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经实验验证与分析后对新型化学战剂的量子化学质谱预测

Quantum Chemical Mass Spectral Predictions of Novichok Agents after Experimental Validation and Analysis.

作者信息

Kim Sungsoo, Shin Moon Sik, Hong Seonghoon, Moon Janghyuk, Jo Seungbum, Jeong Keunhong

机构信息

School of Energy Systems Engineering, Chung-Ang University, Heukseok-Ro, Dongjak-Gu, Seoul 06974, Republic of Korea.

ROK Chemical, Biological and Radiological Defense Research Institute, 12-555, Naegok-dong, Seocho-gu, Seoul 06790, Republic of Korea.

出版信息

ACS Meas Sci Au. 2025 May 23;5(3):378-387. doi: 10.1021/acsmeasuresciau.5c00026. eCollection 2025 Jun 18.

Abstract

The identification of chemical warfare agents, particularly Novichok variants, presents significant challenges due to the inherent dangers and practical limitations of experimental analysis. This study advances a computational approach using quantum chemistry electron ionization mass spectrometry (QCxMS, x = EI) to predict the electron ionization mass spectra (EIMS) of these compounds. We obtained experimental mass spectral data from three synthesized Novichok compounds, providing a crucial benchmark for validating computational predictions. Through systematic comparison of the experimental and predicted spectra, we evaluated how the incorporation of additional polarization functions and expanded valence space in basis sets influences prediction accuracy. Our investigation demonstrated that more complete basis sets yielded significantly improved matching scores across seven compounds while maintaining consistent functional parameters for ionization potential (IP) calculations. Comprehensive analysis of mass spectral patterns revealed distinct correlations between the molecular structure and fragmentation behavior. We identified characteristic patterns in both high and low / regions that correspond to specific structural features, enabling the development of a systematic framework for spectral interpretation. This understanding of the fragmentation mechanisms allowed for the prediction of mass spectra for four additional compounds with varying structural complexity. The strong correlation between the predicted and experimental results for the synthesized compounds validates this computational approach as a promising tool for the rapid identification of new chemical agents without requiring extensive experimental analysis. This methodology represents a significant advancement in our ability to identify and characterize emerging chemical threats while minimizing exposure risks to research personnel.

摘要

由于实验分析存在固有的危险性和实际局限性,化学战剂尤其是新型化学战剂的鉴定面临重大挑战。本研究提出了一种利用量子化学电子电离质谱法(QCxMS,x = EI)来预测这些化合物的电子电离质谱(EIMS)的计算方法。我们从三种合成的新型化学战剂化合物中获得了实验质谱数据,为验证计算预测提供了关键基准。通过对实验光谱和预测光谱的系统比较,我们评估了基组中额外极化函数和扩展价层空间的纳入对预测准确性的影响。我们的研究表明,更完整的基组在计算七种化合物的电离势(IP)时,在保持一致的函数参数的同时,显著提高了匹配分数。对质谱图模式的综合分析揭示了分子结构与碎片行为之间的明显相关性。我们在高、低质量区域都识别出了与特定结构特征相对应的特征模式,从而能够建立一个系统的光谱解释框架。对碎片机制的这种理解使得能够预测另外四种结构复杂程度不同的化合物的质谱。合成化合物的预测结果与实验结果之间的强相关性验证了这种计算方法是一种有前途的工具,可用于快速鉴定新的化学战剂,而无需进行广泛的实验分析。这种方法代表了我们在识别和表征新出现的化学威胁以及将研究人员的暴露风险降至最低方面能力的重大进步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f3e/12183575/dda5e067c11f/tg5c00026_0001.jpg

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