ArticlePloS one2018
Implicit-solvent dissipative particle dynamics force field based on a four-to-one coarse-grained mapping scheme.
Article in PloS one, 2018. 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
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.
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.
Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Cytochrome c Facilitates Binding between Lipid Bilayers and Citrate-Coated Gold Nanoparticles in Coarse-Grained Simulations.Journal of chemical theory and computation · 2025Article
- Computational Methods for Modeling Lipid-Mediated Active Pharmaceutical Ingredient Delivery.Molecular pharmaceutics · 2025Review
- Construction of Multiscale Dissipative Particle Dynamics (DPD) Models from Other Coarse-Grained Models.ACS omega · 2024Article
- Mesoscale simulations: An indispensable approach to understand biomembranes.Biophysical journal · 2023Review
- Systematic Parameterization of Ion-Surfactant Interactions in Dissipative Particle Dynamics Using Setschenow Coefficients.The journal of physical chemistry. B · 2022Article
- Translation of Chemical Structure into Dissipative Particle Dynamics Parameters for Simulation of Surfactant Self-Assembly.The journal of physical chemistry. B · 2021Article
- Computational Modeling of Realistic Cell Membranes.Chemical reviews · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new set of efficient solvent-free dissipative particle dynamics (DPD) force fields was developed for phospholipids and peptides. To enhance transferability, this model maps around four heavy atoms and their connected hydrogen atoms into a coarse-grained elementary bead based on functional group. The effective hybrid potential between any pair of beads is composed of a short-range repulsive soft-core potential that directly adopts the form of an explicit-solvent DPD model and a long-range attractive hydrophobic potential. The parameters of the attractive potentials for lipid molecules were obtained by fitting the explicit-solvent DPD simulation of one bead of any type in a water box, then finely tuning it until the bilayer membrane properties obtained in the explicit-solvent model were matched. These parameters were further extended to amino acids according to bead type. The structural and elastic properties of bilayer membranes, free energy profiles for a lipid flip-flop and amino acid analogues translocating across the membrane, and membrane pore formation induced by antimicrobial peptides obtained from this solvent-free DPD force field considerably agreed with the explicit-solvent DPD results. Importantly, the efficiency of this method is guaranteed to accelerate the assembly of vesicles composed of several thousand lipids by up to 50-fold, rendering the experimental liposome dynamics as well as membrane-peptide interactions feasible at accessible computational expense.
Indexed as
Identifiers
What OpenQuestion holds
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.