通过分子对接和 3D-QSAR 方法从磷脂酰肌醇 3- 激酶-α 抑制剂中合理设计药物,用于癌症免疫疗法

Kevin Tochukwu Dibia, Sandra Nneka Van-Dibia, Philomena Kanwulia Igbokwe
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引用次数: 0

摘要

磷脂酰肌醇 3- 激酶(PI3K)信号通路失调或异常激活常见于各种癌症,与肿瘤生长、转移和抗药性有关。使用适当的抑制剂靶向 PI3K-α 可以破坏这一通路,阻碍癌症进展,并有可能增强免疫系统识别和消灭癌细胞的能力。在这项研究中,我们旨在利用合理药物设计技术,包括虚拟筛选、分子对接和三维-QSAR,设计出一种新型、强效的 PI3K-α 抑制剂,用于癌症免疫疗法。我们从 RCSB 蛋白质数据库中获得了与 (3S)-3-benzyl-3-methyl-5-[5-(2-methylpyrimidin-5-yl)pyrazolo[1,5-a]pyrimidin-3-yl]-1,3-dihydro-2H-indol-2-one (PJ5) 复合物的人类 PI3K-α 蛋白 (6PYS)。利用适当的 Schrödinger Maestro 模块,结合预测性计算分子对接和基于三维场的 QSAR,对配体进行了虚拟筛选。此外,还进行了合理的药物设计,并通过多个 ADMET 描述因子验证了其临床相关性。对接结果表明,磺酰胺类和吡啶类杂环化合物的混合物,在功能上具有来自生物碱的有效分子,表现出充分的协同生物效应,能够增强对 PI3K-α 的足够生物活性。在四个偏最小二乘法因子的基础上建立了基于场的三维-QSAR模型,并采用五个统计指标对模型进行了验证。该方法新设计的配体名为 6'-氨基-5'-(2-氟-1,3-恶唑-5-基)-N-{[3-(羟甲基)氧杂环丁烷-3-基]甲基}-3-甲基-[2,3'-联吡啶]-6-磺酰胺或 T85,其预测生物活性(pIC50)为 8.25。T85 的 ADMET 特性预测值在推荐标准的合理范围内,尤其符合利宾斯基的五原则和乔根森的三原则。总之,本研究的结果为采用合理方法进行硅学药物设计提供了重要启示,可加快新药物分子的发现和开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rational drug design from phosphatidylinositol 3-kinase-α inhibitors through molecular docking and 3D-QSAR methodologies for cancer immunotherapy
Dysregulation or aberrant activation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway is commonly observed in various cancers and is associated with tumor growth, metastasis, and resistance to therapy. Targeting PI3K-α with appropriate inhibitors can disrupt this pathway, hindering cancer progression, and potentially enhancing the immune system’s ability to recognize and eliminate cancer cells. In this study, we aimed to design a novel and potent inhibitor of PI3K-α for cancer immunotherapy using rational drug design techniques, including virtual screening, molecular docking, and 3D-QSAR. We obtained the human PI3K-α protein (6PYS) complexed with (3S)-3-benzyl-3-methyl-5-[5-(2-methylpyrimidin-5-yl)pyrazolo[1,5-a]pyrimidin-3-yl]-1,3-dihydro-2H-indol-2-one (PJ5) from the RCSB Protein Data Bank. Virtual screening of ligands, integrated with predictive computational molecular docking and 3D-field-based-QSAR, was implemented using appropriate Schrödinger Maestro modules. Rational drug design was also carried out, and its clinical relevance was validated across several ADMET descriptors. Docking results suggested that a hybrid of sulfonamide and pyridine-based heterocyclic compounds, functionalized with potent moieties derived from alkaloids, exhibited adequate synergistic biological effects capable of enhancing sufficient biological activity against PI3K-α. A field-based 3D-QSAR model was built on four partial least squares factors, and five statistical metrics were employed to validate the model. The newly designed ligand from this approach, named 6’-amino-5’-(2-fluoro-1,3-oxazol-5-yl)-N-{[3-(hydroxymethyl)oxetan-3-yl]methyl}-3-methyl-[2,3’-bipyridine]-6-sulfonamide or T85, exhibited a predicted bioactivity (pIC50) of 8.25. The predicted ADMET properties of T85 fell reasonably within the range of recommended standards, especially adhering to Lipinski’s rule of five and Jorgensen’s rule of three. In conclusion, the results of this study offer significant insights into in silico drug design using a rational approach, which could expedite the discovery and development of new drug molecules.
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