Document type

Article

Version

Published version

Publication date

Publication license

cc by (c) Comajuncosa Creus, Arnau et al, 2023
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/214861

Stereochemically-aware bioactivity descriptors for uncharacterized chemical compounds

Journal Title

Director/Tutor

Journal ISSN

Volume Title

Abstract

Stereochemistry plays a fundamental role in pharmacology. Here, we systematically investigate the relationship between stereoisomerism and bioactivity on over 1 M compounds, finding that a very significant fraction (~ 40%) of spatial isomer pairs show, to some extent, distinct bioactivities. We then use the 3D representation of these molecules to train a collection of deep neural networks (Signaturizers3D) to generate bioactivity descriptors associated to small molecules, that capture their effects at increasing levels of biological complexity (i.e. from protein targets to clinical outcomes). Further, we assess the ability of the descriptors to distinguish between stereoisomers and to recapitulate their different target binding profiles. Overall, we show how these new stereochemically-aware descriptors provide an even more faithful description of complex small molecule bioactivity properties, capturing key differences in the activity of stereoisomers.

Subject (English)

Citation

Citation

COMAJUNCOSA CREUS, Arnau, et al. Stereochemically-aware bioactivity descriptors for uncharacterized chemical compounds. Journal Of Cheminformatics. 2024. Vol. 16, num. 1. ISSN 1758-2946. [consulted: 8 of June of 2026]. Available at: https://hdl.handle.net/2445/214861

Export metadata

JSON - METS

Share record