RNA molecule is the target of a given miRNA and that this approach is more accurate than other existing methods, usually based on sequence or sequence-related features. Our results also suggest that AGO plays a relevant role in the selection of the miRNA targets. Our method can represent an additional step for refining predictions made by faster but less accurate classical methods for the identification of miRNA targets

SupeRNAlign: a new tool for flexible superposition of homologous RNA structures and inference of accurate structure-based sequence alignments

RNA has been found to play an ever-increasing role in a variety of biological processes. The function of most non-coding RNA molecules depends on their structure. Comparing and classifying macromolecular 3D structures is of crucial importance for structure-based function inference and it is used in the characterization of functional motifs and in structure prediction by comparative modeling. However, compared to the numerous methods for protein structure superposition, there are few tools dedicated to the superimposing of RNA 3D structures. Here, we present SupeRNAlign (v1.3.1), a new method for flexible superposition of RNA 3D structures, and SupeRNAlign-Coffee—a workflow that combines SupeRNAlign with T-Coffee for inferring structure-based sequence alignments. The methods have been benchmarked with eight other methods for RNA structural superposition and alignment. The benchmark included 151 structures from 32 RNA families (with a total of 1734 pairwise superpositions). The accuracy of superpositions was assessed by comparing structure-based sequence alignments to the reference alignments from the Rfam database. SupeRNAlign and SupeRNAlign-Coffee achieved significantly higher scores than most of the benchmarked methods: SupeRNAlign generated the most accurate sequence alignments among the structure superposition methods, and SupeRNAlign-Coffee performed best among the sequence alignment methods

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.:

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5-3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson-Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/

Biotechnology to Combat COVID-19

This book provides an inclusive and comprehensive discussion of the transmission, science, biology, genome sequencing, diagnostics, and therapeutics of COVID-19. It also discusses public and government health measures and the roles of media as well as the impact of society on the ongoing efforts to combat the global pandemic. It addresses almost every topic that has been studied so far in the research on SARS-CoV-2 to gain insights into the fundamentals of the disease and mitigation strategies. This volume is a useful resource for virologists, epidemiologists, biologists, medical professionals, public health and government professionals, and all global citizens who have endured and battled against the pandemic

Basic Cell and Molecular Biology 5e: What We Know and How We Find Out

https://dc.uwm.edu/biosci_facbooks_bergtrom/1014/thumbnail.jp

Annotated Cell and Molecular Biology 5e: What We Know and How We Found Out

https://dc.uwm.edu/biosci_facbooks_bergtrom/1013/thumbnail.jp

2021 - The Second Annual Fall Symposium of Student Scholars

The full program book from the Fall 2020 Symposium of Student Scholars, held on November 18, 2021. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1024/thumbnail.jp

RNA folding kinetics including pseudoknots

RNA Moleküle sind ein essenzieller Bestandteil biologischer Zellen. Ihre Vielfalt an Funktionen ist eng verknüpft mit der jeweiligen Sequenz und der daraus gebildeten Struktur. Der Großteil bekannter RNA Moleküle faltet in eine bestimmte energetisch stabile Struktur, bzw. ̈hnliche suboptimale Strukturen mit der gleichen biologischen Funktion. Riboswitches hingegen, eine bestimmte Gruppe von RNA Molekülen können zwischen zwei strukturell sehr verschiedenen Konformationen wechseln, wobei eine funktional ist und die andere nicht. Die Umfaltung solcher RNA-Schalter wird normalerweise durch verschiedenste Metaboliten ausgelöst die mit der RNA interagieren. Zellen nutzen dieses Prinzip um auf Signale aus der Umwelt effizient reagieren zu können. Im Zuge der synthetischen Biologie wurde eine neue Art von RNA-Schaltern entwickelt, die statt einem bestimmten Metaboliten ein anderes RNA Molekül erkennt [1]. Dieses Prinzip ziehlt weniger darauf ab Signale aus der Umgebung wahrzunehmen, sondern ein weiteres Level an Genregulation zu ermöglichen. In dieser Abeit wird das Program RNAscout.pl präsentiert, welches die Umfaltung zwischen verschiedenen RNA Strukturen berechnet und damit die Effizienz RNA-induzierter RNA-Schalter bewerten kann. Der zugrundeliegenede Algorithmus berechnet ein Set an Zwischenzuständen die sowohl energetisch günstig, als auch strukturell ähnlich zu den beiden stabilen Riboswitch-Konformationen sind. Basierend auf diesem Umfaltungsnetzwerk werden kinetische Simulationen gezeigt, bei denen der Umfaltungsweg des RNA-Schalters vorhergesagt wird. Des Weiteren wird das Programm pk findpath vorgestellt. Der zugrundeliegende Algorithmus berechnet den besten direkten Umfaltungspfad zwischen zwei RNA Strukturen mittels einer Breitensuche. Beide Programme, RNAscout.pl und pk findpath, werden verwendet um abzuschätzen ob natürliche RNA Moleküle optimiert sind um in ihre energetisch günstigste Konformation zu falten. Im Zuge dessen werden die Programme mit existierenden Programmen des Vienna RNA package [2] verglichen.RNA molecules are essential components of living cells. Their wide range of different functions depends on the sequence of nucleotides and the corresponding structure. The majority of known RNA molecules fold into their energetically most stable conformation, as well as structurally similar suboptimal conformations that do not alter the specific task of the molecule. However, there are RNA molecules which can switch between two structurally distant conformations one of which is functional, the other is not. The best known examples are riboswitches, which usually sense various kinds of metabolites from their environment that trigger the refolding from one conformation into the other. The rather new field of synthetic biology led to the construction of an example for a new type of riboswitches, which refold upon interaction with other RNA molecules [1]. Such RNA-triggered riboswitches are not aimed at sensing the environment, but expand the repertoire of gene-regulation. Inspired by this example, we present RNAscout.pl, a new program to study refolding between two RNA conformations, which can be used to estimate the performance of RNA-triggered riboswitches. The underlying algorithm heuristically computes a set of intermediate conformations that are energetically favorable and structurally related to both stable conformations of the riboswitch. Based on this refolding network, we show kinetic simulations that support the expected refolding path for our riboswitch example. Moreover, we present pk findpath, a breadth-first search algorithm to estimate direct paths (i. e. a small subset of all possible paths) between two different RNA conformations. Both programs RNAscout.pl and pk findpath will be used to estimate whether natural RNA molecules are optimized to fold into their energetically most stable conformation. Thereby, we compare the new programs against existing programs of the Vienna RNA package [2

Computer-based Design of β-sheet Containing Proteins

Protein design is an excellent test of the minimal determinants of protein structure. Although 70% of naturally occurring proteins contain β-sheets, most previous design efforts have been limited to α-helix bundle proteins or the redesign of naturally occurring proteins. Here, we test and develop computer based methods for designing proteins rich in β-strands. The molecular modeling program Rosetta was used for three separate design tasks: (1) the design of α/β and α+β proteins with a new method called SEWING, which builds proteins from pieces of naturally occurring proteins, (2) the stabilization of β-sheet proteins via the redesign of surface-facing residues, and (3) the de novo design of β-sandwich proteins. This research showed that it is possible to extend the SEWING method to non-α-helix proteins, allowing the incorporation of structural features found in nature, and that it is possible to dramatically boost protein thermal stability (> 25oC) with the redesign β-sheet surfaces. However, we also found that the de novo design of β-sandwich proteins still remains an elusive goal.Doctor of Philosoph