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

By A. Bochevarov, Edward D Harder, Thomas F Hughes, Jeremy R. Greenwood, D. A. Braden, D. Philipp, David Rinaldo, Mathew D. Halls, Jing Zhang, Richard A. Friesner. 2013

1,644 citations recorded by the source corpus.

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. © 2013 Wiley Periodicals, Inc.

Subfields: Computational Theory and Mathematics, Molecular Biology, Organic Chemistry

View Paper: https://www.semanticscholar.org/paper/ca3e6d92f6f2f86b618dc0a45e37cdb8013d20d1

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In Computational Theory and Mathematics

In Molecular Biology

In Organic Chemistry

Citations in the corpus

Improvements to the APBS biomolecular solvation software suite (2017, background): “The most significant (based on user base and citations) of these include CHARMM [12], AMBER [13], DelPhi [14], Jaguar [15], Zap [16], MIBPB [17], and APBS [18].”