Jaguar: A high-performance quantum chemistry software program with strengths in life and materials sciences
Jaguar: A high-performance quantum chemistry software program with strengths in life and materials sciences
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DOI：
10.1002/qua.24481
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发表时间：
2013-09-15
影响因子：
2.2
通讯作者：
Friesner, Richard A.
中科院分区：
文献类型：
--
作者：
Bochevarov, Art D.;Harder, Edward;Friesner, Richard A.
Jaguar是一个从头计算量子化学程序，专门用于快速预测中型和大型分子系统的电子结构。Jaguar专注于计算方法与合理的计算缩放系统的大小，如密度泛函理论（DFT）和局部二阶Moller-Plesset微扰理论。该方法的良好的缩放和程序的高效率使得进行涉及数千个分子轨道的常规计算成为可能。这种性能是通过利用伪谱近似和几个层次的并行化。速度优势有利于将Jaguar应用于生物分子计算建模。此外，由于其上级波函数猜测过渡金属含系统，美洲虎发现在无机和生物无机化学的应用。对更大系统和过渡金属元素的强调为开发Jaguar用于材料科学建模铺平了道路。本文介绍了捷豹的历史和新的功能，如改进的并行化的许多模块，创新的从头算pKa预测，和新的半经验修正DFT中的非动态相关误差。Jaguar在药物发现、材料科学、力场参数化和其他计算研究领域的应用进行了综述。提供了从最新的捷豹代码获得的时间基准和其他结果。文章最后讨论了该计划未来发展的挑战和方向。(C)2013 Wiley Periodicals，Inc.
Jaguar is an ab initio quantum chemical program that specializes in fast electronic structure predictions for molecular systems of medium and large size. Jaguar focuses on computational methods with reasonable computational scaling with the size of the system, such as density functional theory (DFT) and local second-order Moller-Plesset perturbation theory. The favorable scaling of the methods and the high efficiency of the program make it possible to conduct routine computations involving several thousand molecular orbitals. This performance is achieved through a utilization of the pseudospectral approximation and several levels of parallelization. The speed advantages are beneficial for applying Jaguar in biomolecular computational modeling. Additionally, owing to its superior wave function guess for transition-metal-containing systems, Jaguar finds applications in inorganic and bioinorganic chemistry. The emphasis on larger systems and transition metal elements paves the way toward developing Jaguar for its use in materials science modeling. The article describes the historical and new features of Jaguar, such as improved parallelization of many modules, innovations in ab initio pKa prediction, and new semiempirical corrections for nondynamic correlation errors in DFT. Jaguar applications in drug discovery, materials science, force field parameterization, and other areas of computational research are reviewed. Timing benchmarks and other results obtained from the most recent Jaguar code are provided. The article concludes with a discussion of challenges and directions for future development of the program. (C) 2013 Wiley Periodicals, Inc.