Electron density-based GPT for optimization and suggestion of host–guest binders

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dc.contributor.authorParrilla-Gutiérrez, Juan M.
dc.contributor.authorGranda, Jarosław M.
dc.contributor.authorAyme, Jean-François
dc.contributor.authorBajczyk, Michał D.
dc.contributor.authorWilbraham, Liam
dc.contributor.authorCronin, Leroy
dc.contributor.organizationSchool of Chemistry, University of Glasgow
dc.contributor.organizationSchool of Computing, Engineering and Built Environment, Glasgow Caledonian University
dc.contributor.organizationInstitute of Organic Chemistry, Polish Academy of Sciences
dc.date.accessioned2024-09-02T14:39:20Z
dc.date.available2024-09-02T14:39:20Z
dc.date.issued2024
dc.description.abstractHere 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).en
dc.description.sponsorshipEPSRC (grant nos. EP/L023652/1, EP/R020914/1, EP/S030603/1, EP/R01308X/1, EP/S017046/1 and EP/S019472/1); ERC (project no. 670467 SMART-POM); EC (project no. 766975 MADONNA); DARPA (project nos. W911NF-18- 2-0036, W911NF-17-1-0316 and HR001119S0003); Polish National Agency for Academic Exchange grant number PPN/PPO/2020/1/00034; National Science Center Poland grant number 2021/01/1/ST4/00007.
dc.identifier.citationNat Comput Sci 4, 200–209 (2024) ; https://doi.org/10.1038/s43588-024-00602-x
dc.identifier.doi10.1038/s43588-024-00602-x
dc.identifier.issn2662-8457
dc.identifier.urihttps://open.icm.edu.pl/handle/123456789/24796
dc.language.isoen
dc.publisherNature Portfolio
dc.rightsUznanie autorstwa 4.0 Międzynarodoween
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceNature Computational Science
dc.titleElectron density-based GPT for optimization and suggestion of host–guest bindersen
dc.typearticle
dc.type.versionpublishedVersion
person.identifier.orcidGranda, Jarosław M. [0000-0002-5058-7669]
person.identifier.orcidCronin, Leroy [0000-0001-8035-5757]
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