Issue 8, 2021

De novo molecular drug design benchmarking

Abstract

De novo molecular design for drug discovery is a growing field. Deep neural networks (DNNs) are becoming more widespread in their use for machine learning models. As more DNN models are proposed for molecular design, benchmarking methods are crucial for the comparision and validation of these models. This review looks at recently proposed benchmarking methods Fréchet ChemNet Distance, GuacaMol and Molecular Sets (MOSES), and provides a commentary on their future potential applications in de novo molecular drug design and possible next steps for further validation of these benchmarking methods.

Graphical abstract: De novo molecular drug design benchmarking

Article information

Article type
Review Article
Submitted
07 Marts 2021
Accepted
24 Maijs 2021
First published
03 Jūn. 2021

RSC Med. Chem., 2021,12, 1273-1280

De novo molecular drug design benchmarking

L. L. Grant and C. S. Sit, RSC Med. Chem., 2021, 12, 1273 DOI: 10.1039/D1MD00074H

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