Department of Computer Science, Stanford University, Stanford, CA 94305, USA; Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA; Department of Structural Biology, Stanford University, Stanford, CA 94305, USA; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, USA.
Department of Computer Science, Stanford University, Stanford, CA 94305, USA; Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA; Department of Structural Biology, Stanford University, Stanford, CA 94305, USA; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, USA.
Neuron. 2018 Sep 19;99(6):1129-1143. doi: 10.1016/j.neuron.2018.08.011.
The impact of molecular dynamics (MD) simulations in molecular biology and drug discovery has expanded dramatically in recent years. These simulations capture the behavior of proteins and other biomolecules in full atomic detail and at very fine temporal resolution. Major improvements in simulation speed, accuracy, and accessibility, together with the proliferation of experimental structural data, have increased the appeal of biomolecular simulation to experimentalists-a trend particularly noticeable in, although certainly not limited to, neuroscience. Simulations have proven valuable in deciphering functional mechanisms of proteins and other biomolecules, in uncovering the structural basis for disease, and in the design and optimization of small molecules, peptides, and proteins. Here we describe, in practical terms, the types of information MD simulations can provide and the ways in which they typically motivate further experimental work.
近年来，分子动力学（MD）模拟在分子生物学和药物发现领域的影响显著扩大。这些模拟能够以全原子细节和非常精细的时间分辨率捕捉蛋白质和其他生物分子的行为。模拟速度、准确性和可访问性的重大改进，以及实验结构数据的大量增加，增加了生物分子模拟对实验人员的吸引力——这种趋势在神经科学中尤为明显，但肯定不仅限于此。模拟已被证明在破译蛋白质和其他生物分子的功能机制、揭示疾病的结构基础以及小分子、肽和蛋白质的设计和优化方面具有价值。在这里，我们从实际角度描述了 MD 模拟可以提供的信息类型，以及它们通常激发进一步实验工作的方式。
