scholarly journals Optimized SQE atomic charges for peptides accessible via a web application

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Ondřej Schindler ◽  
Tomáš Raček ◽  
Aleksandra Maršavelski ◽  
Jaroslav Koča ◽  
Karel Berka ◽  
...  
Keyword(s):  
Web Application ◽  
Atomic Charge ◽  
Atomic Charges ◽  
Calculation Methods ◽  
Minimization Method ◽  
Large Molecules ◽  
Charge Equilibration ◽  
Electronegativity Equalization Method ◽  
Macromolecular Systems ◽  
Partial Atomic Charges

Abstract Background Partial atomic charges find many applications in computational chemistry, chemoinformatics, bioinformatics, and nanoscience. Currently, frequently used methods for charge calculation are the Electronegativity Equalization Method (EEM), Charge Equilibration method (QEq), and Extended QEq (EQeq). They all are fast, even for large molecules, but require empirical parameters. However, even these advanced methods have limitations—e.g., their application for peptides, proteins, and other macromolecules is problematic. An empirical charge calculation method that is promising for peptides and other macromolecular systems is the Split-charge Equilibration method (SQE) and its extension SQE+q0. Unfortunately, only one parameter set is available for these methods, and their implementation is not easily accessible. Results In this article, we present for the first time an optimized guided minimization method (optGM) for the fast parameterization of empirical charge calculation methods and compare it with the currently available guided minimization (GDMIN) method. Then, we introduce a further extension to SQE, SQE+qp, adapted for peptide datasets, and compare it with the common approaches EEM, QEq EQeq, SQE, and SQE+q0. Finally, we integrate SQE and SQE+qp into the web application Atomic Charge Calculator II (ACC II), including several parameter sets. Conclusion The main contribution of the article is that it makes SQE methods with their parameters accessible to the users via the ACC II web application (https://acc2.ncbr.muni.cz) and also via a command-line application. Furthermore, our improvement, SQE+qp, provides an excellent solution for peptide datasets. Additionally, optGM provides comparable parameters to GDMIN in a markedly shorter time. Therefore, optGM allows us to perform parameterizations for charge calculation methods with more parameters (e.g., SQE and its extensions) using large datasets. Graphic Abstract

scholarly journals Atomic Charge Calculator II: web-based tool for the calculation of partial atomic charges

2020 ◽  
Vol 48 (W1) ◽  
pp. W591-W596 ◽  
Author(s):  
Tomáš Raček ◽  
Ondřej Schindler ◽  
Dominik Toušek ◽  
Vladimír Horský ◽  
Karel Berka ◽  
...  
Keyword(s):  
Web Application ◽  
Atomic Charge ◽  
Atomic Charges ◽  
Calculation Methods ◽  
Web Based ◽  
Fast Calculation ◽  
Partial Charges ◽  
Partial Atomic Charges ◽  
Empirical Approaches ◽  
Highly Cited

Abstract Partial atomic charges serve as a simple model for the electrostatic distribution of a molecule that drives its interactions with its surroundings. Since partial atomic charges are frequently used in computational chemistry, chemoinformatics and bioinformatics, many computational approaches for calculating them have been introduced. The most applicable are fast and reasonably accurate empirical charge calculation approaches. Here, we introduce Atomic Charge Calculator II (ACC II), a web application that enables the calculation of partial atomic charges via all the main empirical approaches and for all types of molecules. ACC II implements 17 empirical charge calculation methods, including the highly cited (QEq, EEM), the recently published (EQeq, EQeq+C), and the old but still often used (PEOE). ACC II enables the fast calculation of charges even for large macromolecular structures. The web server also offers charge visualization, courtesy of the powerful LiteMol viewer. The calculation setup of ACC II is very straightforward and enables the quick calculation of high-quality partial charges. The application is available at https://acc2.ncbr.muni.cz.

scholarly journals High-Throughput Predictions of Metal–Organic Framework Electronic Properties: Theoretical Challenges, Graph Neural Networks, and Data Exploration

2021 ◽  
Author(s):  
Andrew S. Rosen ◽  
Victor Fung ◽  
Patrick Huck ◽  
Cody T. O'Donnell ◽  
Matthew K. Horton ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Web Application ◽  
Density Functional ◽  
Theoretical Calculations ◽  
Band Gaps ◽  
Atomic Charges ◽  
Metal Organic ◽  
Hybrid Functionals ◽  
Partial Atomic Charges

