PREDICTOR@HOME: PROTEIN STRUCTURE PREDICTION VIA THE WORLD-WIDE-WEB

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This core research project is directed toward the development, implementation and application of structural bioinformatics methods to protein structure prediction, loop modeling and homology modeling. During the last year we have deployed a new computational infrastructure for protein structure prediction utilizing volunteer computing resources through a world-wide-web distributed computing mechanism. This architecture is based on the BOINC (Berkeley Open Infrastructure for Network Computing) middleware (http://boinc.berkeley.edu) and the software packages CHARMM (biomolecular simulation package) and mfold (lattice-based protein folding code, part of the MMTSB Tool Set) called predictor@home (http://predictor.scripps.edu). Predictor@home is a world-community experiment and effort to use distributed world-wide-web volunteer resources to assemble a supercomputer able to predict protein structure from protein sequence. Our work is aimed at testing and evaluating new algorithms and methods of protein structure prediction in the context of the Sixth Biannual CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiment. The goal is to utilize these approaches together with the immense computer power that can be harnessed through the internet and volunteers all over the world to address critical biomedical questions of protein-related diseases. Our ultimate objective in this project is to deploy these resources to provide a This core research project is directed toward the development, implementation and application of structural bioinformatics methods to protein structure prediction, loop modeling and homology modeling. During the last year we have deployed a new computational infrastructure for protein structure prediction utilizing volunteer computing resources through a world-wide-web distributed computing mechanism. This architecture is based on the BOINC (Berkeley Open Infrastructure for Network Computing) middleware (http://boinc.berkeley.edu) and the software packages CHARMM (biomolecular simulation package) and mfold (lattice-based protein folding code, part of the MMTSB Tool Set) called predictor@home (http://predictor.scripps.edu). Predictor@home is a world-community experiment and effort to use distributed world-wide-web volunteer resources to assemble a supercomputer able to predict protein structure from protein sequence. Our work is aimed at testing and evaluating new algorithms and methods of protein structure prediction in the context of the Sixth Biannual CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiment. The goal is to utilize these approaches together with the immense computer power that can be harnessed through the internet and volunteers all over the world to address critical biomedical questions of protein-related diseases. Our ultimate objective in this project is to deploy these resources to provide a service component structure prediction server for the scientific community.