Identification of target-specific bioisosteric fragments from ligand-protein crystallographic data

Bioisosteres are functional groups or atoms that are structurally different but that can form similar intermolecular interactions. Potential bioisosteres were identified here from analysing the X-ray crystallographic structures for sets of different ligands complexed with a fixed protein. The protein was used to align the ligands with each other, and then pairs of ligands compared to identify substructural features with high volume overlap that occurred in approximately the same region of geometric space. The resulting pairs of substructural features can suggest potential bioisosteric replacements for use in lead-optimisation studies. Experiments with 12 sets of ligand-protein complexes from the Protein Data Bank demonstrate the effectiveness of the procedure

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

Is the pharmacy profession innovative enough?: meeting the needs of Australian residents with chronic conditions and their carers using the nominal group technique

Background Community pharmacies are ideally located as a source of support for people with chronic conditions. Yet, we have limited insight into what innovative pharmacy services would support this consumer group to manage their condition/s. The aim of this study was to identify what innovations people with chronic conditions and their carers want from their ideal community pharmacy, and compare with what pharmacists and pharmacy support staff think consumers want. Methods We elicited ideas using the nominal group technique. Participants included people with chronic conditions, unpaid carers, pharmacists and pharmacy support staff, in four regions of Australia. Themes were identified via thematic analysis using the constant comparison method. Results Fifteen consumer/carer, four pharmacist and two pharmacy support staff groups were conducted. Two overarching themes were identified: extended scope of practice for the pharmacist and new or improved pharmacy services. The most innovative role for Australian pharmacists was medication continuance, within a limited time-frame. Consumers and carers wanted improved access to pharmacists, but this did not necessarily align with a faster or automated dispensing service. Other ideas included streamlined access to prescriptions via medication reminders, electronic prescriptions and a chronic illness card. Conclusions This study provides further support for extending the pharmacist’s role in medication continuance, particularly as it represents the consumer’s voice. How this is done, or the methods used, needs to optimise patient safety. A range of innovative strategies were proposed and Australian community pharmacies should advocate for and implement innovative approaches to improve access and ensure continuity of care

Endothelin receptor B antagonists decrease glioma cell viability independently of their cognate receptor

Background: Endothelin receptor antagonists inhibit the progression of many cancers, but research into their influence on glioma has been limited. Methods: We treated glioma cell lines, LN-229 and SW1088, and melanoma cell lines, A375 and WM35, with two endothelin receptor type B (ETRB)-specific antagonists, A-192621 and BQ788, and quantified viable cells by the capacity of their intracellular esterases to convert non-fluorescent calcein AM into green-fluorescent calcein. We assessed cell proliferation by labeling cells with carboxyfluorescein diacetate succinimidyl ester and quantifying the fluorescence by FACS analysis. We also examined the cell cycle status using BrdU/propidium iodide double staining and FACS analysis. We evaluated changes in gene expression by microarray analysis following treatment with A-192621 in glioma cells. We examined the role of ETRB by reducing its expression level using small interfering RNA (siRNA). Results: We report that two ETRB-specific antagonists, A-192621 and BQ788, reduce the number of viable cells in two glioma cell lines in a dose- and time-dependent manner. We describe similar results for two melanoma cell lines. The more potent of the two antagonists, A-192621, decreases the mean number of cell divisions at least in part by inducing a G2/M arrest and apoptosis. Microarray analysis of the effects of A-192621 treatment reveals up-regulation of several DNA damage-inducible genes. These results were confirmed by real-time RT-PCR. Importantly, reducing expression of ETRB with siRNAs does not abrogate the effects of either A-192621 or BQ788 in glioma or melanoma cells. Furthermore, BQ123, an endothelin receptor type A (ETRA)-specific antagonist, has no effect on cell viability in any of these cell lines, indicating that the ETRB-independent effects on cell viability exhibited by A-192621 and BQ788 are not a result of ETRA inhibition. Conclusion: While ETRB antagonists reduce the viability of glioma cells in vitro, it appears unlikely that this effect is mediated by ETRB inhibition or cross-reaction with ETRA. Instead, we present evidence that A-192621 affects glioma and melanoma viability by activating stress/DNA damage response pathways, which leads to cell cycle arrest and apoptosis. This is the first evidence linking ETRB antagonist treatment to enhanced expression of DNA damage-inducible genes

The role of Comprehension in Requirements and Implications for Use Case Descriptions

Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements. Therefore, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Hence, the paper examines guidelines which have been proposed, in this case for use case descriptions, and the extent to which they agree with discourse process theory; before suggesting refinements to the guidelines which attempt to utilise lessons learned from our richer understanding of the underlying discourse process theory. For example, we suggest subtly different sets of writing guidelines for the different tasks of requirements, specification and design

Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers

<p>Abstract</p> <p>Background</p> <p>Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques.</p> <p>Methods</p> <p>In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques.</p> <p>Results</p> <p>Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve.</p> <p>Conclusion</p> <p>Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.</p

Comparative epidemiologic characteristics of pertussis in 10 Central and Eastern European countries, 2000-2013

Publisher Copyright: © 2016 Heininger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.We undertook an epidemiological survey of the annual incidence of pertussis reported from 2000 to 2013 in ten Central and Eastern European countries to ascertain whether increased pertussis reports in some countries share common underlying drivers or whether there are specific features in each country. The annual incidence of pertussis in the participating countries was obtained from relevant government institutions and/or national surveillance systems. We reviewed the changes in the pertussis incidence rates in each country to explore differences and/or similarities between countries in relation to pertussis surveillance; case definitions for detection and confirmation of pertussis; incidence and number of cases of pertussis by year, overall and by age group; population by year, overall and by age group; pertussis immunization schedule and coverage, and switch from whole-cell pertussis vaccines (wP) to acellular pertussis vaccines (aP). There was heterogeneity in the reported annual incidence rates and trends observed across countries. Reported pertussis incidence rates varied considerably, ranging from 0.01 to 96 per 100,000 population, with the highest rates generally reported in Estonia and the lowest in Hungary and Serbia. The greatest burden appears for the most part in infants (<1 year) in Bulgaria, Hungary, Latvia, Romania, and Serbia, but not in the other participating countries where the burden may have shifted to older children, though surveillance of adults may be inappropriate. There was no consistent pattern associated with the switch from wP to aP vaccines on reported pertussis incidence rates. The heterogeneity in reported data may be related to a number of factors including surveillance system characteristics or capabilities, different case definitions, type of pertussis confirmation tests used, public awareness of the disease, as well as real differences in the magnitude of the disease, or a combination of these factors. Our study highlights the need to standardize pertussis detection and confirmation in surveillance programs across Europe, complemented with carefully-designed seroprevalence studies using the same protocols and methodologies.publishersversionPeer reviewe

The Epidemics of Donations: Logistic Growth and Power-Laws

This paper demonstrates that collective social dynamics resulting from individual donations can be well described by an epidemic model. It captures the herding behavior in donations as a non-local interaction between individual via a time-dependent mean field representing the mass media. Our study is based on the statistical analysis of a unique dataset obtained before and after the tsunami disaster of 2004. We find a power-law behavior for the distributions of donations with similar exponents for different countries. Even more remarkably, we show that these exponents are the same before and after the tsunami, which accounts for some kind of universal behavior in donations independent of the actual event. We further show that the time-dependent change of both the number and the total amount of donations after the tsunami follows a logistic growth equation. As a new element, a time-dependent scaling factor appears in this equation which accounts for the growing lack of public interest after the disaster. The results of the model are underpinned by the data analysis and thus also allow for a quantification of the media influence

Promoter prediction and annotation of microbial genomes based on DNA sequence and structural responses to superhelical stress

BACKGROUND: In our previous studies, we found that the sites in prokaryotic genomes which are most susceptible to duplex destabilization under the negative superhelical stresses that occur in vivo are statistically highly significantly associated with intergenic regions that are known or inferred to contain promoters. In this report we investigate how this structural property, either alone or together with other structural and sequence attributes, may be used to search prokaryotic genomes for promoters. RESULTS: We show that the propensity for stress-induced DNA duplex destabilization (SIDD) is closely associated with specific promoter regions. The extent of destabilization in promoter-containing regions is found to be bimodally distributed. When compared with DNA curvature, deformability, thermostability or sequence motif scores within the -10 region, SIDD is found to be the most informative DNA property regarding promoter locations in the E. coli K12 genome. SIDD properties alone perform better at detecting promoter regions than other programs trained on this genome. Because this approach has a very low false positive rate, it can be used to predict with high confidence the subset of promoters that are strongly destabilized. When SIDD properties are combined with -10 motif scores in a linear classification function, they predict promoter regions with better than 80% accuracy. When these methods were tested with promoter and non-promoter sequences from Bacillus subtilis, they achieved similar or higher accuracies. We also present a strictly SIDD-based predictor for annotating promoter sequences in complete microbial genomes. CONCLUSION: In this report we show that the propensity to undergo stress-induced duplex destabilization (SIDD) is a distinctive structural attribute of many prokaryotic promoter sequences. We have developed methods to identify promoter sequences in prokaryotic genomes that use SIDD either as a sole predictor or in combination with other DNA structural and sequence properties. Although these methods cannot predict all the promoter-containing regions in a genome, they do find large sets of potential regions that have high probabilities of being true positives. This approach could be especially valuable for annotating those genomes about which there is limited experimental data