Department of Pharmacy, Faculty of Science (E.J.Y.C., R.W.Y.N., H.T.T., C.L.L.C., E.C.Y.C.) and Department of Biological Sciences (H.F.), National University of Singapore, Singapore, Singapore; Department of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, College of Medicine and Public Health, Flinders University, Adelaide, Australia (P.C.N., J.O.M.); Bioinformatics Institute, Biotransformation Innovation Platform (BioTrans) (F.L.) and Bioinformatics Institute (H.F.), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore; Department of Surgery, National University Health System, Singapore, Singapore (E.C., K.E.); Department of Urology, National University Hospital, Singapore, Singapore (E.C., K.E.); Centre for Computational Biology, DUKE-NUS Medical School, Singapore, Singapore (H.F.); The University of Chicago, Chicago, Illinois (R.Z.S.); National Cancer Institute, Rockville, Maryland (C.J.P., W.D.F.); and National University Cancer Institute, Singapore (NCIS), NUH Medical Centre (NUHMC), Singapore, Singapore (E.C.Y.C.).
Department of Pharmacy, Faculty of Science (E.J.Y.C., R.W.Y.N., H.T.T., C.L.L.C., E.C.Y.C.) and Department of Biological Sciences (H.F.), National University of Singapore, Singapore, Singapore; Department of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, College of Medicine and Public Health, Flinders University, Adelaide, Australia (P.C.N., J.O.M.); Bioinformatics Institute, Biotransformation Innovation Platform (BioTrans) (F.L.) and Bioinformatics Institute (H.F.), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore; Department of Surgery, National University Health System, Singapore, Singapore (E.C., K.E.); Department of Urology, National University Hospital, Singapore, Singapore (E.C., K.E.); Centre for Computational Biology, DUKE-NUS Medical School, Singapore, Singapore (H.F.); The University of Chicago, Chicago, Illinois (R.Z.S.); National Cancer Institute, Rockville, Maryland (C.J.P., W.D.F.); and National University Cancer Institute, Singapore (NCIS), NUH Medical Centre (NUHMC), Singapore, Singapore (E.C.Y.C.)
J Pharmacol Exp Ther. 2020 Sep;374(3):438-451. doi: 10.1124/jpet.120.265868. Epub 2020 Jun 17.
Substantial evidence underscores the clinical efficacy of inhibiting CYP17A1-mediated androgen biosynthesis by abiraterone for treatment of prostate oncology. Previous structural analysis and in vitro assays revealed inconsistencies surrounding the nature and potency of CYP17A1 inhibition by abiraterone. Here, we establish that abiraterone is a slow-, tight-binding inhibitor of CYP17A1, with initial weak binding preceding the subsequent slow isomerization to a high-affinity CYP17A1-abiraterone complex. The in vitro inhibition constant of the final high-affinity CYP17A1-abiraterone complex ( )yielded a binding free energy of -12.8 kcal/mol that was quantitatively consistent with the in silico prediction of -14.5 kcal/mol. Prolonged suppression of dehydroepiandrosterone (DHEA) concentrations observed in VCaP cells after abiraterone washout corroborated its protracted CYP17A1 engagement. Molecular dynamics simulations illuminated potential structural determinants underlying the rapid reversible binding characterizing the two-step induced-fit model. Given the extended residence time (42 hours) of abiraterone within the CYP17A1 active site, in silico simulations demonstrated sustained target engagement even when most abiraterone has been eliminated systemically. Subsequent pharmacokinetic-pharmacodynamic (PK-PD) modeling linking time-dependent CYP17A1 occupancy to in vitro steroidogenic dynamics predicted comparable suppression of downstream DHEA-sulfate at both 1000- and 500-mg doses of abiraterone acetate. This enabled mechanistic rationalization of a clinically reported PK-PD disconnect, in which equipotent reduction of downstream plasma DHEA-sulfate levels was achieved despite a lower systemic exposure of abiraterone. Our novel findings provide the impetus for re-evaluating the current dosing paradigm of abiraterone with the aim of preserving PD efficacy while mitigating its dose-dependent adverse effects and financial burden. SIGNIFICANCE STATEMENT: With the advent of novel molecularly targeted anticancer modalities, it is becoming increasingly evident that optimal dose selection must necessarily be predicated on mechanistic characterization of the relationships between target exposure, drug-target interactions, and pharmacodynamic endpoints. Nevertheless, efficacy has always been perceived as being exclusively synonymous with affinity-based measurements of drug-target binding. This work demonstrates how elucidating the slow-, tight-binding inhibition of CYP17A1 by abiraterone via in vitro and in silico analyses was pivotal in establishing the role of kinetic selectivity in mediating time-dependent CYP17A1 engagement and eventually downstream efficacy outcomes.
大量证据强调了通过阿比特龙抑制 CYP17A1 介导的雄激素生物合成治疗前列腺肿瘤的临床疗效。先前的结构分析和体外测定显示，阿比特龙对 CYP17A1 抑制的性质和效力存在不一致之处。在这里，我们确定阿比特龙是 CYP17A1 的缓慢、紧密结合抑制剂，最初的弱结合在前随后的缓慢异构化到高亲和力 CYP17A1-阿比特龙复合物之前。最终高亲和力 CYP17A1-阿比特龙复合物的体外抑制常数（）产生了-12.8 kcal/mol 的结合自由能，这与-14.5 kcal/mol 的计算预测定量一致。阿比特龙冲洗后在 VCaP 细胞中观察到脱氢表雄酮（DHEA）浓度的延长抑制，证实了其对 CYP17A1 的持续结合。分子动力学模拟阐明了潜在的结构决定因素，这些因素是描述两步诱导拟合模型的快速可逆结合的基础。鉴于阿比特龙在 CYP17A1 活性部位的停留时间（42 小时）延长，计算模拟表明，即使系统中大多数阿比特龙已经消除，仍能持续靶标结合。随后将时变 CYP17A1 占有率与体外类固醇生成动力学相关联的药代动力学-药效学（PK-PD）建模预测，在阿比特龙醋酸盐 1000mg 和 500mg 剂量下，下游 DHEA-硫酸盐的抑制作用相当。这使得对临床报告的 PK-PD 不匹配现象进行了机制合理化，尽管阿比特龙的全身暴露较低，但下游血浆 DHEA-硫酸盐水平的等效降低仍然实现了。我们的新发现为重新评估阿比特龙的当前给药方案提供了动力，目的是在减轻其剂量依赖性不良反应和经济负担的同时保留 PD 疗效。意义：随着新型分子靶向抗癌方式的出现，越来越明显的是，最佳剂量选择必须基于对靶标暴露、药物-靶标相互作用和药效终点之间关系的机制特征的描述。然而，疗效一直被认为完全等同于基于药物-靶标结合的亲和力测量。这项工作表明，通过体外和计算分析阐明阿比特龙对 CYP17A1 的缓慢、紧密结合抑制作用，对于确定动力学选择性在介导时变 CYP17A1 结合和最终下游疗效结果中的作用至关重要。
