Can B3LYP be improved by optimization of the proportions of exchange and correlation functionals?

Lu, Linfeng

doi:10.1002/qua.24876

Cited by 31 publications

(18 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is important to note that the results of the BO are independent of the initial set of points sampled with LHS (Figure ). In ref , the optimization of the free parameters of B-LYP was done with a denser grid (three million calculations). With BO, the total number of calculations is a few thousand, as shown by where M is the number of DF calculations for a single evaluation of and N BO is the number of iterations of BO required to find the minimum of .…”

Section: Resultsmentioning

confidence: 99%

“…For DF models, the gradient of with respect to any of the free parameters x i may not have a simple analytical form, since it also depends on the physical property (denoted as R m i ) chosen to evaluate the accuracy of the model, which is represented by . Because of the complexity involved in computing the gradient of with respect to x i , grid-search methods are the most common approach used to optimize DF models. ,− In this work, we present a scheme based on a machine learning (ML) algorithm in order to efficiently screen different DF models.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bayesian Optimization for Calibrating and Selecting Hybrid-Density Functional Models

Vargas-Hernández

2020

J. Phys. Chem. A

146

View full text Add to dashboard Cite

The accuracy of some density functional (DF) models, widely used in material science, depends on empirical or free parameters which are commonly tuned using reference physical properties. The optimal value of the free parameters is regularly found using grid search algorithms, which computational complexity scales with the number of points in the grid. In this report, we illustrate that Bayesian optimization (BO), a sample-efficient machine learning algorithm, can efficiently calibrate different density functional models, e.g., hybrid-exchange-correlation and range-separated density functionals. We present that, BO can optimize the free parameters of hybrid-exchange-correlation functionals, with approximately 55 evaluations of the root-mean-square or mean-absolute error functions of the atomization energies and the bond length of the Gaussian-1 (G1) database. We also illustrate that BO can identify, without any prior information, the most appropriate exchangecorrelation functional by navigating through the space of density functional models. We optimize and select the free parameters and the exchange-correlation functional form jointly by also minimizing the root-mean-square error function with respect to the atomization energies of the G1 database using BO.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bayesian Optimization for Calibrating and Selecting Hybrid-Density Functional Models

Vargas-Hernández

2020

J. Phys. Chem. A

146

View full text Add to dashboard Cite

show abstract

“…A functional enables a function to be mapped to be mapped to a number and producing another numerical outcome. B3LYP is a hybrid DFT model, it comprises of Hartree‐Fock (HF) exchange, gradient exchange correction, local exchange, local correlation and gradient correlation correction [21] . Here, DFT/B3LYP/6‐311++G(d,p) is used because DFT provides more precise quantum chemical computations in providing electronic structural data of the molecule.…”

Section: Methodsmentioning

confidence: 99%

Theoretical Study of Azetidine Derivative by Quantum Chemical Methods, Molecular Docking and Molecular Dynamic Simulations

Sinha

Yadav

2023

ChemistrySelect

View full text Add to dashboard Cite

Azetidine substituent group has a wide range of application in organic chemistry and medical field. In this study, a novel azetidine derivative and its reaction mechanism has been reported. Using quantum chemical method spectroscopic analysis and other parameters such as electronic and thermodynamic properties were studied to understand the physical as well as chemical behavior of the reported compound. Additionally, to study the antiviral activity, molecular docking studies were carried out against Hepatitis virus C (HCV) NS5B genotype and Norovirus as target protein. In order to validate the docking results molecular dynamic (MD) simulation and Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) were calculated at 90 ns. The RMSD was obtained within the range 0.75 Å to 1.5 Å and binding energies (ΔG bind ) for the two complexes was found to be À 18.34 kJ/mol and À 16.10 kJ/ mol for each respective targets.It was found that reported compound can act as potential inhibitor for HCVand Norovirus.

show abstract

“…Table 1 shows the ԑLUMO, ԑHOMO, and ΔE gaps, chemical potential (μ), electronegativity (χ), stiffness (ղ), softness and electrophilicity (ꞷ) of the drugs. These data have been calculated by utilizing B3LYP functional, leading to better geometry optimization results (54). The HOMO-LUMO energy gap determines the molecules' chemical sensitivity, and a large HOMO-LUMO gap refers to low chemical stability with high dynamics (55).…”

Section: Homo Lumo and Chemical Reactivity Descriptorsmentioning

confidence: 99%

Modified D-Glucofuranose Computationally Screening for Inhibitor of Breast Cancer and Triple Breast Cancer: Chemical Descriptor, Molecular Docking, Molecular Dynamics and Qsar

Kumer

Chakma

Chandro

et al. 2022

J. Chil. Chem. Soc.

View full text Add to dashboard Cite

Drug discovery and the process of new drug design have been formulated much easier in the past two decades by introducing, proliferation of combined physical, biochemical process from computing capabilities and computational approaches. Since the breast cancer is one of the life-threatening problems globally, no effective prescription is still now invented or not available in the market or medical treatment. Although the few number of drugs is just touched on the market, the remedy has consisted of severe side effects and low efficiency. Regarding that fact, the D-glucofuranose and its derivatives have been designed by the quantum calculation, molecular docking, ADMET and SAR analysis. For molecular docking, the cancer protease (3hb5) and triple-negative breast cancer protease (4pv5) are selected for study whereas the binding affinity of cancer protease (3hb5) is found at ranging from -6.20 to -10.40 kcal/mol, and it is slightly lower than triple-negative breast cancer protease (4pv5). Next, the molecular dynamic has performed to make the validation of docking complex. In our forthcoming study, it has shown that the 03, 05, and 08 compounds could be considered the potential drug comparison with standard drug. These three drugs completed all the criteria, including high binding energy, non-toxic, non-carcinogenic, and highly soluble in biological system.

show abstract

Can B3LYP be improved by optimization of the proportions of exchange and correlation functionals?

Cited by 31 publications

References 43 publications

Bayesian Optimization for Calibrating and Selecting Hybrid-Density Functional Models

Bayesian Optimization for Calibrating and Selecting Hybrid-Density Functional Models

Theoretical Study of Azetidine Derivative by Quantum Chemical Methods, Molecular Docking and Molecular Dynamic Simulations

Modified D-Glucofuranose Computationally Screening for Inhibitor of Breast Cancer and Triple Breast Cancer: Chemical Descriptor, Molecular Docking, Molecular Dynamics and Qsar

Contact Info

Product

Resources

About