Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model

The design of pharmaceutically relevant compounds that mimic bioactive peptides or secondary structure elements in proteins is an important task in medicinal chemistry. Over time, various chemical strategies have been developed to convert natural peptide ligands into so-called peptidomimetics. This...

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Main Authors: Atsushi Yoshimori, Jürgen Bajorath
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:European Journal of Medicinal Chemistry Reports
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Online Access:http://www.sciencedirect.com/science/article/pii/S2772417425000056
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author Atsushi Yoshimori
Jürgen Bajorath
author_facet Atsushi Yoshimori
Jürgen Bajorath
author_sort Atsushi Yoshimori
collection DOAJ
description The design of pharmaceutically relevant compounds that mimic bioactive peptides or secondary structure elements in proteins is an important task in medicinal chemistry. Over time, various chemical strategies have been developed to convert natural peptide ligands into so-called peptidomimetics. This process is supported by computational approaches to identify peptidomimetic candidate compounds or design templates mimicking active peptide conformations. However, generating peptidomimetics continues to be challenging. Chemical language models (CLMs) offer new opportunities for molecular design. Therefore, we have revisited computational design of peptidomimetics from a different perspective and devised a CLM to directly transform input peptides into peptidomimetic candidates, without requiring intermediate states. A critically important aspect of the approach has been the generation of training data for effective learning that was guided by a quantitative measure of peptide-likeness such that the CLM could implicitly capture transitions from peptides or peptide-like molecules to compounds with reduced or eliminated peptide character. Herein, we introduce the CLM for peptidomimetics design and establish proof-of-principle for the approach. For given input peptides, both the general model and a version fine-tuned for a specific application were shown to produce a spectrum of candidate compounds with varying similarity, gradually changing chemical features, and diminishing peptide-likeness. As a part of our study, the CLM and data are provided.
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spelling doaj-art-72bad6f22b8d4ec192f68ccc4e02b25e2025-01-30T05:15:13ZengElsevierEuropean Journal of Medicinal Chemistry Reports2772-41742025-04-0113100249Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language modelAtsushi Yoshimori0Jürgen Bajorath1Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, University of Bonn, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, Germany; Lamarr Institute for Machine Learning and Artificial Intelligence, University of Bonn, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, Germany; Institute for Theoretical Medicine, Inc., 26-1 Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-0012, JapanDepartment of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, University of Bonn, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, Germany; Lamarr Institute for Machine Learning and Artificial Intelligence, University of Bonn, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, Germany; Corresponding author. Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, University of Bonn, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, Germany.bajorath@bit.uni-bonn.deThe design of pharmaceutically relevant compounds that mimic bioactive peptides or secondary structure elements in proteins is an important task in medicinal chemistry. Over time, various chemical strategies have been developed to convert natural peptide ligands into so-called peptidomimetics. This process is supported by computational approaches to identify peptidomimetic candidate compounds or design templates mimicking active peptide conformations. However, generating peptidomimetics continues to be challenging. Chemical language models (CLMs) offer new opportunities for molecular design. Therefore, we have revisited computational design of peptidomimetics from a different perspective and devised a CLM to directly transform input peptides into peptidomimetic candidates, without requiring intermediate states. A critically important aspect of the approach has been the generation of training data for effective learning that was guided by a quantitative measure of peptide-likeness such that the CLM could implicitly capture transitions from peptides or peptide-like molecules to compounds with reduced or eliminated peptide character. Herein, we introduce the CLM for peptidomimetics design and establish proof-of-principle for the approach. For given input peptides, both the general model and a version fine-tuned for a specific application were shown to produce a spectrum of candidate compounds with varying similarity, gradually changing chemical features, and diminishing peptide-likeness. As a part of our study, the CLM and data are provided.http://www.sciencedirect.com/science/article/pii/S2772417425000056PeptidesPeptidomimeticsGenerative molecular designChemical language modelsPeptide-to-compound mapping
spellingShingle Atsushi Yoshimori
Jürgen Bajorath
Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model
European Journal of Medicinal Chemistry Reports
Peptides
Peptidomimetics
Generative molecular design
Chemical language models
Peptide-to-compound mapping
title Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model
title_full Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model
title_fullStr Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model
title_full_unstemmed Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model
title_short Direct conversion of peptides into diverse peptidomimetics using a transformer-based chemical language model
title_sort direct conversion of peptides into diverse peptidomimetics using a transformer based chemical language model
topic Peptides
Peptidomimetics
Generative molecular design
Chemical language models
Peptide-to-compound mapping
url http://www.sciencedirect.com/science/article/pii/S2772417425000056
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