Jaguar: A high-performance quantum chemistry software program with strengths in life and materials sciences

被引:1457
作者
Bochevarov, Art D. [1 ]
Harder, Edward [1 ]
Hughes, Thomas F. [1 ]
Greenwood, Jeremy R. [1 ]
Braden, Dale A. [2 ]
Philipp, Dean M. [2 ]
Rinaldo, David [3 ]
Halls, Mathew D. [4 ]
Zhang, Jing [5 ]
Friesner, Richard A. [5 ]
机构
[1] Schrodinger Inc, New York, NY 10036 USA
[2] Schrodinger Inc, Portland, OR 97204 USA
[3] Schrodinger GmbH, D-68165 Mannheim, Germany
[4] Schrodinger Inc, San Diego, CA 92122 USA
[5] Columbia Univ, Dept Chem, New York, NY 10027 USA
关键词
ab initio; density functional theory; life sciences; materials sciences; software; DENSITY-FUNCTIONAL THEORY; MOLECULAR-ORBITAL METHODS; RELATIVISTIC EFFECTIVE POTENTIALS; SELF-CONSISTENT-FIELD; GAUSSIAN-BASIS SETS; TRANSITION-METAL-COMPLEXES; SOLVATION FREE-ENERGIES; REACTIVE FORCE-FIELD; VALENCE BASIS-SETS; PSEUDOSPECTRAL ELECTRONIC-STRUCTURE;
D O I
10.1002/qua.24481
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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.
引用
收藏
页码:2110 / 2142
页数:33
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