2026-10-11T22:09:39Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34021254 2026-09-29T04:40:08Z category_19 portal_316 item_type_3 month_year_09_2026

Data Sheet 5_Knowledge graph and machine learning-guided virtual screening prioritizes putative blockers of the PSMD11/Rpn6-EBOV glycoprotein interface.csv Yanshuang Wang (13203533) Yuanjian Li (710364) Lin Zhu (192179) Zhiguo Jiang (454686) Qian Tang (218689) Hainan Liu (415631) Yong Hu (171926) Zijing Liu (650545) Ziyi Li (349831) Xinwei Zhou (6176357) Xin Qi (177590) Yinan Liao (25135248) Luya Hu (25135251) Yufeng Wang (274657) Yue Liu (292931) Ziqian An (25135254) Qincai Dong (11011581) Cheng Cao (209409) Pharmacology ADMET Co-IP/MS EBOV GP knowledge graph machine learning molecular docking proteasome PSMD11 Introduction<p>Host-directed antiviral discovery requires a traceable route from host-factor identification to testable molecular hypotheses. This study developed such a workflow around a host factor associated with Ebola virus glycoprotein (EBOV GP).</p>Methods<p>GFP-GP pulldown coupled with co-immunoprecipitation/mass spectrometry was used to identify GP-associated host candidates. A PSMD11/Rpn6-centred workflow integrated knowledge-graph inference, ligand-only machine learning, ADMETlab profiling and interface-guided docking. Candidate prioritization was assessed through score-weight sensitivity analysis, applicability-domain assessment and docking controls addressing seed reproducibility, search convergence, whole-receptor context and macrocycle ring-conformer sensitivity. Docking scores were contextualized against a matched 59-compound library.</p>Results<p>The analysis recovered 424 GP-pulldown-specific host proteins and nominated PSMD11/Rpn6 as a proteostasis anchor. The tier-gated knowledge-graph candidate membership was invariant across the tested weight perturbations, with Spearman rho = 0.998 under equal weighting. The selected ExtraTrees model achieved an AUC of 0.912 for the Ki endpoint. Applicability-domain assessment and ADMET profiling differentiated candidate confidence and predicted liabilities. Docking reproducibility checks yielded a maximum standard deviation of 0.05 kcal/mol for conformationally restricted ligands, while macrocyclic candidates showed greater protocol-dependent variability. Rule-based triage integrating upstream evidence, ADMET burden, chemotype diversity and mechanistic coverage returned five candidates: betamethasone, bafilomycin A1, everolimus, pitavastatin and CHEMBL1410015.</p>Discussion<p>The workflow links a proteomic host-factor signal to a compact set of chemically diverse hypotheses with explicit evidence sources and limitations. The candidates remain hypotheses for experimental assessment; direct target engagement, interface blockade and antiviral activity are not established by the present study.</p> 2026-09-29T04:40:08Z Dataset Dataset 10.3389/fphar.2026.1910440.s003 https://figshare.com/articles/dataset/Data_Sheet_5_Knowledge_graph_and_machine_learning-guided_virtual_screening_prioritizes_putative_blockers_of_the_PSMD11_Rpn6-EBOV_glycoprotein_interface_csv/34021254 CC BY 4.0