Ying-Jung Wu1, Ching-Hui Huang2, Tusty-Jiuan Hsieh3, Wei-Lung Tseng4, Chi-Yu Lu1,5,6. 1. Department of Biochemistry, College of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. 2. Division of Cardiology, Department of Internal Medicine, Changhua Christian Hospital, Changhua, 50006, Taiwan. 3. Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. 4. Department of Chemistry, College of Science, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan. 5. Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan. 6. Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, 80708, Taiwan.
Abstract
RATIONALE: Understanding drug-drug interactions and predicting the side effects induced by polypharmacy are difficult because there are few suitable platforms that can predict drug-drug interactions and possible side effects. Hence, developing a platform to identify significant protein markers of drug-drug interactions and their associated side effects is necessary to avoid adverse effects. METHODS: Human liver cells were treated with ethosuximide in combination with cimetidine, ketotifen, metformin, metronidazole, or phenytoin. After sample preparation and extraction, mitochondrial proteins from liver cells were isolated and digested with trypsin. Then, peptide solutions were detected using a nano ultra-performance liquid chromatographic system combined with tandem mass spectrometry. The Ingenuity Pathway Analysis tool was used to simulate drug-drug interactions and identify protein markers associated with drug-induced adverse effects. RESULTS: Several protein markers were identified by the proposed method after liver cells were co-treated with ethosuximide and other drugs. Several of these protein markers have previously been reported in the literature, indicating that the proposed platform is workable. CONCLUSIONS: Using the proposed in vitro platform, significant protein markers of drug-drug interactions could be identified by mass spectrometry. This workflow can then help predict indicators of drug-drug interactions and associated adverse effects for increased safety in clinical prescriptions.
RATIONALE: Understanding drug-drug interactions and predicting the side effects induced by polypharmacy are difficult because there are few suitable platforms that can predict drug-drug interactions and possible side effects. Hence, developing a platform to identify significant protein markers of drug-drug interactions and their associated side effects is necessary to avoid adverse effects. METHODS:Human liver cells were treated with ethosuximide in combination with cimetidine, ketotifen, metformin, metronidazole, or phenytoin. After sample preparation and extraction, mitochondrial proteins from liver cells were isolated and digested with trypsin. Then, peptide solutions were detected using a nano ultra-performance liquid chromatographic system combined with tandem mass spectrometry. The Ingenuity Pathway Analysis tool was used to simulate drug-drug interactions and identify protein markers associated with drug-induced adverse effects. RESULTS: Several protein markers were identified by the proposed method after liver cells were co-treated with ethosuximide and other drugs. Several of these protein markers have previously been reported in the literature, indicating that the proposed platform is workable. CONCLUSIONS: Using the proposed in vitro platform, significant protein markers of drug-drug interactions could be identified by mass spectrometry. This workflow can then help predict indicators of drug-drug interactions and associated adverse effects for increased safety in clinical prescriptions.