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结合实验验证的偏置力引导模拟用于识别GPR17调节剂

Bias-force guided simulations combined with experimental validations towards GPR17 modulators identification.

作者信息

Kari Sana, Murugesan Akshaya, Thiyagarajan Ramesh, Kidambi Srivatsan, Razzokov Jamoliddin, Selvaraj Chandrabose, Kandhavelu Meenakshisundaram, Marimuthu Parthiban

机构信息

Molecular Signaling Group, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O.Box 553, 33101 Tampere, Finland.

Department of Basic Medical Sciences, College of Medicine, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Kingdom of Saudi Arabia.

出版信息

Biomed Pharmacother. 2023 Apr;160:114320. doi: 10.1016/j.biopha.2023.114320. Epub 2023 Jan 28.

Abstract

Glioblastoma Multiforme (GBM) is known to be by far the most aggressive brain tumor to affect adults. The median survival rate of GBM patient's is < 15 months, while the GBM cells aggressively develop resistance to chemo- and radiotherapy with their self-renewal capacity which suggests the pressing need to develop novel preventative measures. We have recently proved that GPR17 -an orphan G protein-coupled receptor- is highly expressed on the GBM cell surface and it has a vital role to play in the disease progression. Despite the progress made on GBM downregulation, there still remain difficulties in developing a promising modulator for GPR17, till date. Here, we have performed robust virtual screening combined with biased-force pulling molecular dynamic (MD) simulations to predict high-affinity GPR17 modulators followed by experimental validation. Initially, the database containing 1379 FDA-approved drugs were screened against the orthosteric binding pocket of the GPR17. The external bias-potentials were then applied to the screened hits during the MD simulations which enabled to predict a spectrum of rupture peak force values that were used to select four approved drugs -ZINC000003792417 (Sacubitril), ZINC000014210457 (Victrelis), ZINC000001536109 (Pralatrexate) and ZINC000003925861 (Vorapaxar)- as top hits. The hits selected turns out to demonstrate unique dissociation pathways, interaction pattern, and change in polar network over time. Subsequently the selected hits with GPR17 were measured by inhibiting the forskolin-stimulated cAMP accumulation in GBM cell lines, LN229 and SNB19. The ex vivo validations shows that Sacubitril drug can act as a full agonist, while Vorapaxar functions as a partial agonist for GPR17. The pEC of Sacubitril was identified as 4.841 and 4.661 for LN229 and SNB19, respectively. Small interference of the RNA (siRNA)- silenced the GPR17 to further validate the targeted binding of Sacubitril with GPR17. In the current investigation, we have identified new repurposable GPR17 specific drugs which are likely to increase the opportunity to treat orphan deadly diseases.

摘要

多形性胶质母细胞瘤(GBM)是目前已知影响成年人的最具侵袭性的脑肿瘤。GBM患者的中位生存期小于15个月,而GBM细胞凭借其自我更新能力对化疗和放疗产生强烈的耐药性,这表明迫切需要开发新的预防措施。我们最近证明,GPR17(一种孤儿G蛋白偶联受体)在GBM细胞表面高度表达,并且在疾病进展中起着至关重要的作用。尽管在GBM下调方面取得了进展,但迄今为止,开发一种有前景的GPR17调节剂仍然存在困难。在这里,我们进行了强大的虚拟筛选,并结合有偏力拉动分子动力学(MD)模拟来预测高亲和力的GPR17调节剂,随后进行实验验证。最初,针对GPR17的正构结合口袋筛选了包含1379种FDA批准药物的数据库。然后在MD模拟过程中对筛选出的命中物施加外部偏置电位,这使得能够预测一系列破裂峰值力值,用于选择四种批准药物——ZINC000003792417(沙库巴曲)、ZINC000014210457(特拉匹韦)、ZINC000001536109(普拉曲沙)和ZINC000003925861(vorapaxar)——作为顶级命中物。所选的命中物显示出独特的解离途径、相互作用模式以及极性网络随时间的变化。随后,通过抑制GBM细胞系LN229和SNB19中福斯高林刺激的cAMP积累来测量所选命中物与GPR17的结合情况。体外验证表明,沙库巴曲药物可作为完全激动剂,而vorapaxar作为GPR17的部分激动剂。沙库巴曲在LN229和SNB19中的pEC分别确定为4.841和4.661。RNA小干扰(siRNA)使GPR17沉默,以进一步验证沙库巴曲与GPR17的靶向结合。在当前的研究中,我们确定了新的可重新利用的GPR17特异性药物,这可能会增加治疗罕见致命疾病的机会。

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