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Predicting Macrocyclic Molecular Recognition with Machine Learning

13 August 2019, Version 1
Working Paper
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

DFT, NMR, ITC, and cell confluence data are used to generate predictive algorithms of supramolecular binding to cucurbit[7]uril and experimentally validate these predictions.

Keywords

Machine learning
Supramolecular interactions
Cucurbituril

Supplementary materials

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Version History

Aug 13, 2019 Version 1

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The content is available under CC BY NC ND 4.0 [opens in a new tab]

DOI

10.26434/chemrxiv.9540068.v1
D O I: 10.26434/chemrxiv.9540068.v1 [opens in a new tab]

Author’s competing interest statement

None

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