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使用天然化合物使卡培他滨治疗中脱靶毒性最小化的计算框架。

Computational framework for minimizing off-target toxicity in capecitabine treatment using natural compounds.

作者信息

Jamal Tanya, Ali Anamta, Chauhan Shweta Singh, Singh Rinni, Parthasarathi Ramakrishnan

机构信息

REACT - Computational Toxicology Group, CSIR- Indian Institute of Toxicology Research, Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, Uttar Pradesh, 226001, India.

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India.

出版信息

Mol Divers. 2025 Feb 26. doi: 10.1007/s11030-025-11139-0.

Abstract

Antineoplastic drugs are becoming prevalent due to increasing cancer casualties around the globe. However, the adverse effects of these drugs are evident due to limited insight into the underlying mechanisms that result in non-specific binding and consequent off-target toxicity. The study investigates the side effects of an antineoplastic drug, Capecitabine, a prodrug converted into fluorouracil by Thymidine Phosphorylase (TP) and degrades the RNA of cancerous cells. However, its non-specific binding with Dihydropyrimidine dehydrogenase (DPD) leads to severe toxicities including leukoencephalopathy, neutropenia, neuropathy, and others. Hence, identifying natural analogs of Capecitabine with comparable attributes is crucial for minimizing its adverse effects. A thorough review of the literature revealed Capecitabine-induced toxicity. 723,878 natural compounds were screened, and drug-like mimics were identified. Their binding with TP and DPD was determined by employing molecular docking, which was validated by MD simulations evaluating conformational stability and variability. Four natural compounds showed better docking scores than the standard drug. The stability of the best hit was further validated with MD simulations. This study, hence, ushers in new perspectives on safer drug alternatives using potent natural analogs and could serve as a lead identification approach for the discovery of safer therapeutics.

摘要

由于全球癌症患者伤亡人数不断增加,抗肿瘤药物正变得越来越普遍。然而,由于对导致非特异性结合及随之而来的脱靶毒性的潜在机制了解有限,这些药物的不良反应很明显。该研究调查了一种抗肿瘤药物卡培他滨的副作用,卡培他滨是一种前体药物,通过胸苷磷酸化酶(TP)转化为氟尿嘧啶,可降解癌细胞的RNA。然而,它与二氢嘧啶脱氢酶(DPD)的非特异性结合会导致严重毒性,包括白质脑病、中性粒细胞减少、神经病变等。因此,识别具有类似特性的卡培他滨天然类似物对于将其不良反应降至最低至关重要。对文献的全面回顾揭示了卡培他滨诱导的毒性。筛选了723,878种天然化合物,并鉴定出类药物模拟物。通过分子对接确定它们与TP和DPD的结合,并通过评估构象稳定性和变异性的分子动力学模拟进行验证。四种天然化合物的对接分数优于标准药物。通过分子动力学模拟进一步验证了最佳命中物的稳定性。因此,这项研究为使用有效的天然类似物寻找更安全的药物替代品带来了新的视角,并可作为发现更安全治疗方法的先导物鉴定方法。

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