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Biochemical and Structural Characterization of the Carbohydrate Transport Substrate-binding-protein SP0092

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Published on: October 2, 2017

QSPR modelling with the topological substructural molecular design approach: beta-cyclodextrin complexation.

Alfonso Pérez-Garrido¹, Aliuska Morales Helguera, M Natália D S Cordeiro

¹Environmental Engineering and Toxicology Department, Catholic University of San Antonio, Guadalupe, Murcia, C.P. 30107, Spain. aperez@pdi.ucam.edu

Journal of Pharmaceutical Sciences

|June 9, 2009

Summary

This study developed a quantitative structure-property relationship (QSPR) model to predict beta-cyclodextrin (beta-CD) complexation. The model highlights hydrophobicity and van der Waals forces as key drivers for complex stability in organic compounds.

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Published on: October 20, 2021

Area of Science:

Computational Chemistry
Molecular Modeling
Supramolecular Chemistry

Background:

Beta-cyclodextrins (beta-CDs) are widely used host molecules in various applications.
Predicting the complexation stability of beta-CDs with diverse organic compounds is crucial for optimizing their use.
Existing methods for predicting complexation may lack accuracy or applicability across a broad range of guest molecules.

Purpose of the Study:

To develop a robust quantitative structure-property relationship (QSPR) model for predicting beta-cyclodextrin (beta-CD) complex stability constants.
To identify key molecular descriptors influencing the complexation of organic compounds with beta-CDs.
To establish a predictive tool based on topological substructural molecular design (TOPS-MODE) descriptors.

Main Methods:

Computation of molecular descriptors using the TOPological Substructural MOlecular DEsign (TOPS-MODE) approach.
Correlation of computed descriptors with experimental beta-CD complex stability constants using linear multivariate data analysis.
Validation of the QSPR model through internal cross-validation and external prediction datasets.

Main Results:

A QSPR model was developed, explaining approximately 86% of the variance in experimental beta-CD complexation data.
The model demonstrated good internal cross-validation statistics and strong predictivity on unseen external data.
Analysis of the model identified hydrophobicity and van der Waals interactions as primary driving forces for beta-CD complexation.

Conclusions:

The developed QSPR model provides an accurate and reliable method for predicting beta-CD complexation abilities of organic compounds.
Hydrophobic groups and bulky substituents significantly enhance the complexation of molecules with beta-CDs.
This study presents the first reported correlation between TOPS-MODE descriptors and beta-CD complexing abilities, offering new insights into host-guest interactions.