The AIDS disease effects over 40 million people worldwide. Certain drugs have the ability to reduce patient viral loads and improve patient health by binding to and inhibiting critical viral enzymes. Unfortunately, the HIV virus causing AIDS has the ability to mutate and become resistant to these drugs. That sometimes happens in a very short period of time, thus requiring the patients to change their drug regime. As new mutations arise, it is important to pick the right anti-viral drug to best treat the patient and to not encourage the development of further drug resistance.
According to Michael Kuiper from VPAC, simulations have been designed to gather drug binding interaction energies of anti-HIV drugs bound to the active site of HIV protease, including drug-resistant versions of the protein. Though a metho¬dology with still ongoing development, it is hoped that this technique can give an accurate assessment of the likely effectiveness of each antiviral drug with respect to any given HIV mutant strain.
Given this information, patients who develop drug resistance can be given the next best effective drug for their HIV strain while reducing the danger of further resistance enhancements. In order to assess the drug binding interactions, each drug and respective HIV mutant enzyme is run as a short molecular dynamics simulation to try and get an averaged energy of interaction between the drug and the HIV protease strain. The huge number of calculations required is well suited for distributed processing, and time-to-solution can be significantly reduced by employing at the same time several supercomputers in a suitable HPC grid. Given a certain level of interoperability, the compute tasks can even be spread over different grids.
This effort has been successfully undertaken by DEISA and GridAustralia-APAC, joined by Monash University, during SC07 in Reno, although both infrastructures use different, incompatible underlying main middleware platforms.
DEISA is based on UNICORE 5 as far as job submission is concerned, while APAC makes use of the Globus Tool Kit. Following different approaches in job management, Globus and UNICORE are not interoperable in their currently established versions. In addition to DEISA’s option of data management via a continental global file system, however, both infrastructures support data transfer via GridFTP, usable both in Globus and in UNICORE.
Input data sets were provided in Australia by the Australian Research Group on an APAC storage server. Series of workflow jobs were submitted as shell scripts at the client site both to DEISA and to APAC through infrastructure specific interfaces, using DESHL for DEISA (a UNICORE command line tool), and Globus WS-Gram client for APAC. The parts of the input data required by each job were automatically moved to the respective DEISA or APAC execution sites in Europe or Australia via GridFTP.
A number of simulations were run with the drug Amprenavir (Apv) acting on various HIV strains. The trajectory data was post-processed to measure the energy of interaction between the drug and each HIV strain. The simulation results were later automatically uploaded on that APAC storage server for post-pro-cessing and visualization by the researchers.
By this transparent linking of compute resources in Australia and in Europe, and by offering reliable, automated bidirectional data transfer between both infrastructures, this project-oriented interoperation of DEISA and APAC could successfully be demonstrated for the first time.
Saara Vaerttoe | alfa
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