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

这个子项目是利用由NIH/NCRR资助的中心拨款提供的资源的许多研究子项目之一。子项目和调查员(PI)可能从另一个NIH来源获得了主要资金，因此可能会出现在其他CRISE条目中。列出的机构是针对中心的，而不一定是针对调查员的机构。这一核心研究项目是针对结构生物信息学方法在蛋白质结构预测、环建模和同源建模中的开发、实现和应用。在过去的一年里，我们部署了一个新的计算基础设施，用于蛋白质结构预测，通过万维网分布式计算机制利用志愿者计算资源。该体系结构基于BOINC(伯克利网络计算开放基础设施)中间件(http://boinc.berkeley.edu)和软件包CHARMM(生物分子模拟包)和MTSB工具集的基于晶格的蛋白质折叠代码)，称为Predictor@Home(http://predictor.scripps.edu).Predictor@Home是一项世界性的实验和努力，目的是利用分散的万维网志愿者资源组装一台能够从蛋白质序列预测蛋白质结构的超级计算机。我们的工作是在第六届蛋白质结构预测技术关键评估(CASP)实验的背景下，测试和评估蛋白质结构预测的新算法和方法。我们的目标是利用这些方法以及可以通过互联网和世界各地的志愿者利用的巨大计算机能力来解决与蛋白质相关的疾病的关键生物医学问题。我们在这个项目中的最终目标是部署这些资源，为蛋白质结构预测、环建模和同源建模提供一个核心研究项目，旨在开发、实施和应用结构生物信息学方法来预测蛋白质结构。在过去的一年里，我们部署了一个新的计算基础设施，用于蛋白质结构预测，通过万维网分布式计算机制利用志愿者计算资源。该体系结构基于BOINC(伯克利网络计算开放基础设施)中间件(http://boinc.berkeley.edu)和软件包CHARMM(生物分子模拟包)和MTSB工具集的基于晶格的蛋白质折叠代码)，称为Predictor@Home(http://predictor.scripps.edu).Predictor@Home是一项世界性的实验和努力，目的是利用分散的万维网志愿者资源组装一台能够从蛋白质序列预测蛋白质结构的超级计算机。我们的工作是在第六届蛋白质结构预测技术关键评估(CASP)实验的背景下，测试和评估蛋白质结构预测的新算法和方法。我们的目标是利用这些方法以及可以通过互联网和世界各地的志愿者利用的巨大计算机能力来解决与蛋白质相关的疾病的关键生物医学问题。我们在这个项目中的最终目标是部署这些资源，为科学界提供一个服务组件结构预测服务器。

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.