Structure prediction of the druggable fragments in SARS-CoV-2 untranslated regions

The outbreak of the COVID-19 pandemic has led to intensive studies of both the structure and replication mechanism of SARS-CoV-2. In spite of some secondary structure experiments being carried out, the 3D structure of the key functional regions of the viral RNA has not yet been well understood. At the beginning of COVID-19 breakout, the RNA-Puzzles community attempted to envisage the three-dimensional structure of 5′- and 3′-Un-Translated Regions (UTRs) of the SARS-CoV-2 genome. Here, we report the results of this prediction challenge, presenting the methodologies developed by six participating groups and discussing 100 RNA 3D models (60 models of 5′-UTR and 40 of 3′-UTR) predicted through applying both human experts and automated server approaches. We describe the original protocol for the reference-free comparative analysis of RNA 3D structures designed especially for this challenge. We elaborate on the deduced consensus structure and the reliability of the predicted structural motifs. All the computationally simulated models, as well as the development and the testing of computational tools dedicated to 3D structure analysis, are available for further study.

KnotAli: Informed Energy Minimization Through the Use of Evolutionary Information

BackgroundImproving the prediction of structures, especially those containing pseudoknots (structures with crossing base pairs) is an ongoing challenge. Homology-based methods utilize structural similarities within a family to predict the structure. However, their prediction is limited to the consensus structure, and the quality of the alignment. Minimum free energy (MFE) based methods, on the other hand, do not rely on familial information and can predict structures of novel RNA molecules. Their prediction normally suffers from inaccuracies due to their underlying energy parameters. ResultsWe present a new method for prediction of RNA pseudoknotted secondary structures that combines the strengths of MFE prediction and alignment-based methods. KnotAli takes a multiple RNA sequence alignment and uses covariation and thermodynamic energy minimization to predict secondary structures for each individual sequence in the alignment. We compared KnotAli’s performance to that of three other alignment-based programs, on a large data set of 10 families with pseudoknotted and pseudoknot-free reference structures. We produced sequence alignments for each family using two well-known sequence aligners (MUSCLE and MAFFT). We found KnotAli to be superior in 6 of the 10 families for MUSCLE and 7 of the 10 for MAFFT. ConclusionsWe find KnotAli’s predictions to be less dependent on alignment quality. In particular, KnotAli is shown to have more accurate predictions compared to other leading methods as alignment quality deteriorates. KnotAli can be found online on github at https://github.com/mateog4712/KnotAli

Does risk matter for executive compensation?

Purpose The purpose of this study is to examine whether chief executive officer (CEOs) are paid for the systematic and/or unsystematic risks and whether there is any optimum risk premium level in the executive pay. Design/methodology/approach Firm and year fixed effect panel data regression was used to estimate the relationship between total CEO compensation and systematic (market) and unsystematic (firm) risks. Findings There is no nexus between CEO pay and unsystematic (diversifiable) risk; however, the association between CEO compensation and systematic (undiversifiable) risk is positively significant in line with agency theory. Moreover, it is revealed that this positive relationship has an optimum point (curvilinear). Research limitations/implications This paper contributes to the controversial argument in the literature by investigating the situation in the Swiss market. Switzerland is an exemplary country because of its direct democracy (consensus) structure for executive pay. This study is limited by the fact that only total CEO compensation is analyzed. Practical implications As a practical implication, it is shown that after the optimal point, the higher compensation does not motivate the CEOs to take higher risks and does not provide the organizations with any additional benefit. Originality/value The finding of this study supports agency theory’s risk premium assumption and provides additional evidence to the contradictory results in the literature with a new country setting that has paramount importance in executive compensation phenomena. It is a comparative finding with prior literature also outlines the future research area in the risk and compensation literature.

Splicing Endonuclease Is an Important Player in rRNA and tRNA Maturation in Archaea

In all three domains of life, tRNA genes contain introns that must be removed to yield functional tRNA. In archaea and eukarya, the first step of this process is catalyzed by a splicing endonuclease. The consensus structure recognized by the splicing endonuclease is a bulge-helix-bulge (BHB) motif which is also found in rRNA precursors. So far, a systematic analysis to identify all biological substrates of the splicing endonuclease has not been carried out. In this study, we employed CRISPRi to repress expression of the splicing endonuclease in the archaeon Haloferax volcanii to identify all substrates of this enzyme. Expression of the splicing endonuclease was reduced to 1% of its normal level, resulting in a significant extension of lag phase in H. volcanii growth. In the repression strain, 41 genes were down-regulated and 102 were up-regulated. As an additional approach in identifying new substrates of the splicing endonuclease, we isolated and sequenced circular RNAs, which identified excised introns removed from tRNA and rRNA precursors as well as from the 5′ UTR of the gene HVO_1309. In vitro processing assays showed that the BHB sites in the 5′ UTR of HVO_1309 and in a 16S rRNA-like precursor are processed by the recombinant splicing endonuclease. The splicing endonuclease is therefore an important player in RNA maturation in archaea.

