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Updated: Jul 11, 2025

Use of Microscale Thermophoresis to Measure Protein-Lipid Interactions
Published on: February 10, 2022
Addressing the complexities in measuring cyclodextrin-sterol binding constants: A multidimensional study
Amelia M Anderson1, Ilse Manet2, Milo Malanga3
1Cyclarity Therapeutics, 8001 Redwood Blvd Novato, CA 94945, USA; Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, E-15782 Santiago de Compostela, Spain; Departamento de Química Orgánica, Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares (CiQUS), Universidade de Santiago de Compostela, Campus Vida s/n, E-15782 Santiago de Compostela, Spain.
Abstract:
A class of cyclodextrin (CD) dimers has emerged as a potential new treatment for atherosclerosis; they work by forming strong, soluble inclusion complexes with oxysterols, allowing the body to reduce and heal arterial plaques. However, characterizing the interactions between CD dimers and oxysterols presents formidable challenges due to low sterol solubility, the synthesis of modified CDs resulting in varying number and position of molecular substitutions, and the diversity of interaction mechanisms. To address these challenges and illuminate the nuances of CD-sterol interactions, we have used multiple orthogonal approaches for a comprehensive characterization. Results obtained from three independent techniques - metadynamics simulations, competitive isothermal titration calorimetry, and circular dichroism - to quantify CD-sterol binding are presented. The objective of this study is to obtain the binding constants and gain insights into the intricate nature of the system, while accounting for the advantages and limitations of each method. Notably, our findings demonstrate ∼1000× stronger affinity of the CD dimer for 7-ketocholesterol in comparison to cholesterol for the 1:1 complex in direct binding assays. These methodologies and findings not only enhance our understanding of CD dimer-sterol interactions, but could also be generally applicable to prediction and quantification of other challenging host-guest complex systems.

