<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>11(5)</volume><submitter>Li L</submitter><pubmed_abstract>Phosphorylation of serine residues within SQ/TQ motifs, particularly Ser237 of the ATP-dependent DNA helicase DDX11, by ataxia telangiectasia mutated (ATM) kinase plays a key role in activating the DNA damage response (DDR) in liver cancer. To disrupt this signaling pathway, we applied a computationally guided drug repurposing approach to identify FDA-approved compounds capable of targeting critical DDX11 residues. A library of 2367 drugs was screened using a structure-based, site-specific docking strategy, yielding seven candidates with binding affinities from -6.5 to -7.7 kcal/mol. Although Afatinib showed the strongest docking score (-7.674 kcal/mol), it lacked hydrogen-bond interactions with Ser237 and Gln238 and was therefore excluded. In contrast, dacomitinib, ergotamine, and cabozan</pubmed_abstract><journal>ACS omega</journal><pagination>7974-7987</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12902871</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Computational and Experimental Verification of Cabozantinib Targeting DDX11 to Inhibit DNA Damage Repair in Liver Cancer.</pubmed_title><pmcid>PMC12902871</pmcid><pubmed_authors>Liu Z</pubmed_authors><pubmed_authors>Liu L</pubmed_authors><pubmed_authors>Huang Z</pubmed_authors><pubmed_authors>Li D</pubmed_authors><pubmed_authors>Zhong J</pubmed_authors><pubmed_authors>Li L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Computational and Experimental Verification of Cabozantinib Targeting DDX11 to Inhibit DNA Damage Repair in Liver Cancer.</name><description>Phosphorylation of serine residues within SQ/TQ motifs, particularly Ser237 of the ATP-dependent DNA helicase DDX11, by ataxia telangiectasia mutated (ATM) kinase plays a key role in activating the DNA damage response (DDR) in liver cancer. To disrupt this signaling pathway, we applied a computationally guided drug repurposing approach to identify FDA-approved compounds capable of targeting critical DDX11 residues. A library of 2367 drugs was screened using a structure-based, site-specific docking strategy, yielding seven candidates with binding affinities from -6.5 to -7.7 kcal/mol. Although Afatinib showed the strongest docking score (-7.674 kcal/mol), it lacked hydrogen-bond interactions with Ser237 and Gln238 and was therefore excluded. In contrast, dacomitinib, ergotamine, and cabozan</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Feb</publication><modification>2026-07-15T18:05:48.888Z</modification><creation>2026-07-08T03:08:31.726Z</creation></dates><accession>S-EPMC12902871</accession><cross_references><pubmed>41696275</pubmed><doi>10.1021/acsomega.5c10093</doi></cross_references></HashMap>