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.

中文翻译：

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对小分子硼剂进行计算机评估，为基于人工智能的硼中子俘获疗法铺平道路


硼中子俘获疗法 （BNCT） 是一种高度靶向、选择性和有效的技术，可治愈各种类型的癌症，对健康细胞的伤害较小。原则上，BNCT 治疗需要选择性地、均匀地将 10 个硼 （10B） 原子分布在肿瘤组织内，并通过捕获足够的中子来引发核裂变反应，释放出高线性能粒子来杀死肿瘤细胞。在 BNCT 中，拥有具有可接受生物选择性、均匀分布并以所需数量交付的高质量硼剂至关重要，类似于化疗和其他用于肿瘤治疗的放疗。尽管如此，目前临床试验中使用的硼药物尚未满足全部要求。另一方面，由于高质量中子源的先进发展和新 BNCT 中心的全球建设，BNCT 加工开启了复兴时代。因此，迫切需要使用具有更高生物承载力的硼剂。分子对接和分子动力学模拟技术等人工智能 （AI） 工具已被用于开发新药。在这项工作中，计算机评估包括 BNCT 相关肿瘤受体蛋白的生物信息学评估、优化小分子硼剂的计算评估，以加快硼药物的筛选过程。结果将适用于为未来利用人工智能的 BNCT 铺平道路。将检查优化的小硼剂（如 4-硼-l-苯丙氨酸 （BPA））和优化蛋白质（如 L 型氨基酸转运蛋白 1（LTA1，也称为 SLC7A5））的计算机分子对接和动态模拟结果。 计算机评估结果肯定会帮助研究人员优化 BNCT 应用的可成药硼剂。优化蛋白质的临床状态与可能用 BNCT 治疗的癌症高度相关，已使用生物信息学技术进行了评估并进行了相应的讨论。此外，还介绍了优化配体 1 和 7 的细胞毒性 （IC50）、硼摄取和组织分布的评估。