Impact of Protonation Sites on Collision-Induced Dissociation-MS/MS Using CIDMD Quantum Chemistry Modeling.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-09-27 DOI:10.1021/acs.jcim.4c00761
Jesi Lee,Dean Joseph Tantillo,Lee-Ping Wang,Oliver Fiehn
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Abstract

Protonation is the most frequent adduct found in positive electrospray ionization collision-induced mass spectra (CID-MS/MS). In a parallel report Lee, J. J. Chem. Inf. Model. 2024, 10.1021/acs.jcim.4c00760, we developed a quantum chemistry framework to predict mass spectra by collision-induced dissociation molecular dynamics (CIDMD). As different protonation sites affect fragmentation pathways of a given molecule, the accuracy of predicting tandem mass spectra by CIDMD ultimately depends on the choice of its protomers. To investigate the impact of molecular protonation sites on MS/MS spectra, we compared CIDMD-predicted spectra to all available experimental MS/MS spectra by similarity matching. We probed 10 molecules with a total of 43 protomers, the largest study to date, including organic acids (sorbic acid, citramalic acid, itaconic acid, mesaconic acid, citraconic acid, and taurine) as well as aromatic amines including uracil, aniline, bufotenine, and psilocin. We demonstrated how different protomers can converge different fragmentation pathways to the same fragment ions but also may explain the presence of different fragment ions in experimental MS/MS spectra. For the first time, we used in silico MS/MS predictions to test the impact of solvents on proton affinities, comparing the gas phase and a mixture of acetonitrile/water (1:1). We also extended applications of in silico MS/MS predictions to investigate the impact of protonation sites on the energy barriers of isomerization between protomers via proton transfer. Despite our initial hypothesis that the thermodynamically most stable protomer should give the best match to the experiment, we found only weak inverse relationships between the calculated proton affinities and corresponding entropy similarities of experimental and CIDMD-predicted MS/MS spectra. CIDMD-predicted mechanistic details of fragmentation reaction pathways revealed a clear preference for specific protomer forms for several molecules. Overall, however, proton affinity was not a good predictor corresponding to the predicted CIDMD spectra. For example, for uracil, only one protomer predicted all experimental MS/MS fragment ions, but this protomer had neither the highest proton affinity nor the best MS/MS match score. Instead of proton affinity, the transfer of protons during the electrospray process from the initial protonation site (i.e., mobile proton model) better explains the differences between the thermodynamic rationale and experimental data. Protomers that undergo fragmentation with lower energy barriers have greater contributions to experimental MS/MS spectra than their thermodynamic Boltzmann populations would suggest. Hence, in silico predictions still need to calculate MS/MS spectra for multiple protomers, as the extent of distributions cannot be readily predicted.
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利用 CIDMD 量子化学建模分析质子化位点对碰撞诱导解离-MS/MS 的影响
质子化是正电喷雾电离碰撞诱导质谱(CID-MS/MS)中最常见的加合物。Lee, J. J. Chem.Inf.Model.2024, 10.1021/acs.jcim.4c00760)中,我们开发了一个量子化学框架,通过碰撞诱导解离分子动力学(CIDMD)预测质谱。由于不同的质子化位点会影响特定分子的碎片路径,因此通过 CIDMD 预测串联质谱的准确性最终取决于其质子的选择。为了研究分子质子化位点对 MS/MS 图谱的影响,我们通过相似性匹配将 CIDMD 预测的图谱与所有可用的实验 MS/MS 图谱进行了比较。我们探查了 10 个分子,共 43 个原体,这是迄今为止规模最大的研究,其中包括有机酸(山梨酸、柠檬酸、衣康酸、中衣康酸、柠康酸和牛磺酸)以及芳香胺,包括尿嘧啶、苯胺、布福丁宁和茜洛辛。我们证明了不同的原生质体如何通过不同的碎裂途径产生相同的片段离子,同时也解释了实验 MS/MS 图谱中存在不同片段离子的原因。通过比较气相和乙腈/水(1:1)混合物,我们首次使用硅学 MS/MS 预测来测试溶剂对质子亲和力的影响。我们还扩展了硅学 MS/MS 预测的应用范围,研究质子化位点对原生质体之间通过质子转移进行异构化的能量障碍的影响。尽管我们最初的假设是热力学上最稳定的原生质体应与实验结果最匹配,但我们发现在实验和 CIDMD 预测的 MS/MS 图谱中,计算出的质子亲和力与相应的熵相似性之间只有微弱的反比关系。CIDMD 预测的碎裂反应途径的机理细节显示,一些分子明显偏好特定的原体形式。但总体而言,质子亲和力并不能很好地预测 CIDMD 预测的光谱。例如,对于尿嘧啶来说,只有一种原体能预测所有实验性 MS/MS 片段离子,但这种原体既没有最高的质子亲和力,也没有最佳的 MS/MS 匹配得分。与质子亲和力相比,电喷雾过程中质子从初始质子化位点的转移(即移动质子模型)更能解释热力学原理与实验数据之间的差异。以较低能障进行碎片化的质子对实验 MS/MS 图谱的贡献比其热力学玻尔兹曼种群所显示的要大。因此,在进行硅学预测时,仍需计算多个原生质体的 MS/MS 图谱,因为其分布范围无法轻易预测。
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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