Using LC Retention Times in Organic Structure Determination: Drug Metabolite Identification
| Autor: | Cyrus Khojasteh, William L. Fitch, Ignacio Aliagas, Kevin M. Johnson |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Time Factors
Computer science Metabolite Drug metabolite Clinical Biochemistry Quantitative Structure-Activity Relationship Pharmaceutical Science RT prediction Hydroxylation 01 natural sciences Mass Spectrometry Article RT Workflow chemistry.chemical_compound Atorvastatin Humans liquid chromatography mass spectrometry (MS) CHI system Pharmacology (medical) Biotransformation Molecular Structure 010405 organic chemistry 010401 analytical chemistry Biochemistry (medical) Hydrogen Bonding Demethylation Drug metabolite identification 0104 chemical sciences Identification (information) chemistry Organic structure Microsomes Liver Biological system Hydrophobic and Hydrophilic Interactions Oxidation-Reduction Retention time Carbanilides Chromatography Liquid |
| Zdroj: | Drug Metabolism Letters |
| ISSN: | 1872-3128 |
| Popis: | Background: There is a continued need for improvements in the efficiency of metabolite structure elucidation. Objective: We propose to take LC Retention Time (RT) into consideration during the process of structure determination. Methods: Herein, we develop a simple methodology that employs a Chromatographic Hydrophobicity Index (CHI) framework for standardizing LC conditions and introduce and utilize the concept of a pre-dictable CHI change upon Phase 1 biotransformation (CHIbt). Through the analysis of literature exam-ples, we offer a Quantitative Structure-Retention Relationship (QSRR) for several types of biotransfor-mation (especially hydroxylation) using physicochemical properties (clogP, hydrogen bonding). Results: The CHI system for retention indexing is shown to be practical and simple to implement. A da-tabase of CHIbt values has been created from re-incubation of 3 compounds and from analysis of an addi-tional 17 datasets from the literature. Application of this database is illustrated. Conclusion: In our experience, this simple methodology allows complementing the discovery efforts that saves resources for in-depth characterization using NMR. |
| Databáze: | OpenAIRE |
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