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Quantifying Small-Molecule Association with Lipid Membranes: Methods, Models, and Limitations

Submitted:

13 May 2026

Posted:

13 May 2026

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Abstract
The association of small molecules with lipid membranes plays a central role in drug delivery, pharmacokinetics, toxicity, and membrane biophysics, also being of fundamental importance in drug pharmacodynamics given that most drug targets are membrane-associated proteins. Accurate determination of solute–membrane association affinities, however, remains challenging due to the diversity of experimental systems, the complexity of membrane environments, and the intrinsic limitations of individual methodologies. This review provides a comprehensive overview of the experimental and computational approaches currently used to quantify small molecules association with lipid membranes. Standard experimental techniques, including spectroscopy-based methods, calorimetry, electrophoretic measurements, and surface-sensitive approaches, are discussed alongside established computational strategies ranging from continuum models to atomistic molecular dynamics simulations. Particular emphasis is placed on the formalisms required for data analysis, including partitioning models and thermodynamic frameworks, as well as on the assumptions underlying each method. The validity limits, sources of uncertainty, and common experimental and interpretative pitfalls are critically examined. By providing a unified and comparative perspective, this work establishes a structured framework for the quantitative study of solute–membrane interactions, guiding new researchers in the selection of appropriate methodologies and in the rigorous analysis of experimental and computational results. Moreover, it enables the consistent and quantitative rationalization of affinity parameters reported across the literature, supporting the development of curated datasets and predictive relationships that can inform the design of new and more effective drugs.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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