Biomolecular Computational Thermodynamics: Strategies for Improved Efficiency

马里兰大学帕克分校的Christopher Jarzynsky获得了化学系理论与计算化学项目的奖励，以表彰他开发了提高生物分子计算效率的理论工具。他的研究重点是提高两个重要且具有挑战性的计算问题的效率：自由能估计和崎岖势能景观的采样。计算热力学的方法基于统计力学恒等式，它将系统的热力学性质与其潜在的微观细节联系起来。虽然这些方法基本上是合理的，但通常在计算上是昂贵的。为了提高计算效率，PI开发了一种新的策略工具包，围绕增强热力学状态之间重叠的原则组织。除了对生物分子应用有广泛的影响外，正在开发的方法在材料、物理、统计和化学等广泛的其他背景下也是相关的。PI已经推出了一个社区驱动的网站，致力于自由能计算方法。

Christopher Jarzynsky of the University of Maryland, College Park, is supported by an award from the Theoretical and Computational Chemistry program within the Division of Chemistry for the development of theoretical tools to improve computational efficiency in biomolecular computations. His research focuses on increasing the efficiency of two important and challenging computational problems: free energy estimation and the sampling of rugged potential energy landscapes. The methods of computational thermodynamics are based on statistical-mechanical identities which relate thermodynamic properties of systems to their underlying microscopic details. While fundamentally sound, these methods are typically computationally expensive. To enhance computational efficiency, the PI has developed a novel toolkit of strategies organized around the principle of enhancing overlap between thermodynamic states.In addition to having a broad impact on biomolecular applications, the methods being developed are relevant in a wide range of other contexts in materials, physics, statistics, and chemistry. The PI has launched a community-driven website devoted to methods for free energy calculations.