Shen Hualiang, Yu Guoqi, Cai Tao, Hu Kai, Shang Tianbo, Luo Yanjuan, Zhu Jiawei, Bai Xiaoxue, Xiong Yicheng, Xi Meiyang, Shen Runpu
Zhejiang Engineering Research Center of Fat-Soluble Vitamin, Shaoxing University, Shaoxing, China.
School of Chemistry and Chemical Engineering, Shaoxing University, Shaoxing, China.
Chem Biol Drug Des. 2025 Mar;105(3):e70082. doi: 10.1111/cbdd.70082.
Parkinson's disease (PD) is the second most common neurodegenerative disease but has limited medications. Targeting leucine-rich repeat kinase 2 (LRRK2) has been identified as a potential strategy for the treatment of PD. The development of LRRK2 inhibitors has attracted much interest, and various compounds have been reported with significant improvement in preclinical and clinical models. Currently, no LRRK2 inhibitor has been approved for PD intervention. Herein, we reported a virtual screening (VS) workflow combining molecular docking and molecular dynamics (MD) simulations to achieve eight compounds for further enzymatic assay. The results indicated a potent LRRK2 inhibitor 2 with IC values of 2.396 and 5.996 μM against LRRK2 and LRRK2 G2019S, respectively, implying the reliability of this VS approach. Combined with predicted favorable drug-like properties, this hit can be used as a starting point for further structural optimization, probably offering insight into targeting LRRK2 for PD treatment in the future.
帕金森病（PD）是第二常见的神经退行性疾病，但可用药物有限。靶向富含亮氨酸重复激酶2（LRRK2）已被确定为治疗PD的一种潜在策略。LRRK2抑制剂的研发引起了广泛关注，已有多种化合物在临床前和临床模型中显示出显著疗效。目前，尚无LRRK2抑制剂被批准用于PD干预。在此，我们报告了一种结合分子对接和分子动力学（MD）模拟的虚拟筛选（VS）工作流程，以获得8种化合物用于进一步的酶活性测定。结果表明，一种有效的LRRK2抑制剂2对LRRK2和LRRK2 G2019S的IC值分别为2.396和5.996 μM，这意味着这种VS方法的可靠性。结合预测的良好类药性质，该命中化合物可作为进一步结构优化的起点，可能为未来靶向LRRK2治疗PD提供思路。
