SUMMARYMolecular docking simulations have high potential to contribute to a wide area of molecular and biomedical research in various disciplines including molecular biology, drug design, environmental studies and psychology. Conducting large‐scale molecular docking experiments requires a vast amount of computing resources. Several types of distributed computing infrastructures have been investigated and utilized recently to conduct such simulations, including service and desktop grid systems or local clusters. This paper investigates and analyses how Windows Azure‐based cloud resources can be applied for this purpose. A virtual screening experiment framework has been implemented on a Windows Azure‐based cloud using the generic worker concept. Virtual machines can be instantiated in the cloud on demand scaling up the simulations based on the volume of molecules to be docked and the available financial resources. Bioscientists are able to execute the simulations and visualise the results from a high‐level user interface. The paper describes the experiences when implementing the molecular docking application on this novel platform and provides the first benchmarking experiments to evaluate the suitability of the infrastructure for computation intensive simulations. Copyright © 2013 John Wiley & Sons, Ltd.

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Abstract. Science gateways can provide access to distributed computing resources and applications at very different levels of granularity. Some gateways do not even hide the details of the underlying infrastructure, while on the other hand some provide completely customized high-level interfaces to end-users. In this chapter the different granularity levels at which science gateways can be developed with WS-PGRADE/gUSE are analysed. The differences between these various granularity levels are also illustrated via the example of a molecular docking gateway and its four different implementations. IntroductionScience gateways, such as gateways built using the WS-PGRADE/gUSE framework [Kacsuk/2012], have the potential to offer transparent and userfriendly access to a wide variety of distributed computing resources. These tools hide the complexity of the underlying infrastructure from the scientist end-users and let them concentrate on their scientific research problem instead of requiring a steep and sometimes impossible learning curve in complex computing paradigms.Many web and desktop-based tools have been developed in the past few years that have been labelled as science gateways. However, close examination of these tools reveals that the level of granularity at which end-users can access the applications is rather varied. There are solutions which do not aim to hide the details of the original command line interface, and simply provide web-based access to the underlying distributed computing infrastructure. On the other extreme, there are custom-built portals supporting a single or a small family of applications and providing highly intuitive graphical user interfaces incorporating visualization tools, for example. Science gateways can be developed at various levels of granularity, significantly influencing how and by which category of users these tools can be utilized.Part of the research carried out in the SCI-BUS European project was to investigate the level of granularity of science gateways that a particular user community requires. As the WS-PGRADE/gUSE framework supports the development of sci-

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Systems biology studies the complex interactions of biological and biochemical systems rather than their individual molecular components. System biology simulations can be embarrassingly parallel jobs that have no dependency among individual simulation instances, and thus lend themselves to parallel execution over distributed resources to reduce their overall execution time. One example of such distributed resources is a Desktop Grid for Volunteer Computing that aims to use vast numbers of computers to support scientific applications. The SZTAKI Desktop Grid (SZDG) uses a modified form of the volunteer computing software BOINC to implement an institution-wide Desktop Grid. This paper reports on experiences of porting the SIMAP systems biology ODE simulator to SZDG. A case study using a simulation of the mammalian ErbB signaling pathway reports on significant speedup.