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靶向甲状腺癌细胞内向整流钾通道 5.1:人工智能辅助的药物发现分子对接。

Targeting the inward rectifier potassium channel 5.1 in thyroid cancer: artificial intelligence-facilitated molecular docking for drug discovery.

机构信息

Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.

Laboratory of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.

出版信息

BMC Endocr Disord. 2023 May 19;23(1):113. doi: 10.1186/s12902-023-01360-z.

DOI:10.1186/s12902-023-01360-z
PMID:37208644
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10197823/
Abstract

BACKGROUND

Recurrent and metastatic thyroid cancer is more invasive and can transform to dedifferentiated thyroid cancer, thus leading to a severe decline in the 10-year survival. The thyroid-stimulating hormone receptor (TSHR) plays an important role in differentiation process. We aim to find a therapeutic target in redifferentiation strategies for thyroid cancer.

METHODS

Our study integrated the differentially expressed genes acquired from the Gene Expression Omnibus database by comparing TSHR expression levels in the Cancer Genome Atlas database. We conducted functional enrichment analysis and verified the expression of these genes by RT-PCR in 68 pairs of thyroid tumor and paratumor tissues. Artificial intelligence-enabled virtual screening was combined with the VirtualFlow platform for deep docking.

RESULTS

We identified five genes (KCNJ16, SLC26A4, TG, TPO, and SYT1) as potential cancer treatment targets. TSHR and KCNJ16 were downregulated in the thyroid tumor tissues, compared with paired normal tissues. In addition, KCNJ16 was lower in the vascular/capsular invasion group. Enrichment analyses revealed that KCNJ16 may play a significant role in cell growth and differentiation. The inward rectifier potassium channel 5.1 (Kir5.1, encoded by KCNJ16) emerged as an interesting target in thyroid cancer. Artificial intelligence-facilitated molecular docking identified Z2087256678_2, Z2211139111_1, Z2211139111_2, and PV-000592319198_1 (-7.3 kcal/mol) as the most potent commercially available molecular targeting Kir5.1.

CONCLUSION

This study may provide greater insights into the differentiation features associated with TSHR expression in thyroid cancer, and Kir5.1 may be a potential therapeutic target in the redifferentiation strategies for recurrent and metastatic thyroid cancer.

摘要

背景

复发性和转移性甲状腺癌更具侵袭性,并可能向去分化甲状腺癌转化,从而导致 10 年生存率严重下降。促甲状腺激素受体(TSHR)在分化过程中发挥重要作用。我们旨在为甲状腺癌的再分化策略寻找治疗靶点。

方法

我们的研究通过比较癌症基因组图谱数据库中 TSHR 的表达水平,整合了从基因表达综合数据库中获得的差异表达基因。我们进行了功能富集分析,并通过 68 对甲状腺肿瘤和肿瘤旁组织的 RT-PCR 验证了这些基因的表达。人工智能辅助的虚拟筛选与 VirtualFlow 平台相结合进行深度对接。

结果

我们确定了五个潜在的癌症治疗靶点基因(KCNJ16、SLC26A4、TG、TPO 和 SYT1)。与配对的正常组织相比,甲状腺肿瘤组织中 TSHR 和 KCNJ16 下调。此外,KCNJ16 在血管/包膜浸润组中较低。富集分析表明,KCNJ16 可能在细胞生长和分化中发挥重要作用。内向整流钾通道 5.1(由 KCNJ16 编码)成为甲状腺癌的一个有趣靶点。人工智能辅助的分子对接确定了 Z2087256678_2、Z2211139111_1、Z2211139111_2 和 PV-000592319198_1(-7.3 kcal/mol)为最有效的商业上可用的靶向 Kir5.1 分子。

结论

本研究可能为甲状腺癌中与 TSHR 表达相关的分化特征提供更深入的了解,Kir5.1 可能是复发性和转移性甲状腺癌再分化策略的潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/1eaaf9cdcb7c/12902_2023_1360_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/68502f259344/12902_2023_1360_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/23ab570c9f92/12902_2023_1360_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/a57bf2296398/12902_2023_1360_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/25c2b67a1e7c/12902_2023_1360_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/583ec4d2fbda/12902_2023_1360_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/1eaaf9cdcb7c/12902_2023_1360_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/68502f259344/12902_2023_1360_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/23ab570c9f92/12902_2023_1360_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/a57bf2296398/12902_2023_1360_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/25c2b67a1e7c/12902_2023_1360_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/583ec4d2fbda/12902_2023_1360_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f12/10197823/1eaaf9cdcb7c/12902_2023_1360_Fig6_HTML.jpg

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