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.