fragSMILES as a chemical string notation for advanced fragment and chirality representation
Generative models have revolutionized de novo drug design, allowing to produce molecules on-demand with desired physicochemical and pharmacological properties. String based molecular representations, such as SMILES (Simplified Molecular Input Line Entry System) and SELFIES (Self-Referencing Embedded Strings), have played a pivotal role in the success of generative approaches, thanks to their capacity to encode atom- and bond- information and ease-of-generation. However, such 'atom-level' string representations could have certain limitations, in terms of capturing information on chirality, and synthetic accessibility of the corresponding designs.In this paper, we present fragSMILES, a novel fragment-based molecular representation in the form of string. fragSMILES encode fragments in a 'chemically-meaningful' way via a novel graph-reduction approach, allowing to obtain an efficient, interpretable, and expressive molecular representation, which also avoids fragment redundancy. fragSMILES contributes to the field of fragment-based representation, by reporting fragments and their 'breaking' bonds independently. Moreover, fragSMILES also embeds information of molecular chirality, thereby overcoming known limitations of existing string notations. When compared with SMILES, SELFIES and t-SMILES for de novo design, the fragSMILES notation showed its promise in generating molecules with desirable biochemical and scaffolds properties.
Authors
- Fabrizio Mastrolorito (ORCID: https://orcid.org/0000-0001-6753-8997)
- Nicola Amoroso (ORCID: https://orcid.org/0000-0003-0211-0783)
- Orazio Nicolotti (ORCID: https://orcid.org/0000-0001-6533-5539)
- Nicola Gambacorta (ORCID: https://orcid.org/0000-0003-1965-1519)
- Maria Vittoria Togo (ORCID: https://orcid.org/0000-0002-5847-1230)
- Fulvio Ciriaco (ORCID: https://orcid.org/0000-0002-0695-6607)
- Daniela Trisciuzzi (ORCID: https://orcid.org/0000-0002-8799-6562)
- Francesca Grisoni (ORCID: https://orcid.org/0000-0001-8552-6615)
- Cosimo Altomare (ORCID: https://orcid.org/0000-0001-5016-5805)
Institutions
- University of Applied Sciences Utrecht (NL)
- University Medical Center Utrecht (NL)
- University of Bari Aldo Moro (IT)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- Communications Chemistry
- Published
- 2025-01-29
- DOI
- https://doi.org/10.1038/s42004-025-01423-3
- Citations
- 12
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 18.05