Evidence map›Paper›PMID 42786569›Full record

ArticleBioinformatics (Oxford, England)2026

DesignMaster: a multi-conditional diffusion framework for rational PROTAC design.

Binze Shi, Yi Hao, Jie Liu, Tong Pan, Luke Isbel, Michael Roy, Ashley P Ng, Xuequn Shang, Fuyi Li

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Binze ShiSchool of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi 710129, China.
Yi HaoSouth Australian immunoGENomics Cancer Institute (SAiGENCI), Adelaide University, Adelaide, SA 5005, Australia.
Jie LiuSouth Australian immunoGENomics Cancer Institute (SAiGENCI), Adelaide University, Adelaide, SA 5005, Australia.
Tong PanSouth Australian immunoGENomics Cancer Institute (SAiGENCI), Adelaide University, Adelaide, SA 5005, Australia.
Luke IsbelSouth Australian immunoGENomics Cancer Institute (SAiGENCI), Adelaide University, Adelaide, SA 5005, Australia.
Michael RoySouth Australian immunoGENomics Cancer Institute (SAiGENCI), Adelaide University, Adelaide, SA 5005, Australia.
Ashley P NgWalter and Eliza Hall Institute of Medical Research, Parkville, VIC 3050, Australia.ORCID 0000-0001-9690-0879
Xuequn ShangSchool of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi 710129, China.
Fuyi LiSouth Australian immunoGENomics Cancer Institute (SAiGENCI), Adelaide University, Adelaide, SA 5005, Australia.ORCID 0000-0001-5216-3213

Funding

Australian National Health and Medical Research Council 2041439South Australian immunoGENomics Cancer Institute
6 · The paper itself

Abstract

motivationProteolysis-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.

resultsTo 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.

Indexed as

Computational BiologySoftwareModels, MolecularProteolysisProteolysis Targeting ChimeraUbiquitin-Protein LigasesProteolysis Targeting ChimeraUbiquitin-Protein Ligases

Identifiers

PMID42786569
PMCPMC13649183

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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.