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...

Hydration Free Energies of Organic Molecules in the FreeSolv Database Calculated with Polarized Atom In Molecules Atomic Charges and the GAFF Force Field.

2018 ◽  
Author(s):  
Maximiliano Riquelme ◽  
Alejandro Lara ◽  
David L. Mobley ◽  
Toon Vestraelen ◽  
Adelio R Matamala ◽  
...  
Keyword(s):  
Force Field ◽  
Functional Groups ◽  
Electrostatic Interactions ◽  
Organic Molecules ◽  
Force Fields ◽  
Chemical Elements ◽  
Atomic Charges ◽  
Free Energies ◽  
Molecular Systems ◽  
Solvent Model

<div>Computer simulations of bio-molecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in bio-molecular systems and are therein described by atomic point charges.</div><div>In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute's electron density computed with an implicit solvent model and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the MBIS atomic charge method, including the solvent polarization, with a root mean square error of 2.0 kcal mol<sup>-1</sup> for the 613 organic molecules studied. The largest deviation was observed for phosphor-containing molecules and the molecules with amide, ester and amine functional groups.</div>

scholarly journals Using Atomic Charges to Describe the pKa of Carboxylic Acids

2020 ◽  
Author(s):  
Zeynep Pinar Haslak ◽  
Sabrina Zareb ◽  
Viktorya Aviyente ◽  
Gerald Monard
Keyword(s):  
Linear Relationship ◽  
Carboxylic Acids ◽  
Atomic Charge ◽  
Basis Sets ◽  
Atomic Charges ◽  
Dft Methods ◽  
Solvent Models ◽  
Dynamics Simulations ◽  
Fast Prediction ◽  
Protein Environment

<div>In this study, we present an accurate protocol for the fast prediction of pKa's of carboxylic acids based on the linear relationship between computed atomic charges of the anionic form of the carboxylate fragment and their experimental pKa values. Five charge descriptors, three charge models, three solvent models, gas phase calculations and several DFT methods (combination of eight DFT functionals and fifteen basis sets) were tested. Among those, the best combination to reproduce experimental pKa's is to compute NPA atomic charge using the SMD model at the M06L/6-311G(d,p) level of theory and selecting the maximum atomic charge on carboxylic oxygen atoms (R^2 = 0.955). The applicability of the suggested protocol and its stability along geometrical changes are verified by molecular dynamics simulations performed for a set of aspartate, glutamate and alanine peptides. By reporting the calculated atomic charge of the carboxylate form into the linear relationship derived in this work, it will be possible to estimate accurately the amino acid’s pKa's in protein environment.</div><div><br></div>

DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges

2020 ◽  
Author(s):  
Jike Wang ◽  
Dongsheng Cao ◽  
Cunchen Tang ◽  
Lei Xu ◽  
Qiaojun He ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Atomic Charge ◽  
High Accuracy ◽  
Substantial Improvement ◽  
Molecular Properties ◽  
Atomic Charges ◽  
Convolutional Network ◽  
Structure Based Drug Design ◽  
Molecular Fingerprints

Abstract Atomic charges play a very important role in drug-target recognition. However, computation of atomic charges with high-level quantum mechanics (QM) calculations is very time-consuming. A number of machine learning (ML)-based atomic charge prediction methods have been proposed to speed up the calculation of high-accuracy atomic charges in recent years. However, most of them used a set of predefined molecular properties, such as molecular fingerprints, for model construction, which is knowledge-dependent and may lead to biased predictions due to the representation preference of different molecular properties used for training. To solve the problem, we present a new architecture based on graph convolutional network (GCN) and develop a high-accuracy atomic charge prediction model named DeepAtomicCharge. The new GCN architecture is designed with only the atomic properties and the connection information between the atoms in molecules and can dynamically learn and convert molecules into appropriate atomic features without any prior knowledge of the molecules. Using the designed GCN architecture, substantial improvement is achieved for the prediction accuracy of atomic charges. The average root-mean-square error (RMSE) of DeepAtomicCharge is 0.0121 e, which is obviously more accurate than that (0.0180 e) reported by the previous benchmark study on the same two external test sets. Moreover, the new GCN architecture needs much lower storage space compared with other methods, and the predicted DDEC atomic charges can be efficiently used in large-scale structure-based drug design, thus opening a new avenue for high-performance atomic charge prediction and application.

