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Cavity Characterization in Supramolecular Cages.

Cavity Characterization in Supramolecular Cages.

Authors :
Guerra JVS
Alves LFG
Bourissou D
Lopes-de-Oliveira PS
Szalóki G
Source :
Journal of chemical information and modeling [J Chem Inf Model] 2023 Jun 26; Vol. 63 (12), pp. 3772-3785. Date of Electronic Publication: 2023 May 02.
Publication Year :
2023

Abstract

Confining molecular guests within artificial hosts has provided a major driving force in the rational design of supramolecular cages with tailored properties. Over the last 30 years, a set of design strategies have been developed that enabled the controlled synthesis of a myriad of cages. Recently, there has been a growing interest in involving in silico methods in this toolbox. Cavity shape and size are important parameters that can be easily accessed by inexpensive geometric algorithms. Although these algorithms are well developed for the detection of nonartificial cavities (e.g., enzymes), they are not routinely used for the rational design of supramolecular cages. In order to test the capabilities of this tool, we have evaluated the performance and characteristics of seven different cavity characterization software in the context of 22 analogues of well-known supramolecular cages. Among the tested software, KVFinder project and Fpocket proved to be the most software to characterize supramolecular cavities. With the results of this work, we aim to popularize this underused technique within the supramolecular community.

Subjects

Subjects :
Algorithms
Software

Details

Language :
English
ISSN :
1549-960X
Volume :
63
Issue :
12
Database :
MEDLINE
Journal :
Journal of chemical information and modeling
Publication Type :
Academic Journal
Accession number :
37129917
Full Text :
https://doi.org/10.1021/acs.jcim.3c00328