REVIEW article
Front. Cell Dev. Biol.
Sec. Cancer Cell Biology
This article is part of the Research TopicMulti-Omics Integration for Precision Oncology: Diagnostic and Prognostic BiomarkerView all 6 articles
Unlocking the Undruggable Spliceosome: Generative AI and Structural Dynamics in Cancer Therapy
Provisionally accepted
- 1Fachhochschule Nordwestschweiz FHNW - Campus Muttenz, Muttenz, Switzerland
- 2Swiss Institute of Bioinformatics, Lausanne, Switzerland
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The spliceosome is a dynamic molecular machine essential for transcriptome diversity, yet its complexity creates specific vulnerabilities in cancer. Recurrent somatic mutations in core factors, particularly SF3B1, U2AF1, and SRSF2, drive malignancies by altering splice-site recognition. Such structural perturbations do not merely drive oncogenesis but manifest as distinctive molecular signatures that can serve as potent diagnostic and prognostic biomarkers. However, therapeutic exploitation of these defects remains challenging. This review argues that unlocking the spliceosome requires a shift from static cryo-EM snapshots to dynamic structural ensembles. We explore how physics-based molecular simulation and enhanced sampling methods are merg-ing with generative AI to identify intermediate states, map cryptic allosteric pockets and target intrinsically disordered regions. Translating these mechanistic insights into the clinic, we evaluate the next generation of therapeutic strategies, ranging from novel molecular biomarkers to rationally designed allosteric modulators and synthetic lethality. Finally, we discuss how deciphering these altered structural dynamics can guide the identification of splicing-derived neoantigens and biomarkers, establishing a roadmap for precision immunotherapy.
Keywords: biomarker, Cancer, Generative AI, molecular dynamics, neoantigens, spliceosome
Received: 23 Dec 2025; Accepted: 29 Jan 2026.
Copyright: © 2026 Steuer and Kahraman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Abdullah Kahraman
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