Recent progress of protein canonical molecular orbital calculation by the third generation density functional method

T. Hirano, F. Sato
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Abstract

Although canonical molecular orbital (CMO) calculations for proteins are very useful for protein engineering, they are computationally expensive and difficult to achieve because proteins are large molecules. We had developed the third-generation density functional (3G DF) method, which performed electronic state calculation with high efficiency in parallel computer by performing only matrix operation during the SCF calculation. In this study, by applying the powerful computing platform of graphic processing unit (GPU) to our 3G DF calculation method, we constructed a computing environment that achieved the large-scale CMO computation with high efficiency.Although canonical molecular orbital (CMO) calculations for proteins are very useful for protein engineering, they are computationally expensive and difficult to achieve because proteins are large molecules. We had developed the third-generation density functional (3G DF) method, which performed electronic state calculation with high efficiency in parallel computer by performing only matrix operation during the SCF calculation. In this study, by applying the powerful computing platform of graphic processing unit (GPU) to our 3G DF calculation method, we constructed a computing environment that achieved the large-scale CMO computation with high efficiency.
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第三代密度泛函法计算蛋白质典型分子轨道的研究进展
尽管蛋白质的典型分子轨道(CMO)计算在蛋白质工程中非常有用,但由于蛋白质是大分子,因此计算成本高且难以实现。我们开发了第三代密度泛函(3G DF)方法,通过在SCF计算过程中只进行矩阵运算,在并行计算机上进行高效率的电子状态计算。在本研究中,我们将图形处理单元(GPU)强大的计算平台应用到我们的3G DF计算方法中,构建了一个高效实现大规模CMO计算的计算环境。尽管蛋白质的典型分子轨道(CMO)计算在蛋白质工程中非常有用,但由于蛋白质是大分子,因此计算成本高且难以实现。我们开发了第三代密度泛函(3G DF)方法,通过在SCF计算过程中只进行矩阵运算,在并行计算机上进行高效率的电子状态计算。在本研究中,我们将图形处理单元(GPU)强大的计算平台应用到我们的3G DF计算方法中,构建了一个高效实现大规模CMO计算的计算环境。
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