DesignMaster: a multi-conditional diffusion framework for rational PROTAC design
- Journal Title
- Bioinformatics
- Abstract
- MOTIVATION: Proteolysis-targeting chimeras (PROTACs) enable targeted protein degradation through ternary complex formation with E3 ubiquitin ligase. However, the rational design of PROTACs remains highly challenging due to limited structure-activity relationship data and the vast conformational diversity of linkers. Existing computational approaches can be broadly divided into structure-based ternary modelling methods and fragment-based linker generation models. Although these approaches have advanced PROTAC design, they typically neglect key physicochemical constraints and linker-length control during the generation process, causing the generated PROTACs to lack balanced structural properties required for effective ternary complex formation with drug-like characteristics. RESULTS: To address these limitations, we propose DesignMaster, a diffusion-based generative framework that explicitly incorporates linker length and physicochemical properties as controllable conditioning signals. DesignMaster employs an E(3)-equivariant graph Transformer with a gated multi-condition fusion module to inject linker length and physicochemical constraints throughout the diffusion process, enabling fine-grained and constraint-aware molecular generation. Experiments on PROTAC-DB 2.0 and 3.0 demonstrate that DesignMaster achieves the best or highly competitive performance across Validity, Uniqueness, and Recovery. The Case study further shows that DesignMaster consistently achieves improved geometric agreement with the reference PROTAC conformations across both the 6W7O and 6HAY complexes, highlighting its potential for practical structure-guided and property-aware PROTAC design. AVAILABILITY: The source code and datasets are available at https://github.com/ABILiLab/DesignMaster.
- Publisher
- Oxford Academic
- Keywords
- Proteolysis Targeting Chimera; *Software; Ubiquitin-Protein Ligases/metabolism/chemistry; Proteolysis; Models, Molecular; *Computational Biology/methods
- Research Division(s)
- Immunology
- PubMed ID
- 42786569
- Publisher's Version
- https://doi.org/10.1093/bioinformatics/btag714
- Open Access at Publisher's Site
https://doi.org/10.1093/bioinformatics/btag714- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2026-10-02 08:19:00
Last Modified: 2026-10-12 01:26:25