Next Article in Journal
Reachability and Observability of Positive Linear Electrical Circuits Systems Described by Generalized Fractional Derivatives
Next Article in Special Issue
Exact Maximum Clique Algorithm for Different Graph Types Using Machine Learning
Previous Article in Journal
Estimation of COVID-19 Transmission and Advice on Public Health Interventions
Previous Article in Special Issue
Convergence Analysis and Dynamical Nature of an Efficient Iterative Method in Banach Spaces
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors

by
Donatella Bálint
1 and
Lorentz Jäntschi
1,2,*
1
Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 11 Arany Janos, 400082 Cluj-Napoca, Romania
2
Department of Physics and Chemistry, Technical University of Cluj-Napoca, 103-105 Muncii Blvd., 400641 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Mathematics 2021, 9(22), 2855; https://doi.org/10.3390/math9222855
Submission received: 28 September 2021 / Revised: 29 October 2021 / Accepted: 7 November 2021 / Published: 10 November 2021
(This article belongs to the Special Issue Mathematical and Molecular Topology)

Abstract

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.
Keywords: Gaussian; optimization; geometry; molecular modeling; amino acids Gaussian; optimization; geometry; molecular modeling; amino acids

Share and Cite

MDPI and ACS Style

Bálint, D.; Jäntschi, L. Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors. Mathematics 2021, 9, 2855. https://doi.org/10.3390/math9222855

AMA Style

Bálint D, Jäntschi L. Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors. Mathematics. 2021; 9(22):2855. https://doi.org/10.3390/math9222855

Chicago/Turabian Style

Bálint, Donatella, and Lorentz Jäntschi. 2021. "Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors" Mathematics 9, no. 22: 2855. https://doi.org/10.3390/math9222855

APA Style

Bálint, D., & Jäntschi, L. (2021). Comparison of Molecular Geometry Optimization Methods Based on Molecular Descriptors. Mathematics, 9(22), 2855. https://doi.org/10.3390/math9222855

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop