Predicting Macrocyclic Molecular Recognition with Machine Learning

13 August 2019, Version 1
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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