ArticleRSC advances2024
Modeling the relative response factor of small molecules in positive electrospray ionization.
Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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
2 citing papers in PubMed.
- AI redefine untargeted metabolomics: estimating chemical amounts for a Human Exposome Project.Frontiers in public health · 2026Review
- Ionization efficiency prediction of electrospray ionization mass spectrometry analytes based on molecular fingerprints and cumulative neutral losses.Journal of cheminformatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Technological advancements in liquid chromatography (LC) electrospray ionization (ESI) high-resolution mass spectrometry (HRMS) have made it an increasingly popular analytical technique in non-targeted analysis (NTA) of environmental and biological samples. One critical limitation of current methods in NTA is the lack of available analytical standards for many of the compounds detected in biological and environmental samples. Computational approaches can provide estimates of concentrations by modeling the relative response factor of a compound (RRF) expressed as the peak area of a given peak divided by its concentration. In this paper, we explore the application of molecular dynamics (MD) in the development of a computational workflow for predicting RRF. We obtained measurements of RRF for 48 compounds with LC - quadrupole time-of-flight (QTOF) MS and calculated their RRF. We used the CGenFF force field to generate the topologies and GROMACS to conduct the (MD) simulations. We calculated the Lennard-Jones and Coulomb interactions between the analytes and all other molecules in the ESI droplet, which were then sampled to construct a multilinear regression model for predicting RRF using Monte Carlo simulations. The best performing model showed a coefficient of determination (
Identifiers
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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.