ANSES, Laboratory for Food Safety, 94701, Maisons-Alfort, France.
ANSES, Laboratory for Food Safety, 94701, Maisons-Alfort, France.
Talanta. 2024 Jan 15;267:125214. doi: 10.1016/j.talanta.2023.125214. Epub 2023 Sep 17.
The development of quantitative structure-retention relationship (QSRR) models has, until recently, required an adequate selection of molecular descriptors necessarily obtained based on a known chemical structure. However, these complex descriptors are not always available nor calculable when the high-resolution mass spectrometry (HRMS) annotation process is underway. Depending on the level of annotation, many structures or even various molecular formulas could be candidates. To secure and improve the annotation process and to save time, a QSRR model (using only 0D molecular descriptors) to predict retention times in reverse-phase liquid chromatography (RPLC) based on the molecular formula was developed, and a general QSRR annotation-based methodology was also proposed.
定量构效关系（QSRR）模型的发展直到最近都需要对分子描述符进行适当的选择，这些描述符必须基于已知的化学结构来获得。然而，当进行高分辨率质谱（HRMS）注释过程时，这些复杂的描述符并不总是可用或可计算的。根据注释的程度，许多结构甚至各种分子式都可能是候选对象。为了确保和改进注释过程并节省时间，开发了一种基于分子式的反相液相色谱（RPLC）保留时间预测的 QSRR 模型（仅使用 0D 分子描述符），并提出了一种基于通用 QSRR 注释的方法。
