Parrilla-Gutiérrez, J. M. , Granda, J. M., Ayme, J.-F., Bajczyk, M. D., Wilbraham, L. and Cronin, L. (2024) Electron density-based GPT for optimization and suggestion of host–guest binders. Nature Computational Science, (doi: 10.1038/s43588-024-00602-x) (Early Online Publication)
![[img]](https://eprints.gla.ac.uk/style/images/fileicons/text.png) |
Text
318921.pdf - Published Version Available under License Creative Commons Attribution. 2MB |
Abstract
Here we present a machine learning model trained on electron density for the production of host–guest binders. These are read out as simplified molecular-input line-entry system (SMILES) format with >98% accuracy, enabling a complete characterization of the molecules in two dimensions. Our model generates three-dimensional representations of the electron density and electrostatic potentials of host–guest systems using a variational autoencoder, and then utilizes these representations to optimize the generation of guests via gradient descent. Finally the guests are converted to SMILES using a transformer. The successful practical application of our model to established molecular host systems, cucurbit[n]uril and metal–organic cages, resulted in the discovery of 9 previously validated guests for CB[6] and 7 unreported guests (with association constant Ka ranging from 13.5 M−1 to 5,470 M−1) and the discovery of 4 unreported guests for [Pd214]4+ (with Ka ranging from 44 M−1 to 529 M−1).
| Item Type: | Articles |
|---|---|
| Additional Information: | L.C. gratefully acknowledges financial support from the EPSRC (grant nos. EP/L023652/1, EP/R020914/1, EP/S030603/1, EP/R01308X/1, EP/S017046/1 and EP/S019472/1), the ERC (project no. 670467 SMART-POM), the EC (project no. 766975 MADONNA) and DARPA (project nos. W911NF-18- 2-0036, W911NF-17-1-0316 and HR001119S0003). J.M.G. acknowledges financial support from the Polish National Agency for Academic Exchange grant number PPN/PPO/2020/1/00034 and the National Science Center Poland grant number 2021/01/1/ST4/00007. |
| Status: | Early Online Publication |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Ayme, Dr Jean-Francois and Granda, Dr Jaroslaw and Cronin, Professor Lee and Parrilla Gutierrez, Dr Juanma and Wilbraham, Mr Liam |
| Authors: | Parrilla-Gutiérrez, J. M., Granda, J. M., Ayme, J.-F., Bajczyk, M. D., Wilbraham, L., and Cronin, L. |
| College/School: | College of Science and Engineering > School of Chemistry |
| Journal Name: | Nature Computational Science |
| Publisher: | Nature Research |
| ISSN: | 2662-8457 |
| ISSN (Online): | 2662-8457 |
| Published Online: | 08 March 2024 |
| Copyright Holders: | Copyright © 2024, The Author(s) |
| First Published: | First published in Nature Computational Science 2024 |
| Publisher Policy: | Reproduced under a Creative Commons licence |
University Staff: Request a correction | Enlighten Editors: Update this record
Funder and Project Information
Funder and Project Information