Issue 87, 2016

The death of the Job plot, transparency, open science and online tools, uncertainty estimation methods and other developments in supramolecular chemistry data analysis

Abstract

Data analysis is central to understanding phenomena in host–guest chemistry. We describe here recent developments in this field starting with the revelation that the popular Job plot method is inappropriate for most problems in host–guest chemistry and that the focus should instead be on systematically fitting data and testing all reasonable binding models. We then discuss approaches for estimating uncertainties in binding studies using case studies and simulations to highlight key issues. Related to this is the need for ready access to data and transparency in the methodology or software used, and we demonstrate an example a webportal (supramolecular.org) that aims to address this issue. We conclude with a list of best-practice protocols for data analysis in supramolecular chemistry that could easily be translated to other related problems in chemistry including measuring rate constants or drug IC50 values.

Graphical abstract: The death of the Job plot, transparency, open science and online tools, uncertainty estimation methods and other developments in supramolecular chemistry data analysis

Supplementary files

Article information

Article type
Feature Article
Submitted
09 5 2016
Accepted
23 8 2016
First published
25 8 2016
This article is Open Access
Creative Commons BY-NC license

Chem. Commun., 2016,52, 12792-12805

Author version available

The death of the Job plot, transparency, open science and online tools, uncertainty estimation methods and other developments in supramolecular chemistry data analysis

D. Brynn Hibbert and P. Thordarson, Chem. Commun., 2016, 52, 12792 DOI: 10.1039/C6CC03888C

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