Giupponi G, Harvey M J, De Fabritiis G
Computational Biochemistry and Biophysics Lab, GRID IMIM Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C/ Doctor Aiguader 88, 08003 Barcelona, Spain.
Drug Discov Today. 2008 Dec;13(23-24):1052-8. doi: 10.1016/j.drudis.2008.08.001. Epub 2008 Sep 16.
The recent introduction of cost-effective accelerator processors (APs), such as the IBM Cell processor and Nvidia's graphics processing units (GPUs), represents an important technological innovation which promises to unleash the full potential of atomistic molecular modeling and simulation for the biotechnology industry. Present APs can deliver over an order of magnitude more floating-point operations per second (flops) than standard processors, broadly equivalent to a decade of Moore's law growth, and significantly reduce the cost of current atom-based molecular simulations. In conjunction with distributed and grid-computing solutions, accelerated molecular simulations may finally be used to extend current in silico protocols by the use of accurate thermodynamic calculations instead of approximate methods and simulate hundreds of protein-ligand complexes with full molecular specificity, a crucial requirement of in silico drug discovery workflows.
近期出现的具有成本效益的加速器处理器(AP),如IBM Cell处理器和英伟达的图形处理单元(GPU),代表了一项重要的技术创新,有望释放原子分子建模与模拟在生物技术产业中的全部潜力。目前的加速器处理器每秒可提供比标准处理器高出一个数量级以上的浮点运算(flops),大致相当于摩尔定律十年的增长幅度,并且显著降低了当前基于原子的分子模拟成本。结合分布式和网格计算解决方案,加速分子模拟最终可能用于扩展当前的计算机模拟协议,通过使用精确的热力学计算而非近似方法,并以完整的分子特异性模拟数百种蛋白质-配体复合物,这是计算机辅助药物发现工作流程的一项关键要求。