Hagiwara Yohsuke, Ohno Kazuki, Orita Masaya, Koga Ryota, Endo Toshio, Akiyama Yutaka, Sekijima Masakazu
Drug Discovery Research, Astellas Pharma Inc., 21 Miyukigaoka, Tsukuba, Ibaraki, 305-8585, Japan.
Curr Comput Aided Drug Des. 2013 Sep;9(3):396-401. doi: 10.2174/15734099113099990031.
The growing power of central processing units (CPU) has made it possible to use quantum mechanical (QM) calculations for in silico drug discovery. However, limited CPU power makes large-scale in silico screening such as virtual screening with QM calculations a challenge. Recently, general-purpose computing on graphics processing units (GPGPU) has offered an alternative, because of its significantly accelerated computational time over CPU. Here, we review a GPGPU-based supercomputer, TSUBAME2.0, and its promise for next generation in silico drug discovery, in high-density (HD) silico drug discovery.
中央处理器（CPU）计算能力的不断提升使得利用量子力学（QM）计算进行计算机辅助药物发现成为可能。然而，有限的CPU能力使得大规模计算机辅助筛选，如基于QM计算的虚拟筛选成为一项挑战。近来，基于图形处理器的通用计算（GPGPU）因其相比CPU显著加速的计算时间提供了一种替代方案。在此，我们综述了基于GPGPU的超级计算机TSUBAME2.0及其在下一代计算机辅助药物发现、高密度（HD）计算机辅助药物发现中的前景。
