Liu Chao
Dongguan City University, Dongguan, China.
PLoS One. 2025 May 29;20(5):e0324018. doi: 10.1371/journal.pone.0324018. eCollection 2025.
This study presents a targeted virtual drug screening approach for autism spectrum disorder (ASD), focusing on Cav1.2 calcium ion channels as potential therapeutic targets. ASD is a complex neurodevelopmental disorder characterized by impairments in social communication and behavior, with genetic factors playing a significant role. Cav1.2 channels have been implicated in the pathophysiology of ASD due to their role in regulating neuronal excitability and synaptic transmission. We employed computational methods to virtually screen a large database of compounds for their potential to modulate Cav1.2 channel function. Molecular docking simulations were used to identify potential Cav1.2 inhibitors, followed by pharmacokinetic modeling to assess drug-like properties. Molecular dynamics (MD) simulations were performed to evaluate the interactions of the top candidates with Cav1.2, and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) analysis was employed to predict binding free energies. This approach identified several promising drug candidates, including ZINC000828320609, which exhibited strong binding affinity to Cav1.2, favorable pharmacokinetic properties, and no predicted toxicity. The virtual screening results provide a solid foundation for further experimental validation and potential drug development for ASD, offering a novel and efficient strategy to target Cav1.2 channels in the treatment of this complex disorder.
本研究提出了一种针对自闭症谱系障碍(ASD)的靶向虚拟药物筛选方法,重点关注Cav1.2钙离子通道作为潜在治疗靶点。ASD是一种复杂的神经发育障碍,其特征是社交沟通和行为受损,遗传因素起重要作用。由于Cav1.2通道在调节神经元兴奋性和突触传递中的作用,它们已被认为与ASD的病理生理学有关。我们采用计算方法对大量化合物数据库进行虚拟筛选,以评估它们调节Cav1.2通道功能的潜力。分子对接模拟用于识别潜在的Cav1.2抑制剂,随后进行药代动力学建模以评估药物样性质。进行分子动力学(MD)模拟以评估顶级候选物与Cav1.2的相互作用,并采用分子力学/泊松-玻尔兹曼表面积(MM/PBSA)分析来预测结合自由能。该方法鉴定出了几种有前景的药物候选物,包括ZINC000828320609,它对Cav1.2表现出强烈的结合亲和力、良好的药代动力学性质且无预测毒性。虚拟筛选结果为ASD的进一步实验验证和潜在药物开发提供了坚实基础,为在治疗这种复杂疾病中靶向Cav1.2通道提供了一种新颖且高效的策略。