ArticleJournal of computer-aided molecular design2023
DeepCubist: Molecular Generator for Designing Peptidomimetics based on Complex three-dimensional scaffolds.
Article in Journal of computer-aided molecular design, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Beyond Simple Mimicry: Next-Generation Geometric Architectures and Future Paradigms in Small-Molecule and Macrocyclic Peptidomimetics.Angewandte Chemie (International ed. in English) · 2026Review
- Hot-Spot-Guided Generative Deep Learning for Drug-Like PPI Inhibitor Design.Interdisciplinary sciences, computational life sciences · 2026Article
- Using generative AI to transform peptide hits into small molecule leads.Beilstein journal of organic chemistry · 2026Article
- Design methods for antimicrobial peptides with improved performance.Zoological research · 2023Review
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Authors and funding
6 authors.
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Abstract
Mimicking bioactive conformations of peptide segments involved in the formation of protein-protein interfaces with small molecules is thought to represent a promising strategy for the design of protein-protein interaction (PPI) inhibitors. For compound design, the use of three-dimensional (3D) scaffolds rich in sp3-centers makes it possible to precisely mimic bioactive peptide conformations. Herein, we introduce DeepCubist, a molecular generator for designing peptidomimetics based on 3D scaffolds. Firstly, enumerated 3D scaffolds are superposed on a target peptide conformation to identify a preferred template structure for designing peptidomimetics. Secondly, heteroatoms and unsaturated bonds are introduced into the template via a deep generative model to produce candidate compounds. DeepCubist was applied to design peptidomimetics of exemplary peptide turn, helix, and loop structures in pharmaceutical targets engaging in PPIs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.