Development of user-friendly, high throughput screening for ligands and inhibitors of carbohydrate modifying enzymes

This paper describes the impact of cloud computing and the use of GPUs on the performance of Autodock and Gromacs respectively. Cloud computing was applicable to reducing the ‘‘tail’’ seen in running Autodock on desktop grids and the GPU version of Gromacs showed significant improvement over the CPU version. A large (200,000 compounds) library of small molecules, seven sialic acid analogues of the putative substrate and 8000 sugar molecules were converted into pdbqt format and used to interrogate the Trichomonas vaginalis neuraminidase using Autodock Vina. Good binding energy was noted for some of the small molecules (~-9 kcal/mol), but the sugars bound with affinity of less than -7.6 kcal/mol. The screening of the sugar library resulted in a ‘‘top hit’’ with a-2,3-sialyllacto-N-fucopentaose III, a derivative of the sialyl Lewisx structure and a known substrate of the enzyme. Indeed in the top 100 hits 8 were related to this structure. A comparison of Autodock Vina and Autodock 4.2 was made for the high affinity small molecules and in some cases the results were superimposable whereas in others, the match was less good. The validation of this work will require extensive ‘‘wet lab’’ work to determine the utility of the workflow in the prediction of potential enzyme inhibitors.

Impact of energy-using product policies

Energy-using products (EuPs), such as domestic appliances, audio-visual and ICT equipment contribute significantly to CO2 emissions, both in the domestic and non-domestic sectors. Policies that encourage the use of more energy efficient products can therefore generate significant reductions in overall energy consumption and hence, CO2 emissions. To the extent that these policies cause an increase the average production cost of EuPs, they may impose economic costs on producers, or on consumers, or on both. In this theoretical paper, an adaptation of a simple vertical product differentiation model – in which products are characterised in terms of their quality and their energy consumption – is used to analyse the impact of the different EuP polices on product innovation and to assess the resultant economic impacts on producers and consumers. It is shown that whereas the imposition of a binding product standard for energy efficiency unambiguously reduces aggregate profit and increases the average market price in the absence of any learning effects, the introduction or strengthening of demand-side measures (such as energy labelling) may reduce, or increase, aggregate profit. Even in the case where the overall impact is unambiguously negative, the effects of product innovation and learning can be in either direction.