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Implementation of protein tertiary structure prediction system with NetSolve

In this study, the protein tertiary structure prediction systems on the grid are proposed for progress of the bioinformatics. The prediction is mainly performed by the protein energy minimization. However, this method has many iterated calculation of the protein energy in most cases. To use the grid as the large-scale computing environment would be valuable for this system. In the system, parallel simulated annealing using genetic crossover (PSA/GAc) is a minimization engine and NetSolve is a basic tool to use the grid. In this study, two types of implementations are prepared. The first naive implementation of the system has a critical overhead due to large communication delay over the Internet. The second system, asynchronous crossover model, improves the performance in the second implementation. The details of the system and the experimental results solving C-peptide are shown as an example of grid application.