Virtual Screening for the Discovery of Microbiome β-Glucuronidase Inhibitors to Alleviate Cancer Drug Toxicity

药理学 药品 药物发现 药物代谢 不利影响 医学 生物 生物信息学
作者
Anup P. Challa,Xin Hu,Yaqin Zhang,Jeffrey Hymes,Bret D. Wallace,Karavadhi Surendra,Hongmao Sun,Samarjit Patnaik,Matthew D. Hall,Min Shen
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:62 (7): 1783-1793 被引量:3
标识
DOI:10.1021/acs.jcim.1c01414
摘要

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.
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