Kendrick Mass Defect Filtering Enables High-Throughput Untargeted Annotation of Minor Phytocannabinoids: Toward Streamlined Phytocannabinomics.

ABSTRACT: Phytocannabinoids are a diverse class of bioactive compounds produced by Cannabis sativa, including both major and a growing number of minor constituents with pharmacological relevance. However, their comprehensive annotation in untargeted high-resolution mass spectrometry (HRMS) data sets remains a significant analytical challenge due to their structural similarity, low abundance, and the complexity of plant matrices. In this study, we present a comparative evaluation of Kendrick Mass Defect (KMD)-based filtering workflows for the efficient untargeted annotation of minor phytocannabinoids. Three data processing strategies were implemented using Compound Discoverer: (i) KMD filtering before the "Compound Detection" tool, (ii) KMD filtering after the "Compound Detection" tool, and (i

SUBMITTER: Cerrato A 

PROVIDER: S-EPMC12715730 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature