Comparative Analysis of Credit Risk Models in Relation to SME Segment

The importance of credit risk management is well known and was deeply investigated by the banking industry. There is a pressure on financial institutions to still improve their credit risk management systems, so the credit risk of a bank is an unflagging object of discussion. The aim of this article to compare the predicting abilities of several bankruptcy models to the SME segment in the Czech Republic and its subsegments - medium sized, small and micro enterprises. We have focused on small and medium sized enterprises (SMEs) considering their fundamental role played in the Czech economy and the considerable attention placed on SMEs. We have chosen popular bankruptcy models that are often applied, namely the Altman Z-score, Altman model developed especially for SMEs in 2007, the Ohlson O-score, the Zmijewski’s model, the Taffler’s model, and the IN05 model. The basic form of the models was used as proposed by their authors. The results were compared using the contingency table and ROC curve. We have found that the best prediction models are Zmijewski´s and Ohlson´s models which use probit and logit methodologies and according to our analysis, their prediction ability is better than that of models based on discriminant analysis. Surprisingly, model IN05 designed for Czech companies provides average results only. One of the worst performing models is Altman 2007, which was created specifically for SMEs, but according to our analysis it only provides subordinates results

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field

Ekonomické zhodnocení Evropské měnové unie

This paper analyzes the impact of a monetary union. The author identifies the main costs and benefits of a monetary union. Costs are the result of a loss of macroeconomic stability, benefits result from microeconomic efficiency gains. The discussion has been based on an economic cost-benefit analysis. Countries may also decide to adopt a common curency for political reasons

Dependence of Company Size on Factors Influencing Bankruptcy

Research background: There is extensive empirical literature on default prediction methodologies. Many authors during the last fifty years have examined several possibilities to predict default or business failure. The reviews from the last years show that the closer the similarity of businesses, the greater accuracy of bankruptcy models. Purpose of the article: The aim of this article is finding if there exist different factors that could predict bankruptcy depending on the size of the company. Our motivation is to show if there exist differences when predicting bankruptcy according the size of the company. Methods: This paper focuses on the Czech economy, specifically at small and medium sized enterprises (SMEs). It is the ongoing research about the value of several popular bankruptcy models that are often applied, namely the Altman Z-score, the Ohlson O-score, the Zmijewski’s model, the Taffler’s model, and the IN05 model. We have used logistic regression and investigated around 2 800 companies, of which 642 failed during the period 2010 – 2017. Findings & Value added: Results of the analysis confirm research hypotheses that there exist different factors which could predict bankruptcy depending on the size of the company and exploit common used financial indicators to assess the probability of bankruptcy precisely. We have found that for the segment of micro-enterprises is necessary to pay attention to liquidity and profitability. Small enterprises emphasize to leverage, liquidity and profitability while the model developed for the segment of medium-sized enterprises measures most of all leverage, liquidity and activity

MD simulations reveal the basis for dynamic assembly of Hfq-RNA complexes.

The conserved protein Hfq is a key factor in the RNA-mediated control of gene expression in most known bacteria. The transient intermediates Hfq forms with RNA support intricate and robust regulatory networks. In Pseudomonas, Hfq recognizes repeats of adenine-purine-any nucleotide (ARN) in target mRNAs via its distal binding side, and together with the catabolite repression control (Crc) protein, assembles into a translation-repression complex. Earlier experiments yielded static, ensemble-averaged structures of the complex, but details of its interface dynamics and assembly pathway remained elusive. Using explicit solvent atomistic molecular dynamics simulations, we modeled the extensive dynamics of the Hfq-RNA interface and found implications for the assembly of the complex. We predict that syn/anti flips of the adenine nucleotides in each ARN repeat contribute to a dynamic recognition mechanism between the Hfq distal side and mRNA targets. We identify a previously unknown binding pocket that can accept any nucleotide and propose that it may serve as a 'status quo' staging point, providing nonspecific binding affinity, until Crc engages the Hfq-RNA binary complex. The dynamical components of the Hfq-RNA recognition can speed up screening of the pool of the surrounding RNAs, participate in rapid accommodation of the RNA on the protein surface, and facilitate competition among different RNAs. The register of Crc in the ternary assembly could be defined by the recognition of a guanine-specific base-phosphate interaction between the first and last ARN repeats of the bound RNA. This dynamic substrate recognition provides structural rationale for the stepwise assembly of multicomponent ribonucleoprotein complexes nucleated by Hfq-RNA binding

Synergy between NMR measurements and MD simulations of protein/RNA complexes: Application to the RRMs, the most common RNA Recognition Motifs

RNA Recognition Motif (RRM) proteins represent an abundant and variable class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 µs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM-RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein-RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements with mutant protein. We also predict that several segments of the protein-RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can reveal important information not obtainable from the NMR data alone, can be used to interpret the NMR atomistic models, and can provide qualified predictions. Finally, we propose a protocol for “MD-adapted structure ensemble” as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased µs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein-RNA complexe

Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations.Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement

An intricate balance of hydrogen bonding, ion atmosphere and dynamics facilitates a seamless uracil to cytosine substitution in the U-turn of the neomycin-sensing riboswitch

The neomycin sensing riboswitch is the smallest biologically functional RNA riboswitch, forming a hairpin capped with a U-turn loop—a well-known RNA motif containing a conserved uracil. It was shown previously that a U→C substitution of the eponymous conserved uracil does not alter the riboswitch structure due to C protonation at N3. Furthermore, cytosine is evolutionary permitted to replace uracil in other U-turns. Here, we use molecular dynamics simulations to study the molecular basis of this substitution in the neomycin sensing riboswitch and show that a structure-stabilizing monovalent cation-binding site in the wild-type RNA is the main reason for its negligible structural effect. We then use NMR spectroscopy to confirm the existence of this cation-binding site and to demonstrate its effects on RNA stability. Lastly, using quantum chemical calculations, we show that the cation-binding site is altering the electronic environment of the wild-type U-turn so that it is more similar to the cytosine mutant. The study reveals an amazingly complex and delicate interplay between various energy contributions shaping up the 3D structure and evolution of nucleic acids

Molecular basis for the increased affinity of an RNA recognition motif protein engineered to re-direct its specificity -PART 4

<p>Trajectory and input files for the simulation of the Rbfox* variant. </p