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Distinctive Supramolecular Features of β-Cyclodextrin Inclusion Complexes with Antidepressants Protriptyline and Maprotiline: A Comprehensive Structural Investigation.

ABSTRACT: Depression, a global mental illness, is worsened due to the coronavirus disease 2019 (COVID-2019) pandemic. Tricyclic antidepressants (TCAs) are efficacious for the treatment of depression, even though they have more side effects. Cyclodextrins (CDs) are powerful encapsulating agents for improving molecular stability, water solubility, and lessening the undesired effects of drugs. Because the atomic-level understanding of the β-CD-TCA inclusion complexes remains elusive, we carried out a comprehensive structural study via single-crystal X-ray diffraction and density functional theory (DFT) full-geometry optimization. Here, we focus on two complexes lining on the opposite side of the β-CD-TCA stability spectrum based on binding constants (K_as) in solution, β-CD-protriptyline (PRT) 1-most stable and β-CD-maprotiline (MPL) 2-least stable. X-ray crystallography unveiled that in the β-CD cavity, the PRT B-ring and MPL A-ring are aligned at a nearly perfect right angle against the O4 plane and primarily maintained in position by intermolecular C-H···π interactions. The increased rigidity of the tricyclic cores is arising from the PRT -CH=CH- bridge widens, and the MPL -CH₂-CH₂- flexure narrows the butterfly angles, facilitating the deepest and shallower insertions of PRT B-ring (1) and MPL A-ring (2) in the distorted round β-CD cavity for better complexation. This is indicated by the DFT-derived complex stabilization energies (ΔE_stbs), although the complex stability orders based on K_as and ΔE_stbs are different. The dispersion and the basis set superposition error (BSSE) corrections were considered to improve the DFT results. Plus, the distinctive 3D arrangements of 1 and 2 are discussed. This work provides the first crystallographic evidence of PRT and MPL stabilized in the β-CD cavity, suggesting the potential application of CDs for efficient drug delivery.

SUBMITTER: Aree T

PROVIDER: S-EPMC8400697 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundIn this study we investigated the predictability of three thermodynamic quantities related to complex formation. As a model system we chose the host-guest complexes of beta-cyclodextrin (beta-CD) with different guest molecules. A training dataset comprised of 176 beta-CD guest molecules with experimentally determined thermodynamic quantities was taken from the literature. We compared the performance of three different statistical regression methods - principal component regression (PCR), partial least squares regression (PLSR), and support vector machine regression combined with forward feature selection (SVMR/FSS) - with respect to their ability to generate predictive quantitative structure property relationship (QSPR) models for DeltaG degrees, DeltaH degrees and DeltaS degrees on the basis of computed molecular descriptors.ResultsWe found that SVMR/FFS marginally outperforms PLSR and PCR in the prediction of DeltaG degrees, with PLSR performing slightly better than PCR. PLSR and PCR proved to be more stable in a nested cross-validation protocol. Whereas DeltaG degrees can be predicted in good agreement with experimental values, none of the methods led to comparably good predictive models for DeltaH degrees. In using the methods outlined in this study, we found that DeltaS degrees appears almost unpredictable. In order to understand the differences in the ease of predicting the quantities, we performed a detailed analysis. As a result we can show that free energies are less sensitive (than enthalpy or entropy) to the small structural variations of guest molecules. This property, as well as the lower sensitivity of DeltaG degrees to experimental conditions, are possible explanations for its greater predictability.ConclusionThis study shows that the ease of predicting DeltaG degrees cannot be explained by the predictability of either DeltaH degrees or DeltaS degrees. Our analysis suggests that the poor predictability of TDeltaS degrees and, to a lesser extent, DeltaH degrees has to do with a stronger dependence of these quantities on the structural details of the complex and only to a lesser extent on experimental error.

Dataset Information

Distinctive Supramolecular Features of β-Cyclodextrin Inclusion Complexes with Antidepressants Protriptyline and Maprotiline: A Comprehensive Structural Investigation.

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