Benchmarking Electronic Structure Methods for Accurate Fixed-Charge Electrostatic Models

2019 ◽  
Author(s):  
Alex Zhou ◽  
Michael Schauperl ◽  
Paul Nerenberg
Keyword(s):  
Electronic Structure ◽  
Gas Phase ◽  
Condensed Phase ◽  
Force Fields ◽  
Dipole Moments ◽  
Fixed Charge ◽  
Basis Set ◽  
Atomic Charges ◽  
Molecular Dipole ◽  
Partial Atomic Charges

<p>The accuracy of classical molecular mechanics (MM) force fields used for condensed phase molecular simulations depends strongly on the accuracy of modeling nonbonded interactions between atoms, such as electrostatic interactions. Some popular fixed-charge MM force fields use partial atomic charges derived from gas phase electronic structure calculations using the Hartree-Fock method with the relatively small 6-31G* basis set (HF/6-31G*). It is generally believed that HF/6-31G* generates fortuitously overpolarized electron distributions, as would be expected in the higher dielectric environment of the condensed phase. Using a benchmark set of 47 molecules we show that HF/6-31G* overpolarizes molecules by just under 10% on average with respect to experimental gas phase dipole moments. The overpolarization of this method/basis set combination varies significantly though and, in some cases, even leads to molecular dipole moments that are lower than experimental gas phase measurements. We further demonstrate that using computationally inexpensive density functional theory (DFT) methods, together with appropriate augmented basis sets and a continuum solvent model, can yield molecular dipole moments that are both more strongly and more uniformly overpolarized. These data suggest that these methods – or ones similar to them – should be adopted for the derivation of accurate partial atomic charges for next-generation MM force fields.<br></p>

scholarly journals Origin of the Multiferroic-Like Properties of Er2CoMnO6

2016 ◽  
Vol 257 ◽  
pp. 95-98 ◽  
Author(s):  
Javier Blasco ◽  
Gloria Subías ◽  
Joaquín García ◽  
Jolanta Stankiewicz ◽  
José Alberto Rodríguez-Velamazán ◽  
...  
Keyword(s):  
Low Temperature ◽  
Heating Rate ◽  
Strong Dependence ◽  
Double Perovskite ◽  
Electric Polarization ◽  
Ferromagnetic Transition ◽  
Electrical Polarization ◽  
Magnetoelectric Properties ◽  
Monoclinic Distortion ◽  
Thermally Stimulated Depolarization

We report on the magnetoelectric properties of Er2CoMnO6. This compound adopts the structure of a double perovskite with a strong monoclinic distortion. Our specimen exhibits a nearly perfect Co-Mn order. It undergoes a ferromagnetic transition at TC~70 K due to the Co2+-O-Mn4+ ferromagnetic superexchange interaction. Below 30 K, the Er3+ moments start to order antiferromagnetically to the Co/Mn sublattice. Pyroelectric measurements reveal electrical polarization at low temperature but its strong dependence on the heating rate indicates the lack of a spontaneous ferroelectricity. Instead, electric polarization is derived from thermally stimulated depolarization currents.

Towards improved force fields: III. Polarization through modified atomic charges

1999 ◽  
Vol 20 (7) ◽  
pp. 704-712 ◽  
Author(s):  
Peter J. Winn ◽  
Gy�rgy G. Ferenczy ◽  
Christopher A. Reynolds
Keyword(s):  
Force Fields ◽  
Atomic Charges

scholarly journals RELATION OF ELECTRONIC STRUCTURES WITH THEIR ANTIMALARIAL ACTIVITIES ON ARTEMISININ DERIVATIVES

2010 ◽  
Vol 4 (3) ◽  
pp. 212-217 ◽  
Author(s):  
Ria Armunanto ◽  
Sri Sudiono
Keyword(s):  
Electronic Structures ◽  
Antimalarial Activity ◽  
Atomic Charge ◽  
Quantitative Structure Activity Relationship ◽  
Equation Model ◽  
Atomic Charges ◽  
Quantitative Structure ◽  
Artemisinin Derivatives ◽  
Structure Activity

Relation of electronic structures with their anti malaria activities on artemisinin derivatives was evaluated by means of quantitative structure activity relationship (QSAR) method. To describe electronic structures, atomic charges and dipol moments calculated by quantum mechanics on PM3 semiempirical level. A linear relation between activities and electronic structures was used to construct linear equation models. An equation model showing a good statistically criteria and a realibility of antimalarial activity was chosen to be used to design a compound with new activities against P. facilparum. Results show that 13 equation models were obtained, showing only three models with a good criteria. O2 and C4 atoms were observed for a key role of an improvement of the antimalarial activity.   Keywords: artemisinin, antimalaria, atomic charge, dipole moment, PM3

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