Title |
Critical assessment of different methods for quantitative measurement of metallodrug-protein associations
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Published in |
Analytical & Bioanalytical Chemistry, August 2018
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DOI | 10.1007/s00216-018-1328-8 |
Pubmed ID | |
Authors |
Luis Galvez, Sarah Theiner, Márkó Grabarics, Christian R. Kowol, Bernhard K. Keppler, Stephan Hann, Gunda Koellensperger |
Abstract |
Quantitative screening for potential drug-protein binding is an essential step in developing novel metal-based anticancer drugs. ICP-MS approaches are at the core of this task; however, many applications lack in the capability of large-scale high-throughput screenings and proper validation. In this work, we critically discuss the analytical figures of merit and the potential method-based quantitative differences applying four different ICP-MS strategies to ex vivo drug-serum incubations. Two candidate drugs, more specifically, two Pt(IV) complexes with known differences of binding affinity towards serum proteins were selected. The study integrated centrifugal ultrafiltration followed by flow injection analysis, turbulent flow chromatography (TFC), and size exclusion chromatography (SEC), all combined with inductively coupled plasma-mass spectrometry (ICP-MS). As a novelty, for the first time, UHPLC SEC-ICP-MS was implemented to enable rapid protein separation to be performed within a few minutes at > 90% column recovery for protein adducts and small molecules. Graphical abstract Quantitative screening for potential drug-protein binding is an essential step in developingnovel metal-based anticancer drugs. |
X Demographics
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Country | Count | As % |
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United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 67% |
Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
Geographical breakdown
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Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 5 | 21% |
Student > Master | 5 | 21% |
Student > Ph. D. Student | 5 | 21% |
Student > Doctoral Student | 2 | 8% |
Researcher | 1 | 4% |
Other | 1 | 4% |
Unknown | 5 | 21% |
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Business, Management and Accounting | 1 | 4% |
Other | 0 | 0% |
Unknown | 6 | 25% |