2nd International Conference on Chemo and Bioinformatics ICCBIKG 2023 (2-5)
АУТОР(И) / AUTHOR(S): Rudolf Bauer
Е-АДРЕСА / E-MAIL:
DOI: 10.46793/ICCBI23.002B
САЖЕТАК / ABSTRACT:
Drug discovery from medicinal plants has always been a longstanding and fruitful endeavor in the quest for novel therapeutic agents. Chemometric techniques, such as multivariate data analysis, enable the systematic analysis of complex chemical profiles obtained from plant extracts and correlation with activity. Compounds exhibiting high correlations in orthogonal projections to latent structures discriminant analysis (OPLS-DA) of pharmacological and MS data, are most promising for the identification of active constituents. Feature-based molecular networking within the Global Natural Product Social Molecular Networking (GNPS) helps to identify interesting compound clusters. Several examples are presented which demonstrate how these methods can be applied in drug discovery from medicinal plants.
КЉУЧНЕ РЕЧИ / KEYWORDS:
Medicinal plants, LC-MS, metabolomics, chemometrics, drug discovery
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