Computational prediction of retention times of veterinary antibiotics obtained by liquid chromatography-mass spectrometry.
Cristian RojasNicole SarmientoEmilia AyoraReinaldo Pis DiezPublished in: Journal of the science of food and agriculture (2024)
The in silico model developed in this work identified three molecular descriptors associated with aqueous solubility, octanol-water partition coefficient, and the presence of negative and lipophilic atom pairs. The QSPR developed here could be implemented by agricultural and food chemists to identify and monitor existing and new antibiotics within the framework of LC-MS. The computational model was developed in accordance with five principles outlined by the Organization for Economic Co-operation and Development. © 2024 Society of Chemical Industry.
Keyphrases
- mass spectrometry
- liquid chromatography
- high resolution mass spectrometry
- tandem mass spectrometry
- high resolution
- risk assessment
- climate change
- heavy metals
- magnetic resonance imaging
- molecular docking
- computed tomography
- ionic liquid
- magnetic resonance
- high performance liquid chromatography
- molecular dynamics
- gas chromatography
- single molecule
- ms ms