ArticleNature communications2025
Discovery of a bifunctional PKMYT1-targeting PROTAC empowered by AI-generation.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- GNPS-assisted identification of bioactive constituents fromRSC advances · 2026Article
- Advancing PROTAC therapeutics through chemistry-guided design of smart delivery systems.Acta pharmacologica Sinica · 2026Review
- Multi-objective optimization in the context of generative chemistry.Nature communications · 2026Review
- Design, Synthesis, Biological Activity Evaluation, and Molecular Docking of 2-Aminopyrimidine-Based PKMYT1 Inhibitors.Biomedicines · 2026Article
- Phenols: From Replacing to Embracing.ChemMedChem · 2026Review
- Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi-scenario applications, and translational prospects.Smart molecules : open access · 2026Review
- Post-translational modifications in metabolic reprogramming: implications for metabolic therapy and immunotherapy in cancer.Signal transduction and targeted therapy · 2026Review
- Computational mapping of productive POI-E3 ligase conformations to guide de novo degrader design: application to WEE1 and PKMYT1 PROTACs.Journal of cheminformatics · 2026Article
- PKMYT1 in Cancer: Beyond Cell Cycle Checkpoints to Context-Dependent Therapeutic Vulnerability.Genes, chromosomes & cancer · 2026Review
- Scorpion gut microbiomes as a source of bioactive and rare actinobacteria with nonribosomal peptide potential.Antonie van Leeuwenhoek · 2026Article
- PROTAC-mediated multi-target protein degradation in Alzheimer's disease: mechanistic insights, therapeutic applications, and translational challenges.RSC medicinal chemistry · 2026Review
- Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- Defining the Active Conformation of Typical Protein Kinase Domains from Substrate-Bound PDB Structures Enables Active-State AlphaFold2 Models for All 437 Human Catalytic Protein Kinases.bioRxiv : the preprint server for biology · 2026Article
- Integrating artificial intelligence across the cancer drug discovery pipeline using a design-test-refine workflow.Frontiers in oncology · 2026Review
- E3 ubiquitin ligases: structural diversity, dysregulation in disease, and their emerging role in targeted therapeutic strategies.Frontiers in molecular biosciences · 2026Review
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PKMYT1 has recently emerged as a compelling therapeutic target for precision cancer therapy due to its synthetic lethality with oncogenic alterations such as CCNE1 amplification and mutations in FBXW7 and PPP2R1A. Current small molecule PKMYT1 inhibitors face limitations, such as insufficient molecular diversity and poor selectivity. We herein use our generative AI platform to develop a bifunctional PKMYT1 degrader by linking an entirely novel PKMYT1 inhibitor to an optimized cereblon (CRBN) binder. The lead PROTAC D16-M1P2 demonstrates dual mechanisms of PKMYT1 degradation and inhibition, with strong antiproliferative potency facilitated by high selectivity. It also exhibits favorable oral bioavailability, stronger pharmacodynamic effects relative to the PKMYT1 inhibitor alone, and robust antitumor response as a monotherapy in xenograft models. This PROTAC serves as a precise chemical probe to explore PKMYT1 biology and a promising lead for further cancer therapy exploration.
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Registered trials
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.