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  • Blugene

    Most biological functions involve proteins and while a protein's chemical composition is determined by a sequence of amino acids joined like links of a chain, a protein folds into a highly complex, three-dimensional shape such as illustrated in the two figures below.

    It is hypothesized that the shape of a protein is the principal determinant of its function. Arbitrary strings of amino acids do not, in general, fold into a well-defined three-dimensional structure, but evolution has selected out the proteins used in biological processes for their ability to fold reproducibly (sometimes with assistance, sometimes without) into a particular three-dimensional structure within a relatively short time. Some diseases are actually caused by slight misfoldings of a particular protein. Understanding the mechanisms that cause a string of amino acids to fold into a specific three-dimensional structure is an outstanding scientific challenge. Appropriate use of large scale biomolecular simulation to study protein folding is expected to shed significant light into this process. Extensive collaborations with the biological research community will be needed to find the best way of applying the unique computational resources available to the Blue Gene project to advance our understanding of protein folding. The level of performance provided by Blue Gene (sufficient to simulate the folding of a small protein in a year of running time) is expected to enable a tremendous increase in the scale of simulations that can be carried out as compared with existing supercomputers. Successful simulation studies of protein folding on this scale may require advances in the techniques, models, and algorithms used in biomolecular simulation, including:
    • force field models
    • algorithms for long range force evaluation
    • molecular dynamics techniques
    • efficient sampling methods

    IBM has initiated research efforts in some of these areas, in collaboration with academia and will be widening the scope of these activities over the course of the project. This collaborative effort will lead, in time, to better methods and models for simulating biologically interesting systems. The advances in our understanding of biomolecular simulation required to achieve the scientific goals of the Blue Gene project can be applied to a variety of related problems including
    • drug-protein interactions (docking)
    • enzyme catalysis (with hybrid quantum and classical methods)
    • molecular structure refinement
    • scoring of predicted structures for fold recognition
    • scoring for use in chemical database retrieval

    We shall also explore the use of Blue Gene in other scientific computing areas. We expect that lessons learned from this project will apply to future high performance IBM systems in a broader range of scientific and commercial applications.

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