Quantifying intrinsic specificity: A potential complement to affinity in drug screening

We report here the investigation of a novel description of specificity in protein-ligand binding based on energy landscape theory. We define a new term, intrinsic specificity ratio (ISR), which describes the level of discrimination in binding free energies of the native basin for a protein-ligand complex from the weaker binding states of the same ligand. We discuss the relationship between the intrinsic specificity we defined here and the conventional definition of specificity. In a docking study of molecules with the enzyme COX-2, we demonstrate a statistical correspondence between ISR value and geometrical shapes of the small molecules binding to COX-2. We further observe that the known selective (nonselective) inhibitors of COX-2 have higher (lower) ISR values. We suggest that intrinsic specificity ratio may be a useful new criterion and a complement to affinity in drug screening and in searching for potential drug lead compounds.

Quantifying robustness and dissipation cost of yeast cell cycle network: The funneled energy landscape perspectives

We study the origin of robustness of yeast cell cycle cellular network through uncovering its underlying energy landscape. This is realized from the information of the steady-state probabilities by solving a discrete set of kinetic master equations for the network. We discovered that the potential landscape of yeast cell cycle network is funneled toward the global minimum, G1 state. The ratio of the energy gap between G1 and average versus roughness of the landscape termed as robustness ratio ( RR) becomes a quantitative measure of the robustness and stability for the network. The funneled landscape is quite robust against random perturbations from the inherent wiring or connections of the network. There exists a global phase transition between the more sensitive response or less self-degradation phase leading to underlying funneled global landscape with large RR, and insensitive response or more self-degradation phase leading to shallower underlying landscape of the network with small RR. Furthermore, we show that the more robust landscape also leads to less dissipation cost of the network. Least dissipation and robust landscape might be a realization of Darwinian principle of natural selection at cellular network level. It may provide an optimal criterion for network wiring connections and design.

Quantifying the kinetic paths of flexible biomolecular recognition

Biomolecular recognition often involves large conformational changes, sometimes even local unfolding. The identification of kinetic pathways has become a central issue in understanding the nature of binding. A new approach is proposed here to study the dynamics of this binding-folding process through the establishment of a path-integral framework on the underlying energy landscape. The dominant kinetic paths of binding and folding can be determined and quantified. The significant coupling between the binding and folding of biomolecules often exists in many important cellular processes. In this case, the corresponding kinetic paths of binding are shown to be intimately correlated with those of folding and the dynamics becomes quite cooperative. This implies that binding and folding happen concurrently. When the coupling between binding and folding is weak (strong), the kinetic process usually starts with significant folding (binding) first, with the binding (folding) later proceeding to the end. The kinetic rate can be obtained through the contributions from the dominant paths. The rate is shown to have a bell-shaped dependence on temperature in the concentration-saturated regime consistent with experiment. The changes of the kinetics that occur upon changing the parameters of the underlying binding-folding energy landscape are studied.

Quantifying the value of improved wind energy forecasts in a pool-based electricity market

This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.

Quantifying data quality for clinical trials using electronic data capture.

BACKGROUND: Historically, only partial assessments of data quality have been performed in clinical trials, for which the most common method of measuring database error rates has been to compare the case report form (CRF) to database entries and count discrepancies. Importantly, errors arising from medical record abstraction and transcription are rarely evaluated as part of such quality assessments. Electronic Data Capture (EDC) technology has had a further impact, as paper CRFs typically leveraged for quality measurement are not used in EDC processes. METHODS AND PRINCIPAL FINDINGS: The National Institute on Drug Abuse Treatment Clinical Trials Network has developed, implemented, and evaluated methodology for holistically assessing data quality on EDC trials. We characterize the average source-to-database error rate (14.3 errors per 10,000 fields) for the first year of use of the new evaluation method. This error rate was significantly lower than the average of published error rates for source-to-database audits, and was similar to CRF-to-database error rates reported in the published literature. We attribute this largely to an absence of medical record abstraction on the trials we examined, and to an outpatient setting characterized by less acute patient conditions. CONCLUSIONS: Historically, medical record abstraction is the most significant source of error by an order of magnitude, and should be measured and managed during the course of clinical trials. Source-to-database error rates are highly dependent on the amount of structured data collection in the clinical setting and on the complexity of the medical record, dependencies that should be considered when developing data quality benchmarks.

Cohabitation: quantifying an equitable share

Discusses the House of Lords judgment in Stack v Dowden on the factors the courts may consider when determining whether to rebut the presumption that former cohabitees, who were registered as joint legal owners of a property, were also joint beneficial owners with equal shares in the property. [From the Legal Journals Index]

Quantifying the beneficial interests of cohabitees

Discusses entitlements to a share of the sale proceeds of the family home where partners are cohabiting but not married and the property is registered in the name of one person only. Explains the obligation to establish that a cohabitee has an equitable interest in the property under the principles of constructive or resulting trusts. Considers how the court is able to quantify the respective shares, both before and after Oxley v Hiscock. [From the Legal Journals Index]

Quantifying ecosystem-level consequences of ocean acidification and warming by scaling up individual level responses of a predator snail and its trophic interactions

Understanding long‐term, ecosystem‐level impacts of climate change is challenging because experimental research frequently focuses on short‐term, individual‐level impacts in isolation. We address this shortcoming first through an interdisciplinary ensemble of novel experimental techniques to investigate the impacts of 14‐month exposure to ocean acidification and warming (OAW) on the physiology, activity, predatory behaviour and susceptibility to predation of an important marine gastropod (Nucella lapillus). We simultaneously estimated the potential impacts of these global drivers on N. lapillus population dynamics and dispersal parameters. We then used these data to parameterize a dynamic bioclimatic envelope model, to investigate the consequences of OAW on the distribution of the species in the wider NE Atlantic region by 2100. The model accounts also for changes in the distribution of resources, suitable habitat and environment simulated by finely resolved biogeochemical models, under three IPCC global emissions scenarios. The experiments showed that temperature had the greatest impact on individual‐level responses, while acidification had a similarly important role in the mediation of predatory behaviour and susceptibility to predators. Changes in Nucella predatory behaviour appeared to serve as a strategy to mitigate individual‐level impacts of acidification, but the development of this response may be limited in the presence of predators. The model projected significant large‐scale changes in the distribution of Nucella by the year 2100 that were exacerbated by rising greenhouse gas emissions. These changes were spatially heterogeneous, as the degree of impact of OAW on the combination of responses considered by the model varied depending on local‐environmental conditions and resource availability. Such changes in macro‐scale distributions cannot be predicted by investigating individual‐level impacts in isolation, or by considering climate stressors separately. Scaling up the results of experimental climate change research requires approaches that account for long‐term, multiscale responses to multiple stressors, in an ecosystem context.

Quantifying the impact of environmental variables upon catch-per-unit-effort of the Blue Shark Prionace glauca in the Western English Channel

The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

Quantifying the impact of environmental variables upon catch-per-unit-effort of the Blue Shark Prionace glauca in the Western English Channel

The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.