GCI is ideally suited for fragment-based drug discovery due to inherent sensitivity of the detection principle, and the ability to capture fast transitions. Here we show a collection of challenging target classes across a variety of fragment-based drug discovery campaigns where GCI was used to screen fragment libraries (~ 1100 compounds). Hits were picked based on statistical errors and kinetic rate constants. Identified hits were subsequently validated via orthogonal methods including XRC and DSF, highlighting the robustness, reliability, and superior sensitivity of GCI.
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GCI is ideally suited for fragment-based drug discovery due to inherent sensitivity of the detection principle, and the ability to capture fast transitions. Here we show a collection of challenging target classes across a variety of fragment-based drug discovery campaigns where GCI was used to screen fragment libraries (~ 1100 compounds). Hits were picked based on statistical errors and kinetic rate constants. Identified hits were subsequently validated via orthogonal methods including XRC and DSF, highlighting the robustness, reliability, and superior sensitivity of GCI.
