Volume 113, Issue 18 pp. 2110-2142
Software News & Updates
Open Access

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

Art D. Bochevarov

Corresponding Author

Art D. Bochevarov

Schrödinger Inc, 120 West 45th St, 17th floor, New York, New York, 10036

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Edward Harder

Edward Harder

Schrödinger Inc, 120 West 45th St, 17th floor, New York, New York, 10036

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Thomas F. Hughes

Thomas F. Hughes

Schrödinger Inc, 120 West 45th St, 17th floor, New York, New York, 10036

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Jeremy R. Greenwood

Jeremy R. Greenwood

Schrödinger Inc, 120 West 45th St, 17th floor, New York, New York, 10036

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Dale A. Braden

Dale A. Braden

Schrödinger Inc, 101 SW Main Street, Suite 1300, Portland, Oregon, 97204

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Dean M. Philipp

Dean M. Philipp

Schrödinger Inc, 101 SW Main Street, Suite 1300, Portland, Oregon, 97204

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David Rinaldo

David Rinaldo

Schrödinger GmbH, Dynamostrasse 13, D-68165 Mannheim, Germany

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Mathew D. Halls

Mathew D. Halls

Schrödinger Inc, 8910 University Center Lane, Suite 270, San Diego, California, 92122

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Jing Zhang

Jing Zhang

Department of Chemistry, Columbia University, 3000 Broadway, New York, New York, 10027

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Richard A. Friesner

Richard A. Friesner

Department of Chemistry, Columbia University, 3000 Broadway, New York, New York, 10027

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First published: 04 July 2013
Citations: 1,553

© 2013 The Authors. Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial-NoDerivs Licence, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Abstract

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 Møller–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. © 2013 Wiley Periodicals, Inc.

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