Natural products are sources of inspiration and reservoir of high valuable molecules. Recently, analytical tools based on liquid chromatography coupled to tandem mass spectrometry to generate molecular network became widely employed for dereplication. This strategy greatly accelerates the identification of known and structural hypothesis of unknown. Despite the availability of different ionization sources, alternatives to classical electrospray ionization (ESI), such as atmospheric pressure chemical ionization (APCI) or photoionization (APPI), have been neglected. In particular, APPI has been described for its ionization efficiency on non-polar molecules bearing no acid or basic groups. For that reason, we investigated APPI potential to generate molecular network and compare it to ESI on several criteria that are generation of ion species, sensitivity and signal-to-noise ratio (SNR) for different extracts rich in highly conjugated natural products. We first optimized APPI experimental conditions on crude extract from a fungus, Penicillium sclerotiorum, producing polyketones belonging to the azaphilone family. Then we compared APPI and ESI on different fractions of the fungus and on two plant extracts, French Guyanese Swartzia panacoco (Aubl.) R.S. Cowan (arial parts) and Indian Cassia auriculata L. (leaves) containing phenolic compounds, such as flavonoids. While ESI generated more ion species and displayed a better sensitivity, APPI generated only protonated adduct and better SNR. Comparing ESI and APPI generated species on molecular network reveal that both strategies overlap for the majority of protonated ions.

天然产物是灵感的来源和高价值分子的储备。近来，基于液相色谱与串联质谱联用生成分子网络的分析工具已被广泛用于重复数据删除。这种策略大大加快了对已知和未知结构假设的识别。尽管可以使用不同的电离源，但是传统的电喷雾电离（ESI）的替代方法已被忽略，例如大气压化学电离（APCI）或光电离（APPI）。特别地，已经描述了APPI在不带有酸或碱性基团的非极性分子上的电离效率。因此，我们研究了APPI产生分子网络的潜力，并将其与ESI进行了比较，并根据几个标准（即离子物种的产生）进行了比较，富含高度共轭天然产物的不同提取物的灵敏度和信噪比（SNR）。我们首先针对真菌的粗提物优化了APPI实验条件，青霉菌，产生属于氮杂磷酮家族的聚酮。然后，我们比较了真菌不同部分和两种植物提取物的APPI和ESI，这两种植物提取物是法国圭亚那Swartzia panacoco（Aubl。）RS Cowan（阿里亚部分）和印度肉桂（Cassia auriculata L。）（叶子），其中含有酚类化合物，例如类黄酮。ESI产生更多的离子种类并显示出更好的灵敏度，而APPI仅产生质子化的加合物和更好的SNR。在分子网络上比较ESI和APPI生成的物质表明，两种策略在大多数质子化离子上都有重叠。