ight childhood cancer project,' some 8000 years of research should be cut by using the grid, says Akira Nakagawara, president of the Chiba Cancer Centre at Chiba University in Japan. 'In the ordinary lab, it is absolutely impossible to do this kind of research,' he notes. The project is screening three million small compounds against six targets in the hope of finding about 30 chemicals that could potentially treat the childhood cancer neuroblastoma. Already seven chemicals that specifically kill the neuroblastoma cells have been finalised for the first target.
Likewise, the separate 'Help conquer cancer' project - which is analysing 86 million x-ray crystallography images to aid understanding of cancer-related proteins - has been able to dramatically slash research times. 'It is a long project even on the grid,' says Igor Jurisica from the Ontario Cancer Institute in Canada. 'But without WCG we would not be able to make this comprehensive analysis in our lifetime.' The computation helps the team to identify characteristic gene or protein expression 'signatures' that can assist in diagnosing and monitoring diseases, or predicting how well patients will respond to certain treatments. Three of the lung cancer signatures are in preclinical stage already, while similar signatures in leukaemia, ovarian and head and neck cancer are in the pipeline.
For Stan Watowich at the University of Texas Medical Branch in Galveston, US, doing research in this way is a no-brainer - particularly in disease areas considered high risk or financially unattractive. Watowich's team is using the WCG to find treatment cures for dengue fever and West Nile virus and has been able to cut research times from an estimated 25 years on traditional laboratory multiprocessor computers to just weeks via the WCG.
In the first phase of the project, the team investigated about 15 different proteins that could be potential drug targets because of the role each plays in disease pathogenesis. Some 2.5 million small drug-like molecules were screened against these 15 proteins, resulting in over 35 million docking simulations. Now in the second phase, this number has been whittled down to 5000 promising candidate molecules and the team is running free energy calculations for each protein target. From these calculations, 50 of the best binding compounds for each target protein will be tested in biochemical assays to confirm the computer predictions. Active compounds will then be evaluated in cell culture assays and other preclinical tests with the ultimate goal of moving promising new drug candidates into clinical trials in humans with regulatory drug approval as the end result, says Watowich.
Not only does this research aim to attack the high attrition rate for compounds moving through the development process by providing more promising drug candidates that should have an improved probability of regulatory approval, Watowich says it also aims to show it is possible to accelerate drug discovery by completing accurate free energy of binding calculations on highly distributed computer resources. 'If successful, our grid-based drug discovery approach can be applied to almost any disease with defined molecular triggers,' he adds.
The end of experiments?
So does this all point to grid-based computer simulations trumping traditional lab-based work? Jasinski says it is important to see the two as complementary. 'Today's science demands both approaches. A computer can certainly offer certain efficiencies that reduce time and expense dramatically. At some point though, it becomes necessary to perform experiments with physical matter.' Likewise, he says there are very few things in life that are infallible. While there are advantages to electronic simulations, they are, in the end, only as good as the accuracy of the computational model, he says. False positives do exist, and it requires additional research to eliminate these.
Volunteers can monitor their contributions using screen savers and get 'points' for work done
In the case of finding new drugs, Watowich adds that the c