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P-糖蛋白抑制剂的计算加速鉴定

Computationally accelerated identification of P-glycoprotein inhibitors.

作者信息

McCormick Lauren A, McCormick James W, Park Chanyang, Follit Courtney A, Wise John G, Vogel Pia D

机构信息

Department of Biological Sciences, Southern Methodist University, Dallas, Texas, United States of America.

Center for Drug Discovery, Design and Delivery, Southern Methodist University, Dallas, Texas, United States of America.

出版信息

PLoS One. 2025 Aug 13;20(8):e0325121. doi: 10.1371/journal.pone.0325121. eCollection 2025.

Abstract

Overexpression of the polyspecific efflux transporter, P-glycoprotein (P-gp, MDR1, ABCB1), is a major mechanism by which cancer cells acquire multidrug resistance (MDR), the resistance to diverse chemotherapeutic drugs. Inhibiting drug transport by P-gp can resensitize cancer cells to chemotherapy, but there are no P-gp inhibitors available to patients. Clinically unsuccessful P-gp inhibitors tend to bind at the pump's transmembrane drug binding domains and are often P-gp transport substrates, resulting in lowered intracellular concentration of the drug and altered pharmacokinetics. In prior work, we used computationally accelerated drug discovery to identify novel P-gp inhibitors that target the pump's cytoplasmic nucleotide binding domains. Our first-draft study provided conclusive evidence that the nucleotide binding domains of P-gp are viable targets for drug discovery. Here we develop an enhanced, computationally accelerated drug discovery pipeline that expands upon our prior work by iteratively screening compounds against multiple conformations of P-gp with molecular docking. Targeted molecular dynamics simulations with our homology model of human P-gp were used to generate docking receptors in conformations mimicking a putative drug transport cycle. We offset the increased computational complexity using custom Tanimoto chemical datasets, which maximize the chemical diversity of ligands screened by docking. Using our expanded, virtual-assisted pipeline, we identified nine novel P-gp inhibitors that reverse MDR in two types of P-gp overexpressing human cancer cell lines, reflecting a 13.4% hit rate. Of these inhibitors, all were non-toxic to non-cancerous human cells, and six were not likely to be transport substrates of P-gp. Our novel P-gp inhibitors are chemically diverse and are good candidates for lead optimization. Our results demonstrate that the nucleotide binding domains of P-gp are an underappreciated target in the effort to reverse P-gp-mediated multidrug resistance in cancer.

摘要

多特异性外排转运蛋白P-糖蛋白(P-gp,MDR1,ABCB1)的过表达是癌细胞获得多药耐药性(MDR)的主要机制,即对多种化疗药物产生耐药性。抑制P-糖蛋白的药物转运可使癌细胞对化疗重新敏感,但目前尚无可供患者使用的P-糖蛋白抑制剂。临床上未成功的P-糖蛋白抑制剂往往结合在转运蛋白的跨膜药物结合结构域,并且通常是P-糖蛋白转运底物,导致药物细胞内浓度降低和药代动力学改变。在先前的研究中,我们利用计算加速药物发现来鉴定靶向转运蛋白胞质核苷酸结合结构域的新型P-糖蛋白抑制剂。我们的初步研究提供了确凿的证据,表明P-糖蛋白的核苷酸结合结构域是药物发现的可行靶点。在此,我们开发了一种增强的、计算加速的药物发现流程,该流程在我们先前工作的基础上进行扩展,通过分子对接针对P-糖蛋白的多种构象迭代筛选化合物。使用我们的人P-糖蛋白同源模型进行靶向分子动力学模拟,以生成模拟假定药物转运循环构象的对接受体。我们使用定制的Tanimoto化学数据集抵消了增加的计算复杂性,该数据集最大限度地提高了通过对接筛选的配体的化学多样性。使用我们扩展的虚拟辅助流程,我们鉴定了九种新型P-糖蛋白抑制剂,它们可逆转两种P-糖蛋白过表达的人癌细胞系中的MDR,命中率为13.4%。在这些抑制剂中,所有抑制剂对非癌细胞均无毒,六种抑制剂不太可能是P-糖蛋白的转运底物。我们的新型P-糖蛋白抑制剂化学性质多样,是先导优化的良好候选物。我们的结果表明,在逆转癌症中P-糖蛋白介导的多药耐药性的努力中,P-糖蛋白的核苷酸结合结构域是一个未得到充分重视的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76a2/12349723/0bd0f9123545/pone.0325121.g001.jpg

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