With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for (opto)electronic and energy storage applications, we present a new dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the new dataset of computed MOF properties to train machine learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project.

scholarly journals COMPARAÇÃO ENTRE MÉTODOS PARA DETERMINAÇÃO DE CARGAS ATÔMICAS EM SISTEMAS MOLECULARES: A MOLÉCULA N-{N-(PTERINA-7-IL)CARBONILGLICIL}-L-TIROSINA (NNPT)

Química Nova ◽  
2020 ◽  
Author(s):  
Fernanda Botelho ◽  
Roberta Oliveira ◽  
Joyce Almeida ◽  
Tanos França ◽  
Itamar Borges
Keyword(s):  
Dipole Moment ◽  
Atomic Charge ◽  
Basis Sets ◽  
Atomic Charges ◽  
Resonance Effects ◽  
Molecular Systems ◽  
Moment Vector ◽  
Different Types ◽  
Partial Atomic Charges ◽  
Charge Calculations

COMPARISON BETWEEN ATOMIC CHARGE METHODS FOR MOLECULAR SYSTEMS: THE N-{N-(PTERIN-7-YL) CARBONYLGLYCYL}-L-TYROSINE (NNPT) MOLECULE. Selecting a method to compute partial atomic charges is not trivial because different methods usually provide different charge values and there is no consensus on the most useful approach. In this work, Mulliken, MBS, Chelp, Chelpg, MK, Hirshfeld, NPA, DMA and AIM methods were selected to compute atomic charges and electric dipole moment vector of N-{N-(Pterin-7-yl)carbonylglycyl}-L-tyrosine molecule, a ricin inhibitor which has different types of bonds and chemical environments. While MBS and DMA methods provided the most chemically consistent charges according to atomic electronegativity and electron resonance effects criteria, Chelp, Chelpg and MK had the worst performances. Atomic charges and dipole moment calculated by the Hirshfeld method had the smallest magnitudes, a well-known behavior. Despite the differences among atomic charges predicted by all methods, the direction of the dipole moment vector was essentially the same. Further charge calculations using different basis sets and quantum methods indicated that the dependency on this aspect was the highest for Mulliken and Chelp and the lowest for MBS, Hirshfeld and DMA methods. Thus, results point to MBS and DMA as the most suitable methods for computing chemically consistent atomic charges and dipole moment vectors of similar systems for different applications; e.g., molecular dynamics.

CLB18: A New Structural Database with Unusual Carbon–Carbon Long Bonds

2020 ◽  
Author(s):  
Pierpaolo Morgante ◽  
Roberto Peverati
Keyword(s):  
Transition Metal Complexes ◽  
Low Cost ◽  
Geometry Optimization ◽  
Structure Calculation ◽  
Unique Property ◽  
Spin States ◽  
Calculation Methods ◽  
Large Molecules ◽  
Barrier Heights ◽  
Structural Database

<div><div><div><p>In this Letter, we introduce a new database called carbon long bond 18 (CLB18), composed of 18 structures with one long C–C bond. We use this new database to evaluate the performance of several low-cost methods commonly used for geometry optimization of medium and large molecules. We found that the long bonds in CLB18 are electronically different from those found in barrier heights databases. We also report the unexpected correlation between the results of CLB18 and those of the energetics of spin states in transition-metal complexes. Given this unique property, CLB18 can be a useful tool for assessing existing electronic structure calculation methods and developing new ones.</p></div></div></div>

Using Atomic Charges to Model Molecular Polarization.

2022 ◽  
Author(s):  
Frank Jensen
Keyword(s):  
Force Fields ◽  
Atomic Charge ◽  
Electric Polarization ◽  
Special Focus ◽  
Atomic Charges ◽  
Electrical Polarization

We review different models for introducing electrical polarization in force fields, with special focus on methods where polarization is modelled at the atomic charge level. While electric polarization has been...

scholarly journals Predicting partial atomic charges in siliceous zeolites

2019 ◽  
Vol 277 ◽  
pp. 184-196 ◽  
Author(s):  
Jarod J. Wolffis ◽  
Danny E.P. Vanpoucke ◽  
Amit Sharma ◽  
Keith V. Lawler ◽  
Paul M. Forster
Keyword(s):  
Atomic Charges ◽  
Partial Atomic Charges
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