The SMFA program for quantum chemistry calculations on large molecules

Abstract

SMFA is a general program package for performing quantum chemistry calculations on large molecules, using an energy‐based fragmentation approach. The program can calculate electronic energies, energy gradients and second derivatives; perform geometry optimization; find first order saddle points (transition states); perform energy optimized scans along a user‐defined path; and evaluate various molecular properties. The program can use any of the following quantum chemistry packages: GAMESS(US), GAUSSIAN, NWChem and Q‐Chem. In addition, SMFA provides a number of utility programs that, inter alia, calculate vibrational frequencies and infrared spectra with isotopic substitutions, the electrostatic potential on the solvent‐accessible‐surface, and isodesmic and higher order near‐iso‐energetic reaction schemes. Calculations of the electronic energy and related properties can be carried out using a scheme that provides a computation time that is linearly dependent on the size of the molecule or, if the user has enough processing units available, in a walltime that is independent of the size of the molecule. This article is categorized under: Software > Quantum Chemistry Electronic Structure Theory > Ab Initio Electronic Structure Methods Structure and Mechanism > Computational Biochemistry and Biophysics

Accelerating the Calculation of Solute–Solvent Interaction Energies through Systematic Molecular Fragmentation

“…It is possible to reduce the wall time of these calculations by employing multiple nodes, without significantly increasing the total CPU time. The reduction in wall time that is possible for these cluster calculations is less than that for more CPU intensive calculations reported previously . Nonetheless, using 32 cores in two nodes, a selection of representative clusters of 160 waters requires an average of 14:05 min per cluster containing the solute, and 11:23 min for the water cluster only, via eq .…”

“…Systematic molecular fragmentation by annihilation (SMFA) is a method for approximating the total electronic energy of a molecule by evaluating the energy of certain small molecular fragments, with significantly reduced computational effort. How the standard SMFA method works has been described in detail previously. − The code is contained in a freely available program package . In summary, a molecule is defined as a collection of chemical functional groups that are connected by single bonds (or hydrogen bonds).…”

“…For longer separations, the interaction energy is evaluated by using perturbation theory [based on ab initio calculations of charge distributions, static polarizability, and the imaginary frequency polarizability] as the sum of an electrostatic interaction, a dispersion interaction, and a contribution from induction. Hence, the total molecular energy, E , is given by Equation has been shown to be accurate to within a few kJ mol –1 for many organic and biological molecules, if the value of Level is sufficiently large . The method is termed “systematic” because one can observe convergence of the molecular energy as the value of Level is systematically increased.…”

“…Moreover, SMFA is a fully automated approach that applies to any molecular system. Hence, SMFA is available as a program package 39 that requires little input from the user apart from the usual specifications of the electronic structure method to be used.…”

fragHAR: towardsab initioquantum-crystallographic X-ray structure refinement for polypeptides and proteins

“…This approach, which is obviously linear-scaling, makes QM calculations feasible for proteins (Stoll, 1992;Doll et al, 1997;Zhang & Zhang, 2003;Sö derhjelm & Ryde, 2009;Yang, 1991;Lee et al, 1996;Yang & Lee, 1995;Kohn, 1996;Dixon & Merz, 1996;Gogonea et al, 2000;Stewart, 1996;Daniels et al, 1997;Daniels & Scuseria, 1999;Scuseria, 1999). These methods have been reviewed by Collins & Bettens (2015), and a general program to implement them by scripting other ab initio packages has been presented by Kobayashi et al (2019).…”