GAFit

GAFit

We have developed a software package based on a genetic algorithm that fits an analytic function to a given set of data points. The code, called GAFit, was also interfaced with the CHARMM and MOPAC programs in order to facilitate force field parameterizations and fittings of specific reaction parameters (SRP) for semiempirical Hamiltonians.

It may be applied to a wide range of fitting problems, though it has been especially designed to significantly reduce the hard work involved in the development of potential energy surfaces for complex systems. For this purpose, it has been equipped with several programs to help the user in the preparation of the input files.

We showcase the application of the computational tool to several chemical-relevant problems: force-field parameterization, with emphasis on nonbonded energy terms or intermolecular potentials, derivation of SRP for semiempirical Hamiltonians, and fittings of generic analytical functions[1].

The last version, 1.6b, introduces a new module named generic. This module's target is to interface a broad range of external programs with a litte effort from the user.

Downloads

Download the Simplified User Guide
The most recent version of the User Manual (1.6) can be donwloaded here
The most recent version of GAFit (1.6c) can be downloaded here

Authors

Roberto Rodriguez-Fernandez, Francisco Baptista Pereira, Jorge M. C. Marques , Saulo Vázquez-Rodríguez, Emilio Martínez-Núñez

GAFit has been used in the works

GAFit, either in its present or earlier versions, has been used in the following papers:

• The PM6-FGC Method: Improved Corrections for Amines and Amides

Martiño Ríos-García, Berta Fernández, Jesús Rodríguez-Otero, Enrique M. Cabaleiro-Lago, Saulo A. Vázquez
Molecules 27(5):1678, 2022. DOI: 10.3390/molecules27051678

• New Approach for Correcting Noncovalent Interactions in Semiempirical Quantum Mechanical Methods: The Importance of Multiple-Orientation Sampling

Sergio Pérez-Tabero, Berta Fernández, Enrique M. Cabaleiro-Lago, Emilio Martínez-Núñez, Saulo A. Vázquez Journal of Chemical Theory and Computation 17(9), 5556–5567, 2021. DOI: 10.1021/acs.jctc.1c00365

• A Trajectory-Based Method to Explore Reaction Mechanisms

Saulo A Vázquez, Xose Luis Otero, Emilio Martinez-Nuñez Molecules 23(12):3156, 2018. DOI: 10.3390/molecules23123156

• Exploring the first‐shell and second‐shell structures arising in the microsolvation of Li+ by rare gases

Wanderson Silva Jesus, J. M. C. Marques, Frederico V. Prudente, Francisco B. Pereira International Journal of Quantum Chemistry 119(20):e25860, 2018. DOI: 10.1002/qua.25860

• GAFit: a general-purpose, user-friendly program for fitting potential energy surfaces

R. Rodríguez-Fernández, F.B. Pereira, J.M.C. Marques, E. Martínez-Núñez, S.A. Vázquez Computer Physics Communications 417, 89-98, 2017. DOI: 10.1016/j.cpc.2017.02.008

• Intermolecular potentials for simulations of collisions of SiNCS+ and (CH3)2SiNCS+ ions with fluorinated self-assembled monolayers

Juan José Nogueira, Antonio Sánchez-Coronilla, Jorge M. C. Marques, William L. Hase, Emilio Martínez-Núñez, Saulo A. Vázquez Chemical Physics 399, 193-204, 2012. DOI: 10.1016/j.chemphys.2011.02.014

• Direct fit of spectroscopic data of diatomic molecules by using genetic algorithms: II. The ground state of RbCs

M.M. Almeida, F.V. Prudente, C.E. Fellows, J.M.C. Marques, F.B. Pereira Journal of Physics B: Atomic, Molecular and Optical Physics 44, 225102, 2011. DOI: 10.1088/0953-4075/44/22/225102

• A new genetic algorithm to be used in the direct fit of potential energy curves to ab initio and spectroscopic data

J.M.C. Marques, F.V. Prudente, F.B. Pereira, M.M. Almeida, A.M. Maniero, C.E. Fellows Journal of Physics B: Atomic, Molecular and Optical Physics 41 (8), 085103, 2008. DOI: 10.1088/0953-4075/41/8/085103

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