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RPS6KB1相关癌症抑制剂的计算机模拟研究:一项药物再利用研究。

In-silico investigation of RPS6KB1 associated cancer inhibitor: a drug repurposing study.

作者信息

Rajendrasozhan Saravanan, Ahmad Irfan, Obaidur Rab Safia, Alshahrani Mohammad Y, Abdullah Almuqri Eman, Ahmad Siddiqui Jamshaid, Mushtaque Md

机构信息

Department of Chemistry, College of Science, University of Ha'il, Ha'il, Saudi Arabia.

Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.

出版信息

J Biomol Struct Dyn. 2025 Jun;43(9):4678-4685. doi: 10.1080/07391102.2024.2304679. Epub 2024 Jan 19.

DOI:10.1080/07391102.2024.2304679
PMID:38240100
Abstract

The ribosomal protein S6 kinase beta-1 (RPS6KB1), also known as p70S6 kinase, plays a crucial role in various disease-related conditions such as diabetes, obesity, and cancer. Its activity is regulated by phosphorylation events, including phosphorylation of Threonine 389 in the hydrophobic motif by the mammalian target of rapamycin complex 1 (mTORC1) and phosphorylation of Threonine 229 in the activation loop by PDK1 (phosphoinositide-dependent kinase 1). However, other phenomena connected to RPS6KB1 remain unknown. In this study, we employed virtual screening and molecular docking techniques on the molecules in the ZINC library to identify potential inhibitors. Molecular dynamics (MD) simulations and MMGBSA calculations were carried out on promising compounds to determine their binding affinity and stability. We also evaluated the drug-likeness properties of the selected compounds. A comparative study between the native RPS6KB1 structure, co-crystal ligands, and the shortlisted molecules from the ZINC dataset was carried out. The identified molecules possess significant potential for future and studies, paving the way for developing effective cancer treatments.

摘要

核糖体蛋白S6激酶β-1(RPS6KB1),也被称为p70S6激酶,在糖尿病、肥胖症和癌症等各种与疾病相关的状况中发挥着关键作用。其活性受磷酸化事件调控,包括雷帕霉素复合物1(mTORC1)对疏水基序中苏氨酸389的磷酸化以及磷酸肌醇依赖性激酶1(PDK1)对激活环中苏氨酸229的磷酸化。然而,与RPS6KB1相关的其他现象仍不为人知。在本研究中,我们对ZINC库中的分子采用虚拟筛选和分子对接技术来识别潜在抑制剂。对有前景的化合物进行了分子动力学(MD)模拟和MMGBSA计算,以确定它们的结合亲和力和稳定性。我们还评估了所选化合物的类药性质。对天然RPS6KB1结构、共晶配体以及来自ZINC数据集的入围分子进行了比较研究。所鉴定的分子在未来研究中具有巨大潜力,为开发有效的癌症治疗方法铺平了道路。

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