计算药剂学在纳米金刚石中的应用研究进展

Research progress in the application of computational pharmaceutics in nanodiamonds

摘要

目的: 系统阐明计算药剂学在揭示纳米金刚石(nanodiamond,ND)结构与功能关系中的关键作用,以应对其实验研究中的微观复杂性挑战。方法: 聚焦分子动力学模拟(molecular dynamics,MD)、密度泛函理论(density functional theory,DFT)及机器学习等多尺度计算方法,综述其在ND研究中的应用策略与进展。结果: 计算模拟成功揭示了ND表面修饰对药物控释的pH响应机制、形状与电荷对跨膜行为的影响规律以及空位色心(NV/SiV)的光学稳定性。模拟结果与实验观测高度吻合,并为ND的分散特性、界面相互作用等提供了原子尺度洞察。结论: 计算药剂学是推动ND理性设计与应用开发的核心驱动力,通过发展高精度机器学习势函数和深度多尺度耦合,将加速ND在精准医疗与生物传感等前沿领域的创新应用。

Abstract

Objective: To systematically elucidate the pivotal role of computational pharmaceutics in unveiling the structure-function relationships of nanodiamond (ND), addressing the challenges posed by their microscopic complexity in experimental research. Methods: This review focused on multi-scale computational approaches, including molecular dynamics (MD) simulation, density functional theory (DFT), and machine learning, summarizing their application strategies and progress in ND research. Results: Computational simulations successfully revealed the pH-responsive drug release mechanisms governed by ND surface modifications, the influence of shape and charge on transmembrane behavior, and the optical stability of vacancy centers (e.g., NV/SiV). The simulation results showed strong agreement with experimental observations and provided atomic-scale insights into ND dispersion properties and interfacial interactions. Conclusion: Computational pharmaceutics serves as a core driver for the rational design and application development of ND. Advancing high-precision machine learning potentials and deep multi-scale coupling will accelerate innovative applications of ND in cutting-edge fields such as precision medicine and biosensing.

关键词

计算药剂学 / 纳米金刚石 / 分子动力学模拟 / 量子力学模拟 / 机器学习

Key words

computational pharmaceutics / nanodiamond / molecular dynamics simulation / quantum mechanical simulation / machine learning

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基金资助

国家自然科学基金资助项目(81903553);山东省自然科学基金资助项目(ZR2017QH006);山东省医药卫生科技资助项目(202413020723);济宁医学院国(境)外访问资助项目(2024-2025)