Evidence map›Paper›PMID 42724590›Full record

ArticleAmerican journal of cancer research2026

AI-assisted design and virtual profiling of targeted degraders for pancreatic cancer therapy via PROTAC technology.

Bing Du, Kunjie Wang, Zhu Wu, Shaofan Qiu, Filippiadis Dimitrios Konstantinos, Shuo Yu

Abstract read
In one paragraph

Article in American journal of cancer research, 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

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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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

6 authors.

Bing DuDepartment of Oncology, The Second Hospital of Hebei Medical University Shijiazhuang 050000, Hebei, China.
Kunjie WangDepartment of Oncology, Affiliated Hospital of Hebei University Baoding 071000, Hebei, China.
Zhu WuThe Hunan Provincial Key Laboratory of The TCM Agricultural Biogenomics, Changsha Medical University Changsha 410219, Hunan, China.
Shaofan QiuDepartment of Gastrointestinal Surgery, The Second Hospital of Hebei Medical University Shijiazhuang 050000, Hebei, China.
Filippiadis Dimitrios KonstantinosEvgenidion University Hospital Athens 11528, Greece.
Shuo YuDepartment of Surgical Oncology, The Second Hospital of Hebei Medical University Shijiazhuang 050000, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer remains one of the most lethal malignancies because of late diagnosis, aggressive progression, therapy resistance, and limited effective treatment options. Bromodomain-containing protein 4 (BRD4) is an important epigenetic regulator implicated in pancreatic cancer progression through its role in transcriptional control, cell proliferation, and survival signaling. Targeted protein degradation using proteolysis-targeting chimeras (PROTACs) offers a potential strategy for eliminating disease-associated proteins through ubiquitin-proteasome-mediated degradation rather than transient pharmacological inhibition. In this study, an AI-assisted and structure-guided computational workflow was used to design and virtually prioritize BRD4-targeting PROTAC candidates recruiting DCAF15 as the E3 ligase component. The workflow integrated protein-structure evaluation, pharmacophore-based ligand screening, ADMET and Lipinski filtering, binary protein-ligand docking, molecular-interaction analysis, rational linker selection, BRD4-DCAF15 protein-protein docking, PROTAC-mediated ternary-complex docking, and molecular dynamics simulation. The results identified CLTTMPBA-linker-E7820 as a computationally prioritized PROTAC architecture with favorable predicted binding behavior, residue-level interaction patterns, and simulated ternary-complex stability. Importantly, this study is entirely computational and should be interpreted as an early-stage in silico prioritization framework rather than experimental evidence of BRD4 degradation or anticancer efficacy. The proposed BRD4-DCAF15 PROTAC candidates represent lead hypotheses that require biochemical, cellular, pharmacological, and in vivo validation, including confirmation of target engagement, ternary-complex formation, proteasome-dependent BRD4 degradation, downstream transcriptional modulation, pancreatic cancer cell inhibition, selectivity, pharmacokinetics, toxicity, and antitumor efficacy.

Indexed as

AI-assisted drug designBRD4 oncogenic proteinPancreatic cancerPROTAC technologytargeted protein degradation

Identifiers

PMID42724590
PMCPMC13559328

What OpenQuestion holds

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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.