Rapid Consensus Structure: Continuous Common Knowledge in Asynchronous Distributed Systems

A distributed system guarantees the acceptance of Byzantine fault tolerance (BFT) for information transmission. Practical BFT (pBFT) and asynchronous BFT (aBFT) are among the various available forms of BFT. Distributed systems generally share information with all participating nodes. After information is shared, the systems reshare it. Thus, ensuring BFT consumes a considerable amount of time. Herein, we propose Decision search protocols that apply the gossip protocol, denoted by DecisionBFT, for distributed networks with guaranteed BFT. Each protocol in DecisionBFT is completely asynchronous and leaderless; it has an eventual consensus but no round-robin or proof-of-work. The core concept of the proposed technology is the consensus structure, which is based on the directed acyclic graph (DAG) and gossip protocol. In the most general form, each node in the algorithm has a set of k neighbors of most preference. When receiving transactions, a node creates and connects an event block with all its neighbors. Each event block is signed by the hashes of the creating node and its k peers. The consensus structure of the event blocks utilizes a DAG, which guarantees aBFT. The proposed framework uses Lamport timestamps and concurrent common knowledge. Further, an example of a Decision search algorithm, based on the gossip protocol DecisionBFT, is presented. The proposed DecisionBFT protocol can reach a consensus when 2/3 of all participants agree to an event block without any additional communication overhead. The DecisionBFT protocol relies on a cost function to identify the k peers and generate the DAG-based consensus structure. By creating a dynamic flag table that stores connection information between blocks, the gossip protocol achieves a consensus in fewer steps than that in the case of the existing aBFT protocol.

Bayesian inference of chromatin structure ensembles from population-averaged contact data

Mounting experimental evidence suggests a role for the spatial organization of chromatin in crucial processes of the cell nucleus such as transcription regulation. Chromosome conformation capture techniques allow us to characterize chromatin structure by mapping contacts between chromosomal loci on a genome-wide scale. The most widespread modality is to measure contact frequencies averaged over a population of cells. Single-cell variants exist, but suffer from low contact numbers and have not yet gained the same resolution as population methods. While intriguing biological insights have already been garnered from ensemble-averaged data, information about three-dimensional (3D) genome organization in the underlying individual cells remains largely obscured because the contact maps show only an average over a huge population of cells. Moreover, computational methods for structure modeling of chromatin have mostly focused on fitting a single consensus structure, thereby ignoring any cell-to-cell variability in the model itself. Here, we propose a fully Bayesian method to infer ensembles of chromatin structures and to determine the optimal number of states in a principled, objective way. We illustrate our approach on simulated data and compute multistate models of chromatin from chromosome conformation capture carbon copy (5C) data. Comparison with independent data suggests that the inferred ensembles represent the underlying sample population faithfully. Harnessing the rich information contained in multistate models, we investigate cell-to-cell variability of chromatin organization into topologically associating domains, thus highlighting the ability of our approach to deliver insights into chromatin organization of great biological relevance.

Shared unfolding pathways of unrelated immunoglobulin-like β-sandwich proteins

The Dynameomics project contains native state and unfolding simulations of 807 protein domains, where each domain is representative of a different metafold; these metafolds encompass ~97% of protein fold space. There is a long-standing question in structural biology as to whether proteins in the same fold family share the same folding/unfolding characteristics. Using molecular dynamics simulations from the Dynameomics project, we conducted a detailed study of protein unfolding/folding pathways for 5 protein domains from the immunoglobulin (Ig)-like β-sandwich metafold (the highest ranked metafold in our database). The domains have sequence similarities ranging from 4 to 15% and are all from different SCOP superfamilies, yet they share the same overall Ig-like topology. Despite having very different amino acid sequences, the dominant unfolding pathway is very similar for the 5 proteins, and the secondary structures that are peripheral to the aligned, shared core domain add variability to the unfolding pathway. Aligned residues in the core domain display consensus structure in the transition state primarily through conservation of hydrophobic positions. Commonalities in the obligate folding nucleus indicate that insights into the major events in the folding/unfolding of other domains from this metafold may be obtainable from unfolding simulations of a few representative proteins.

Riboswitches in Archaea

Background: Riboswitches are cis-acting, non-coding RNA elements found in the 5’UTR of bacterial mRNA and 3’ UTR of eukaryotic mRNA, that fold in a complex manner to act as receptors for specific metabolites hence altering their conformation in response to the change in concentrations of a ligand or metabolite. Riboswitches function as gene regulators in numerous bacteria, archaea, fungi, algae and plants. Aim and Objective: This study identifies different classes of riboswitches in the Archaeal domain of life. Previous studies have suggested that riboswitches carry a conserved aptameric domain in different domains of life. Since Archaea are considered to be the most idiosyncratic organisms it was interesting to look for the conservation pattern of riboswitches in these obviously strange microorganisms. Materials and Methods: Completely sequenced Archaeal Genomes present in the NCBI repository were used for studying riboswitches and other ncRNAs. The sequence files in FASTA format were downloaded from NCBI Genome database and information related to these genomes was retrieved from GenBank. Three bioinformatics approaches were used namely, ab initio, consensus structure prediction and statistical model-based prediction for identifying riboswitches. Results: Archaeal genomes have a sporadic distribution of putative riboswitches like the TPP, FMN, Guanidine, Lysine and c-di-AMP riboswitches, which are known to occur in bacteria. Also, a class of riboswitch sensing c-di-GMP, a second messenger, has been identified in a few Archaeal organisms. Conclusion: This study clearly reveals that bioinformatics methods are likely to play a major role in identifying conserved riboswitches and in establishing how widespread these classes are in all domains of life, even though the final confirmation may come from wet lab methods.