Ramirez · Frontiers in chemistry 2021 · In vitro chromatographic and in silico QSAR/QSRR modeling study · n=28 compounds

Permeability Data of Organosulfur Garlic Compounds Estimated by Immobilized Artificial Membrane Chromatography: Correlation Across Several Biological Barriers.

Cited 14 times in the scientific literature.

Level 5 - mechanism / opinion, no new human data

In vitro chromatography and in silico modeling study without human or animal subjects

PubMed 34616711 · doi:10.3389/fchem.2021.690707 · record verified 2026-08-28

What was done

The authors measured chromatographic capacity factors (log k' (IAM)) for 28 garlic-derived organosulfur compounds (OSCs) using immobilized artificial membrane high-performance liquid chromatography (IAM-HPLC). They developed quantitative structure-retention relationship (QSRR) models to determine the molecular descriptors influencing retention. They subsequently evaluated the correlation between IAM retention parameters and predicted absorption, distribution, metabolism, and excretion (ADME) profiles—specifically human gastrointestinal absorption (HIA), blood-brain barrier (BBB) permeation, and skin permeability—modeled via SwissADME and PreADMET web tools using chemometric approaches.

What was found

The abstract reports no specific numerical values, correlation coefficients, or statistical metrics. Qualitatively, IAM retention was primarily governed by hydrophobic factors, with contributions from molecular flexibility and electronic descriptors (relative negative charge and Mulliken electronegativity). The predicted ADME properties (HIA, BBB, and skin permeability) were reported to be strongly dependent on the experimental hydrophobic factors derived from log k' (IAM).

Why it matters

Demonstrating that IAM-HPLC retention correlates with computational barrier-permeability models provides an efficient, animal-free screening tool to estimate the pharmacokinetic properties of garlic-derived organosulfur compounds before in vivo testing.

Limits

The study is restricted to in vitro chromatographic measurements and computational (in silico) predictions, with no direct in vivo human or animal pharmacokinetic validation. Specific quantitative metrics (such as R², Q², or error estimates) are omitted from the abstract. The sample size is limited to 28 organosulfur compounds.

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