Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Applications of density functional theory in COVID-19 drug modeling.

ABSTRACT: The rapidly evolving Coronavirus 2019 (COVID-19) pandemic has led to millions of deaths around the world, highlighting the pressing need to develop effective antiviral pharmaceuticals. Recent efforts with computer-aided rational drug discovery have allowed detailed examination of drug-macromolecule interactions primarily by molecular mechanics (MM) techniques. Less widely applied in COVID-19 drug modeling is density functional theory (DFT), a quantum mechanics (QM) method that enables electronic structure calculations and elucidations of reaction mechanisms. Here, we review recent advances in applying DFT in molecular modeling studies of COVID-19 pharmaceuticals. We start by providing an overview of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drugs and targets, followed by a brief introduction to DFT. We then provide a discussion of different approaches by which DFT has been applied. Finally, we discuss essential factors to consider when incorporating DFT in future drug modeling research.

SUBMITTER: Ye N

PROVIDER: S-EPMC8695517 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Applications of density functional theory in COVID-19 drug modeling.

Ye Naike N Yang Zekai Z Liu Yuchen Y

Drug discovery today 20211223 5

The rapidly evolving Coronavirus 2019 (COVID-19) pandemic has led to millions of deaths around the world, highlighting the pressing need to develop effective antiviral pharmaceuticals. Recent efforts with computer-aided rational drug discovery have allowed detailed examination of drug-macromolecule interactions primarily by molecular mechanics (MM) techniques. Less widely applied in COVID-19 drug modeling is density functional theory (DFT), a quantum mechanics (QM) method that enables electronic ...[more]

PMID: 34954327

Similar Datasets

Density functional theory modeling of chromate adsorption onto ferrihydrite nanoparticles.

Project description:Density functional theory (DFT) calculations were performed on a model of a ferrihydrite nanoparticle interacting with chromate ([Formula: see text]) in water. Two configurations each of monodentate and bidentate adsorbed chromate as well as an outer-sphere and a dissolved bichromate ([Formula: see text]) were simulated. In addition to the 3-D periodic planewave DFT models, molecular clusters were extracted from the energy-minimized structures. Calculated interatomic distances from the periodic and cluster models compare favorably with Extended X-ray Absorption Fine Structure spectroscopy values, with larger discrepancies seen for the clusters due to over-relaxation of the model substrate. Relative potential energies were derived from the periodic models and Gibbs free energies from the cluster models. A key result is that the bidentate binuclear configuration is the lowest in potential energy in the periodic models followed by the outer-sphere complex. This result is consistent with observations of the predominance of bidentate chromate adsorption on ferrihydrite under conditions of high surface coverage (Johnston Environ Sci Technol 46:5851-5858, 2012). Cluster models were also used to perform frequency analyses for comparison with observed ATR FTIR spectra. Calculated frequencies on monodentate, bidentate binuclear, and outer-sphere complexes each have infrared (IR)-active modes consistent with experiment. Inconsistencies between the thermodynamic predictions and the IR-frequency analysis suggest that the 3-D periodic models are not capturing key components of the system that influence the adsorption equilibria under varying conditions of pH, ionic strength and electrolyte composition. Model equilibration via molecular dynamics (MD) simulations is necessary to escape metastable states created during DFT energy minimizations based on the initial classical force field MD-derived starting configurations.

| S-EPMC5832661 | biostudies-literature

Multilevel Density Functional Theory.

Project description:Following recent developments in multilevel embedding methods, we introduce a novel density matrix-based multilevel approach within the framework of density functional theory (DFT). In this multilevel DFT, the system is partitioned in an active and an inactive fragment, and all interactions are retained between the two parts. The decomposition of the total system is performed upon the density matrix. The orthogonality between the two parts is maintained by solving the Kohn-Sham equations in the MO basis for the active part only, while keeping the inactive density matrix frozen. This results in the reduction of computational cost. We outline the theory and implementation and discuss the differences and similarities with state-of-the-art DFT embedding methods. We present applications to aqueous solutions of methyloxirane and glycidol.

| S-EPMC7880574 | biostudies-literature

Nonlocal pseudopotential energy density functional for orbital-free density functional theory.

Project description:Orbital-free density functional theory (OF-DFT) is an electronic structure method with a low computational cost that scales linearly with the number of simulated atoms, making it suitable for large-scale material simulations. It is generally considered that OF-DFT strictly requires the use of local pseudopotentials, rather than orbital-dependent nonlocal pseudopotentials, for the calculation of electron-ion interaction energies, as no orbitals are available. This is unfortunate situation since the nonlocal pseudopotentials are known to give much better transferability and calculation accuracy than local ones. We report here the development of a theoretical scheme that allows the direct use of nonlocal pseudopotentials in OF-DFT. In this scheme, a nonlocal pseudopotential energy density functional is derived by the projection of nonlocal pseudopotential onto the non-interacting density matrix (instead of "orbitals") that can be approximated explicitly as a functional of electron density. Our development defies the belief that nonlocal pseudopotentials are not applicable to OF-DFT, leading to the creation for an alternate theoretical framework of OF-DFT that works superior to the traditional approach.

| S-EPMC8927098 | biostudies-literature

SARS-CoV-2 infection of primary human lung epithelium for COVID-19 modeling and drug discovery

Project description:Coronavirus disease 2019 (COVID-19) is the latest respiratory pandemic resulting from zoonotic transmission of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). Severe symptoms include viral pneumonia secondary to infection and inflammation of the lower respiratory tract, in some cases causing death. We developed primary human lung epithelial infection models to understand responses of proximal and distal lung epithelium to SARS-CoV-2 infection. Differentiated air-liquid interface cultures of proximal airway epithelium and 3D organoid cultures of alveolar epithelium were readily infected by SARS-CoV-2 leading to an epithelial cell-autonomous proinflammatory response. We validated the efficacy of selected candidate COVID-19 drugs confirming that Remdesivir strongly suppressed viral infection/replication. We provide a relevant platform for studying COVID-19 pathobiology and for rapid drug screening against SARS-CoV-2 and future emergent respiratory pathogens.

