Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors

Various methods (Hartree–Fock methods, semi-empirical methods, Density Functional Theory, Molecular Mechanics) used to optimize a molecule structure feature the same basic approach but differ in the mathematical approximations used. The geometry optimization procedure calculates the energy at an ini...

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Autores principales:	Donatella Bálint, Lorentz Jäntschi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Gaussian optimization geometry molecular modeling amino acids Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/52910e91cd6f449c897d8650b4537be8
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spelling	oai:doaj.org-article:52910e91cd6f449c897d8650b4537be82021-11-25T18:16:35ZComparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors10.3390/math92228552227-7390https://doaj.org/article/52910e91cd6f449c897d8650b4537be82021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2855https://doaj.org/toc/2227-7390Various methods (Hartree–Fock methods, semi-empirical methods, Density Functional Theory, Molecular Mechanics) used to optimize a molecule structure feature the same basic approach but differ in the mathematical approximations used. The geometry optimization procedure calculates the energy at an initial geometry of a molecule and then proceeds to search a new geometry with a lower energy. Using the 3D structures collected from the PubChem database, 20 amino acid geometry optimization calculations were performed with several methods. The purpose of the study was to analyze these methods (39) to find the relationship between them and to determine which to use under different circumstances. Cluster analysis and principal component analysis were performed to evaluate the similarities between the different methods. The results after the analysis can classified into three main groups and can be selected accordingly to solve different types of problems.Donatella BálintLorentz JäntschiMDPI AGarticleGaussianoptimizationgeometrymolecular modelingamino acidsMathematicsQA1-939ENMathematics, Vol 9, Iss 2855, p 2855 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Gaussian optimization geometry molecular modeling amino acids Mathematics QA1-939
spellingShingle	Gaussian optimization geometry molecular modeling amino acids Mathematics QA1-939 Donatella Bálint Lorentz Jäntschi Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors
description	Various methods (Hartree–Fock methods, semi-empirical methods, Density Functional Theory, Molecular Mechanics) used to optimize a molecule structure feature the same basic approach but differ in the mathematical approximations used. The geometry optimization procedure calculates the energy at an initial geometry of a molecule and then proceeds to search a new geometry with a lower energy. Using the 3D structures collected from the PubChem database, 20 amino acid geometry optimization calculations were performed with several methods. The purpose of the study was to analyze these methods (39) to find the relationship between them and to determine which to use under different circumstances. Cluster analysis and principal component analysis were performed to evaluate the similarities between the different methods. The results after the analysis can classified into three main groups and can be selected accordingly to solve different types of problems.
format	article
author	Donatella Bálint Lorentz Jäntschi
author_facet	Donatella Bálint Lorentz Jäntschi
author_sort	Donatella Bálint
title	Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors
title_short	Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors
title_full	Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors
title_fullStr	Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors
title_full_unstemmed	Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors
title_sort	comparison of molecular geometry optimization methods based on molecular descriptors
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/52910e91cd6f449c897d8650b4537be8
work_keys_str_mv	AT donatellabalint comparisonofmoleculargeometryoptimizationmethodsbasedonmoleculardescriptors AT lorentzjantschi comparisonofmoleculargeometryoptimizationmethodsbasedonmoleculardescriptors
_version_	1718411379030884352

Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors

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