A novel Bayesian approach to drug design with simple and complex enzymes: Use with lens aldehyde dehydrogenase and the glyoxalase pathway

Purpose: Acquiring details of kinetic parameters of enzymes is crucial to biochemical understanding, drug development, and clinical diagnosis in ocular diseases. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. Methods: We have developed Bayesian utility functions to minimise kinetic parameter variance involving differentiation of model expressions and matrix inversion. These have been applied to the simple kinetics of the enzymes in the glyoxalase pathway (of importance in posttranslational modification of proteins in cataract), and the complex kinetics of lens aldehyde dehydrogenase (also of relevance to cataract). Results: Our successful application of Bayesian statistics has allowed us to identify a set of rules for designing optimum kinetic experiments iteratively. Most importantly, the distribution of points in the range is critical; it is not simply a matter of even or multiple increases. At least 60 % must be below the KM (or plural if more than one dissociation constant) and 40% above. This choice halves the variance found using a simple even spread across the range.With both the glyoxalase system and lens aldehyde dehydrogenase we have significantly improved the variance of kinetic parameter estimation while reducing the number and costs of experiments. Conclusions: We have developed an optimal and iterative method for selecting features of design such as substrate range, number of measurements and choice of intermediate points. Our novel approach minimises parameter error and costs, and maximises experimental efficiency. It is applicable to many areas of ocular drug design, including receptor-ligand binding and immunoglobulin binding, and should be an important tool in ocular drug discovery.

The impact of multiskilling on UK construction manpower

The overall significance of the construction and building services sector internationally cannot be overemphasised. In the UK, the industry currently accounts for 10% gross domestic product (GDP) and employs 2 million people, which is more than 1 in 14 of the total workforce. However, regardless of its output (approximately £65 billion annually) there has been a steady decline in the number of trade entrants into the construction and building services sector. Consequently, the available ‘pool of labour’ is inadequately resourced; productivity is low; the existing labour force is overstressed; there is an increase in site deaths; and a long-term labour shortage is envisaged. Today, the evidence seems to suggest that multiskilling is a tentative redress for ameliorating the skills crisis in the construction and building sectors. A 43-year time-series of data on 23 manpower attributes was evaluated as part of this investigation. The developed linear regression models show that the concept of multiskilling obeys the ‘law of diminishing returns'. That is, a weak relation was found between construction output and a three or more combination of manpower attributes. An optimisation model is prescribed for traditional trades.