ArticleJournal of chemical theory and computation2019
Quantitative Characterization of Protein-Lipid Interactions by Free Energy Simulation between Binary Bilayers.
Article in Journal of chemical theory and computation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Gramicidin A in Asymmetric Lipid Membranes.Biomolecules · 2024Article
- Energetics of the Transmembrane Peptide Sorting by Hydrophobic Mismatch.The journal of physical chemistry letters · 2024Article
- Enhanced Sampling Molecular Dynamics Simulations Reveal Transport Mechanism of Glycoconjugate Drugs through GLUT1.International journal of molecular sciences · 2024Article
- Alteration of Average Thickness of Lipid Bilayer by Membrane-Deforming Inclusions.Biomolecules · 2023Article
- Unsaturated Lipids Facilitate Partitioning of Transmembrane Peptides into the Liquid Ordered Phase.Journal of chemical theory and computation · 2023Article
- Efficient calculation of the free energy for protein partitioning using restraining potentials.Biophysical journal · 2023Article
- Initiation and evolution of pores formed by influenza fusion peptides probed by lysolipid inclusion.Biophysical journal · 2023Article
Corrections and comments
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Authors and funding
5 authors at 5 institutions in 2 countries.
Funding
Abstract
Using a recently developed binary bilayer system (BBS) consisting of two patches of laterally contacting bilayers, umbrella sampling molecular dynamics (MD) simulations were performed for quantitative characterization of protein-lipid interactions. The BBS is composed of 1,2-dilauroyl-
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Registered trials
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.