Cao Haitao, Zeng Junjian, Xue Lixin
Department of Cardiovascular Medicine, Wenling First People's Hospital affiliated to Wenzhou Medical University, Wenling, Zhejiang, 317510, China.
Shaoxing University Yuanpei College, Shaoxing, Zhejiang, 312300, China.
BMC Chem. 2025 Jul 3;19(1):192. doi: 10.1186/s13065-025-01568-1.
Traditional pharmaceutical experiments often involve diverse drug compounds with distinct synthesis and identification requirements, typically relying on substantial amounts of chemical reagents and sophisticated analytical instruments-factors that present notable limitations in teaching environments.
This study aims to demonstrate the feasibility and educational value of integrating computational methods into drug synthesis and analysis, using acetylsalicylic acid (ASA) as a case study.
Students synthesized ASA experimentally and used molecular modeling and spectral simulation tools to analyze the compound. Computational techniques were employed to simulate UV-Vis, infrared (IR), and Raman spectra, with comparisons made to experimental results. The COSMO solvation model was applied to investigate solvent effects, and discrepancies in spectral peak assignments were resolved using computational data.
Comparison of experimental and simulated spectra demonstrated high consistency, with R² values of 0.9933 and 0.9995, confirming the predictive power of the computational model. Solvent effects, such as the redshift of UV absorption in aqueous media, were successfully reproduced. Computational analysis resolved ambiguous IR peak assignments caused by overlap or impurities. While limitations such as the lack of NMR data, use of a single functional (GGA/BLYP), and simplified solvation were acknowledged, the integrated approach significantly improved student engagement and conceptual understanding. This study demonstrates the pedagogical and analytical benefits of combining experimental and computational methods, enhancing interpretative accuracy, supporting green chemistry, and offering a reproducible, resource-efficient framework for pharmaceutical education.
传统的药物实验通常涉及多种具有不同合成和鉴定要求的药物化合物，通常依赖大量化学试剂和精密分析仪器，这些因素在教学环境中存在显著局限性。
本研究旨在以乙酰水杨酸（ASA）为例，证明将计算方法整合到药物合成与分析中的可行性和教育价值。
学生通过实验合成ASA，并使用分子建模和光谱模拟工具对该化合物进行分析。采用计算技术模拟紫外可见光谱、红外光谱（IR）和拉曼光谱，并与实验结果进行比较。应用COSMO溶剂化模型研究溶剂效应，并利用计算数据解决光谱峰归属中的差异。
实验光谱与模拟光谱的比较显示出高度一致性，R²值分别为0.9933和0.9995，证实了计算模型的预测能力。成功再现了溶剂效应，如水介质中紫外吸收的红移。计算分析解决了由重叠或杂质导致的红外峰归属不明确的问题。尽管承认存在诸如缺乏核磁共振数据、使用单一泛函（GGA/BLYP）和简化溶剂化等局限性，但综合方法显著提高了学生的参与度和概念理解。本研究证明了结合实验和计算方法在教学和分析方面的益处，提高了解释准确性，支持了绿色化学，并为药物教育提供了一个可重复、资源高效的框架。
