对小分子硼制剂进行硅学评估,为基于人工智能的硼中子俘获疗法铺平道路。

IF 6 2区 医学 Q1 CHEMISTRY, MEDICINAL
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引用次数: 0

摘要

硼中子俘获疗法(BNCT)是一种具有高度针对性、选择性和有效性的技术,用于治疗各种癌症,对健康细胞的伤害较小。从原理上讲,硼中子俘获疗法需要将 10B 原子选择性地均匀分布在肿瘤组织内,并通过俘获足够的中子引发核裂变反应,从而释放出高线能粒子杀死肿瘤细胞。在 BNCT 中,关键是要有高质量的硼制剂,具有可接受的生物选择性、均匀分布和所需数量,类似于化疗和其他治疗肿瘤的放射疗法。然而,目前用于临床试验的硼药物尚未完全满足要求。另一方面,由于高质量中子源的先进发展和全球新的 BNCT 中心的建设,BNCT 处理开启了复兴时代。因此,迫切需要使用生物能力更强的硼剂。分子对接和分子动态模拟技术等人工智能(AI)工具已被用于开发新药物。在这项工作中,采用了包括 BNCT 相关肿瘤受体蛋白的生物信息学评估、硼制剂优化小分子的计算评估在内的硅学评估,以加快硼药物的筛选过程。这些成果将为未来利用人工智能的 BNCT 铺平道路。我们将研究优化的小分子硼制剂(如 4-硼基-l-苯丙氨酸(BPA))与优化蛋白质(如 L 型氨基酸转运体 1(LTA1,又称 SLC7A5))的分子对接和动态模拟结果。硅学评估结果必将有助于研究人员优化可用于 BNCT 的药物硼制剂。利用生物信息学技术对优化蛋白质的临床状态进行了评估和相应的讨论,这些蛋白质与可能用 BNCT 治疗的癌症高度相关。此外,还对优化配体 1 和 7 的细胞毒性(IC50)、硼吸收和组织分布进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

In silico assessments of the small molecular boron agents to pave the way for artificial intelligence-based boron neutron capture therapy

In silico assessments of the small molecular boron agents to pave the way for artificial intelligence-based boron neutron capture therapy

Boron neutron capture therapy (BNCT) is a highly targeted, selective and effective technique to cure various types of cancers, with less harm to the healthy cells. In principle, BNCT treatment needs to distribute the 10boron (10B) atoms inside the tumor tissues, selectively and homogeneously, as well as to initiate a nuclear fission reaction by capturing sufficient neutrons which releases high linear energy particles to kill the tumor cells. In BNCT, it is crucial to have high quality boron agents with acceptable bio-selectivity, homogeneous distribution and deliver in required quantity, similar to chemotherapy and other radiotherapy for tumor treatment. Nevertheless, boron drugs currently used in clinical trials yet to meet the full requirements. On the other hand, BNCT processing has opened up the era of renaissance due to the advanced development of the high-quality neutron source and the global construction of new BNCT centers. Consequently, there is an urgent need to use boron agents that have increased biocapacity. Artificial intelligence (AI) tools such as molecular docking and molecular dynamic simulation technologies have been utilized to develop new medicines. In this work, the in silico assessments including bioinformatics assessments of BNCT related tumoral receptor proteins, computational assessments of optimized small molecules of boron agents, are employed to speed up the screening process for boron drugs. The outcomes will be applicable to pave the way for future BNCT that utilizes artificial intelligence. The in silico molecular docking and dynamic simulation results of the optimized small boron agents, such as 4-borono-l-phenylalanine (BPA) with optimized proteins like the L-type amino acid transporter 1 (LTA1, also known as SLC7A5) will be examined. The in silico assessments results will certainly be helpful to researchers in optimizing druggable boron agents for the BNCT application. The clinical status of the optimized proteins, which are highly relevant to cancers that may be treated with BNCT, has been assessed using bioinformatics technology and discussed accordingly. Furthermore, the evaluations of cytotoxicity (IC50), boron uptake and tissue distribution of the optimized ligands 1 and 7 have been presented.

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来源期刊
CiteScore
11.70
自引率
9.00%
发文量
863
审稿时长
29 days
期刊介绍: The European Journal of Medicinal Chemistry is a global journal that publishes studies on all aspects of medicinal chemistry. It provides a medium for publication of original papers and also welcomes critical review papers. A typical paper would report on the organic synthesis, characterization and pharmacological evaluation of compounds. Other topics of interest are drug design, QSAR, molecular modeling, drug-receptor interactions, molecular aspects of drug metabolism, prodrug synthesis and drug targeting. The journal expects manuscripts to present the rational for a study, provide insight into the design of compounds or understanding of mechanism, or clarify the targets.
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