Cocrystal Prediction by Artificial Neural Networks

24 June 2020, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

A significant amount of attention has been given to the design and synthesis of cocrystals by both industry and academia because of its potential to change a molecule’s physicochemical properties. This paper reports on the application of a data-driven cocrystal prediction method, based on two types of artificial neural network models and cocrystal data present in the Cambridge Structural Database. The models accept pairs of coformers and predict whether a cocrystal is likely to form.

Keywords

Cocrystals
Cambridge Structural Database analysis
Artificial neural network
Deep Learning Applications
Link Prediction

Supplementary materials

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Cocrystal prediction by artificial neural networks - Supplementary Information Version 2
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