Evidence map›Paper›PMID 36260519›Full record

ArticleThe journal of physical chemistry. A2022

Computation of Förster Resonance Energy Transfer in Lipid Bilayer Membranes.

Richard Jacobi, David Hernández-Castillo, Novitasari Sinambela, Julian Bösking, Andrea Pannwitz, Leticia González

Abstract read
In one paragraph

Article in The journal of physical chemistry. A, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Red Light Absorption of [ReMolecules (Basel, Switzerland) · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Richard JacobiInstitute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090Vienna, Austria.ORCID 0000-0001-9949-3519
David Hernández-CastilloInstitute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090Vienna, Austria.
Novitasari SinambelaInstitute of Inorganic Chemistry I, Ulm University, Albert-Einstein-Allee 11, 89081Ulm, Germany.
Julian BöskingInstitute of Inorganic Chemistry I, Ulm University, Albert-Einstein-Allee 11, 89081Ulm, Germany.
Andrea PannwitzInstitute of Inorganic Chemistry I, Ulm University, Albert-Einstein-Allee 11, 89081Ulm, Germany.ORCID 0000-0001-9633-0730
Leticia GonzálezInstitute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090Vienna, Austria.ORCID 0000-0001-5112-794X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Calculations of Förster Resonance Energy Transfer (FRET) often neglect the influence of different chromophore orientations or changes in the spectral overlap. In this work, we present two computational approaches to estimate the energy transfer rate between chromophores embedded in lipid bilayer membranes. In the first approach, we assess the transition dipole moments and the spectral overlap by means of quantum chemical calculations in implicit solvation, and we investigate the alignment and distance between the chromophores in classical molecular dynamics simulations. In the second, all properties are evaluated integrally with hybrid quantum mechanical/molecular mechanics (QM/MM) calculations. Both approaches come with advantages and drawbacks, and despite the fact that they do not agree quantitatively, they provide complementary insights on the different factors that influence the FRET rate. We hope that these models can be used as a basis to optimize energy transfers in nonisotropic media.

Indexed as

Fluorescence Resonance Energy TransferQuantum TheoryLipid BilayersMolecular Dynamics SimulationLipid Bilayers

Identifiers

PMID36260519
PMCPMC9639162

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.