Issue 28, 2022

A focus on simulation and machine learning as complementary tools for chemical space navigation

Abstract

Computer-aided molecular design benefits from the integration of two complementary approaches: machine learning and first-principles simulation. Mohr et al. (B. Mohr, K. Shmilovich, I. S. Kleinwächter, D. Schneider, A. L. Ferguson and T. Bereau, Chem. Sci., 2022, 13, 4498–4511, https://pubs.rsc.org/en/content/articlelanding/2022/sc/d2sc00116k) demonstrated the discovery of a cardiolipin-selective molecule via the combination of coarse-grained molecular dynamics, alchemical free energy calculations, Bayesian optimization and interpretable regression to reveal design principles.

Graphical abstract: A focus on simulation and machine learning as complementary tools for chemical space navigation

Article information

Article type
Commentary
First published
11 jul. 2022
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2022,13, 8221-8223

A focus on simulation and machine learning as complementary tools for chemical space navigation

M. Aldeghi and C. W. Coley, Chem. Sci., 2022, 13, 8221 DOI: 10.1039/D2SC90130G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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