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• W2343546465 abstract "Selection of target-binding ligands from DNA-encoded libraries of small molecules (DELSMs) is a rapidly developing approach in drug-lead discovery. Methods of kinetic capillary electrophoresis (KCE) may facilitate highly efficient homogeneous selection of ligands from DELSMs. However, KCE methods require accurate prediction of electrophoretic mobilities of protein-ligand complexes. Such prediction, in turn, requires a theory that would be applicable to DNA tags of different structures used in different DELSMs. Here we present such a theory. It utilizes a model of a globular protein connected, through a single point (small molecule), to a linear DNA tag containing a combination of alternating double-stranded and single-stranded DNA (dsDNA and ssDNA) regions of varying lengths. The theory links the unknown electrophoretic mobility of protein-DNA complex with experimentally determined electrophoretic mobilities of the protein and DNA. Mobility prediction was initially tested by using a protein interacting with 18 ligands of various combinations of dsDNA and ssDNA regions, which mimicked different DELSMs. For all studied ligands, deviation of the predicted mobility from the experimentally determined value was within 11%. Finally, the prediction was tested for two proteins and two ligands with a DNA tag identical to those of DELSM manufactured by GlaxoSmithKline. Deviation between the predicted and experimentally determined mobilities did not exceed 5%. These results confirm the accuracy and robustness of our model, which makes KCE methods one step closer to their practical use in selection of drug leads, and diagnostic probes from DELSMs." @default.
• W2343546465 created "2016-06-24" @default.
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• W2343546465 date "2016-05-05" @default.
• W2343546465 modified "2023-10-16" @default.
• W2343546465 title "Predicting Electrophoretic Mobility of Protein–Ligand Complexes for Ligands from DNA-Encoded Libraries of Small Molecules" @default.
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• W2343546465 doi "https://doi.org/10.1021/acs.analchem.6b00980" @default.
• W2343546465 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27119259" @default.
• W2343546465 hasPublicationYear "2016" @default.
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