Bhattacharjee Arnab, Kar Supratik, Ojha Probir Kumar
Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India.
Chemometrics and Molecular Modeling Laboratory, Department of Chemistry and Physics, Kean University, 1000 Morris Avenue, Union, NJ 07083, USA.
Comput Biol Chem. 2025 Apr;115:108347. doi: 10.1016/j.compbiolchem.2025.108347. Epub 2025 Jan 13.
Multiple myeloma (MM) is the second most frequently diagnosed hematological malignancy, presenting limited treatment options with no curative potential and significant drug resistance. Recent studies involving genetic knockdown established the crucial role of GRK6 in upholding the viability of MM cells, emphasizing the need to identify potential inhibitors. Computational exploration of GRK6 inhibitors has not been attempted previously. Herein, the present study reports a multilayered lead prioritization and optimization framework using chemometrics and molecular simulations. 2D QSAR studies revealed that hydrogen bonding and polar interactions enhanced GRK6 inhibitory activity, while increased electron accessibility posed a risk of off-target effects. The pharmacophore hypothesis (DDHRRR_1) featured two hydrogen bond donors, one hydrophobic region, and three aromatic rings, laying the foundation for the 3D QSAR models. Hydrophobic groups, such as pyridine and pyrazole, were shown to enhance inhibition, while smaller groups, like ethyl and hydroxyl, reduced activity. 12,557 DrugBank compounds were screened using the developed chemometric models and molecular docking in tandem, which led to the identification of 7 potential parent leads for subsequent QSAR-guided structural optimizations. 350 lead analogs were generated and the top 4 were further analyzed using molecular docking, ADMET, molecular dynamics, and metadynamics analysis based on Principal Component Analysis (PCA), Probability Density Function (PDF), and Free Energy Landscapes (FEL). Upon cumulative retrospection, we propose a novel analog of DB07168 (DB07168-A13) (docking score: -11.2 kcal/mol, MM-GBSA binding energy: -55.2 kcal/mol) as the most promising GRK6 inhibitor, warranting further in vitro validation, for addressing prospective therapeutic intervention in MM.
多发性骨髓瘤（MM）是第二常见的血液系统恶性肿瘤，治疗选择有限，没有治愈潜力且存在显著耐药性。最近涉及基因敲低的研究证实了GRK6在维持MM细胞活力方面的关键作用，凸显了识别潜在抑制剂的必要性。此前尚未尝试对GRK6抑制剂进行计算探索。在此，本研究报告了一个使用化学计量学和分子模拟的多层先导化合物优先级排序和优化框架。二维定量构效关系（QSAR）研究表明，氢键和极性相互作用增强了GRK6抑制活性，而电子可及性增加则带来了脱靶效应的风险。药效团假说（DDHRRR_1）具有两个氢键供体、一个疏水区域和三个芳香环，为三维QSAR模型奠定了基础。吡啶和吡唑等疏水基团显示可增强抑制作用，而乙基和羟基等较小基团则降低活性。使用开发的化学计量学模型和分子对接串联筛选了12557种药物银行化合物，从而确定了7种潜在的母体先导化合物，用于后续QSAR指导的结构优化。生成了350种先导类似物，并基于主成分分析（PCA）、概率密度函数（PDF）和自由能景观（FEL），使用分子对接、ADMET、分子动力学和元动力学分析对排名前4的类似物进行了进一步分析。经过累积回顾，我们提出一种新型的DB07168类似物（DB07168-A13）（对接分数：-11.2 kcal/mol，MM-GBSA结合能：-55.2 kcal/mol）作为最有前景的GRK6抑制剂，值得进一步进行体外验证，以解决MM的前瞻性治疗干预问题。