2020-11-06 | GSE155518 | GEO

Boron-Carbon-Nitride Sheet as a Novel Surface for Biological Applications: Insights from Density Functional Theory.

Project description:Understanding the interaction between nanoscale materials and nucleobases is essential for their use in nanobiotechnology and nanomedicine. Our ab initio calculations indicate that the interaction of nucleobases [adenine (A), cytosine (C), guanine (G), thymine (T), and uracil (U)] with boron-carbon-nitride (BCN) is mainly governed by van der Waals interactions. The adsorption energies, ranging from -0.560 to -0.879 eV, decrease in the order of G > A > T > C > U, which can be attributed to π-π interactions and different side groups of the nucleobases. We found that anions (N and O atoms) of nucleobases prefer to stay on top of cation (B) of the substrate. The results also showed that BCN exhibits superior binding strength than graphene and boron-nitride-based materials. We also found that upon adsorption, the fundamental properties of BCN and nucleobases remains unaltered, which suggests that BCN is a promising template for self-assembly of nucleobases.

| S-EPMC6648852 | biostudies-literature

Density-functional fluctuation theory of crowds.

Project description:A primary goal of collective population behavior studies is to determine the rules governing crowd distributions in order to predict future behaviors in new environments. Current top-down modeling approaches describe, instead of predict, specific emergent behaviors, whereas bottom-up approaches must postulate, instead of directly determine, rules for individual behaviors. Here, we employ classical density functional theory (DFT) to quantify, directly from observations of local crowd density, the rules that predict mass behaviors under new circumstances. To demonstrate our theory-based, data-driven approach, we use a model crowd consisting of walking fruit flies and extract two functions that separately describe spatial and social preferences. The resulting theory accurately predicts experimental fly distributions in new environments and provides quantification of the crowd "mood". Should this approach generalize beyond milling crowds, it may find powerful applications in fields ranging from spatial ecology and active matter to demography and economics.

| S-EPMC6117271 | biostudies-literature

Density Matrix Embedding Using Multiconfiguration Pair-Density Functional Theory.

Project description:We present a quantum embedding method for ground and excited states of extended systems that uses multiconfiguration pair-density functional theory (MC-PDFT) with densities provided by periodic density matrix embedding theory (pDMET). We compute local excitations in oxygen mono- and divacancies on a magnesium oxide (100) surface and find absolute deviations within 0.05 eV between pDMET using the MC-PDFT, denoted as pDME-PDFT, and the more expensive, nonembedded MC-PDFT approach. We further use pDME-PDFT to calculate local excitations in larger supercells for the monovacancy defect, for which the use of nonembedded MC-PDFT is prohibitively costly.

| S-EPMC10308814 | biostudies-literature

Modeling nuclear resonance vibrational spectroscopic data of binuclear non-heme iron enzymes using density functional theory.

Project description:Nuclear resonance vibrational spectroscopy (NRVS) is a powerful technique that can provide geometric structural information on key reaction intermediates of Fe-containing systems when utilized in combination with density functional theory (DFT). However, in the case of binuclear non-heme iron enzymes, DFT-predicted NRVS spectra have been found to be sensitive to truncation method used to model the active sites of the enzymes. Therefore, in this study various-level truncation schemes have been tested to predict the NRVS spectrum of a binuclear non-heme iron enzyme, and a reasonably sized DFT model that is suitable for employing the NRVS/DFT combined methodology to characterize binuclear non-heme iron enzymes has been developed.

| S-EPMC5607781 | biostudies-literature

Current Status of COVID-19 Therapies and Drug Repositioning Applications.

Project description:The rapid and global spread of a new human coronavirus (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of COVID-19. Drug repositioning is an attractive approach that can facilitate the drug discovery process by repurposing existing pharmaceuticals to treat illnesses other than their primary indications. Here, we review current information concerning the global health issue of COVID-19 including promising approved drugs and ongoing clinical trials for prospective treatment options. In addition, we describe computational approaches to be used in drug repurposing and highlight examples of in silico studies of drug development efforts against SARS-CoV-2.

| S-EPMC7305759 | biostudies-literature

Putting error bars on density functional theory.

Project description:Predicting the error in density functional theory (DFT) calculations due to the choice of exchange-correlation (XC) functional is crucial to the success of DFT, but currently, there are limited options to estimate this a priori. This is particularly important for high-throughput screening of new materials. In this work, the structure and elastic properties of binary and ternary oxides are computed using four XC functionals: LDA, PBE-GGA, PBEsol, and vdW-DF with C09 exchange. To analyze the systemic errors inherent to each XC functional, we employed materials informatics methods to predict the expected errors. The predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide "error bars" for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials.

| S-EPMC11364665 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data