For many macromolecular systems the accurate sampling of the relevant regions on the potential energy surface cannot be obtained by a single, long Molecular Dynamics (MD) trajectory. New approaches are required to promote more efficient sampling. We present the design and implementation of the Extensible Toolkit for Advanced Sampling and analYsis (Ex-TASY) for building and executing advanced sampling workflows on HPC systems. ExTASY provides Python based “templated scripts” that interface to an interoperable and high-performance pilot-based run time system, which abstracts the complexity of managing multiple simulations. ExTASY supports the use of existing highly-optimised parallel MD code and their coupling to analysis tools based upon collective coordinates which do not require a priori knowledge of the system to bias. We describe two workflows which both couple large “ensembles” of relatively short MD simulations with analysis tools to automatically analyse the generated trajectories and identify molecular conformational structures that will be used on-the-fly as new starting points for further “simulation-analysis” iterations. One of the workflows leverages the Locally Scaled Diffusion Maps technique; the other makes use of Complementary Coordinates techniques to enhance sampling and generate start-points for the next generation of MD simulations. We show that the ExTASY tools have been deployed on a range of HPC systems including ARCHER (Cray CX30), Blue Waters (Cray XE6/XK7), and Stampede (Linux cluster), and that good strong scaling can be obtained up to 1000s of MD simulations, independent of the size of each simulation. We discuss how ExTASY can be easily extended or modified by end-users to build their own workflows, and ongoing work to improve the usability and robustness of ExTASY.

Allergens are proteins that elicit T helper lymphocyte type 2 (Th2) responses culminating in IgE antibody production and allergic disease. However, we have no answer to the fundamental question of why certain proteins are allergens, while others are not. We hypothesized that analysis of the surface of diverse allergens may reveal common structural features which might enable them to be recognized as Th2-inducing antigens by cells of the innate immune system. We have therefore used the ConSurf server to search for allergen-specific motifs. This has enabled us to identify residue conservation patterns in the homologues of Ara t 8 (plant profilin), Act c 1 (actinidin), Bet v 1 (plant pathogenesis-related protein) and Ves v 5 (venom allergen). The results demonstrate the presence of allergen-specific patches consisting of an unusually high proportion of surface-exposed hydrophobic residues. The patches that have been identified may represent molecular patterns recognizable by cells of the innate immune system.