
pmid: 28986384
Fragment-based approaches in chemical biology and drug discovery have been widely adopted worldwide in both academia and industry. Fragment hits tend to interact weakly with their targets, necessitating the use of sensitive biophysical techniques to detect their binding. Common fragment screening techniques include differential scanning fluorimetry (DSF) and ligand-observed NMR. Validation and characterization of hits is usually performed using a combination of protein-observed NMR, isothermal titration calorimetry (ITC) and X-ray crystallography. In this context, MS is a relatively underutilized technique in fragment screening for drug discovery. MS-based techniques have the advantage of high sensitivity, low sample consumption and being label-free. This review highlights recent examples of the emerging use of MS-based techniques in fragment screening.
ligand-observed mass spectrometry, Magnetic Resonance Spectroscopy, native mass spectrometry, Proteins, Calorimetry, Crystallography, X-Ray, Ligands, Mass Spectrometry, High-Throughput Screening Assays, Small Molecule Libraries, Structure-Activity Relationship, Drug Design, Drug Discovery, Combinatorial Chemistry Techniques, Humans, Fluorometry, fragment-based drug discovery, Protein Binding
ligand-observed mass spectrometry, Magnetic Resonance Spectroscopy, native mass spectrometry, Proteins, Calorimetry, Crystallography, X-Ray, Ligands, Mass Spectrometry, High-Throughput Screening Assays, Small Molecule Libraries, Structure-Activity Relationship, Drug Design, Drug Discovery, Combinatorial Chemistry Techniques, Humans, Fluorometry, fragment-based drug discovery, Protein Binding
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
