{"doi":"10.1021/acs.jcim.1c01414","title":"Virtual Screening for the Discovery of Microbiome β-Glucuronidase Inhibitors to Alleviate Cancer Drug Toxicity","abstract":"Despite the potency of most first-line anti-cancer drugs, nonadherence to these drug regimens remains high and is attributable to the prevalence of “off-target” drug effects that result in serious adverse events (SAEs) like hair loss, nausea, vomiting, and diarrhea. Some anti-cancer drugs are converted by liver uridine 5′-diphospho-glucuronosyltransferases through homeostatic host metabolism to form drug-glucuronide conjugates. These sugar-conjugated metabolites are generally inactive and can be safely excreted via the biliary system into the gastrointestinal tract. However, β-glucuronidase (βGUS) enzymes expressed by commensal gut bacteria can remove the glucuronic acid moiety, producing the reactivated drug and triggering dose-limiting side effects. Small-molecule βGUS inhibitors may reduce this drug-induced gut toxicity, allowing patients to complete their full course of treatment. Herein, we report the discovery of novel chemical series of βGUS inhibitors by structure-based virtual high-throughput screening (vHTS). We developed homology models for βGUS and applied them to large-scale vHTS against nearly 400,000 compounds within the chemical libraries of the National Center for Advancing Translational Sciences at the National Institutes of Health. From the vHTS results, we cherry-picked 291 compounds via a multifactor prioritization procedure, providing 69 diverse compounds that exhibited positive inhibitory activity in a follow-up βGUS biochemical assay in vitro. Our findings correspond to a hit rate of 24% and could inform the successful downstream development of a therapeutic adjunct that targets the human microbiome to prevent SAEs associated with first-line, standard-of-care anti-cancer drugs.","journal":"Journal of Chemical Information and Modeling","year":2022,"id":263006,"datarank":0.40620753016533157,"base_score":2.70805020110221,"endowment":2.70805020110221,"self_citation_contribution":0.40620753016533157,"citation_network_contribution":0.0,"self_endowment_contribution":0.40620753016533157,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9578,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":267852,"name":"Xin Hu","orcid":"0000-0003-1164-5130","position":1,"is_corresponding":false},{"id":509642,"name":"Yaqin Zhang","orcid":"0000-0003-3436-4569","position":2,"is_corresponding":false},{"id":919416,"name":"Jeffrey L. Hymes","orcid":"0000-0001-5540-131X","position":3,"is_corresponding":false},{"id":245442,"name":"Bret D. Wallace","orcid":"0000-0002-9107-5045","position":4,"is_corresponding":false},{"id":700096,"name":"Karavadhi Surendra","orcid":null,"position":5,"is_corresponding":false},{"id":332246,"name":"Hongmao Sun","orcid":"0000-0003-4042-6498","position":6,"is_corresponding":false},{"id":353889,"name":"Samarjit Patnaik","orcid":"0000-0002-4265-7620","position":7,"is_corresponding":false},{"id":255126,"name":"Matthew D. Hall","orcid":"0000-0002-5073-442X","position":8,"is_corresponding":false},{"id":239789,"name":"Min Shen","orcid":"0000-0002-8218-0433","position":9,"is_corresponding":false},{"id":676633,"name":"Anup P. Challa","orcid":"0000-0002-8886-7308","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:26:29.321923Z","pmid":"35357819","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}