Abstract
Small molecule ligands that can specifically recognize the surface of cancer cells have wide utilities in cancer diagnosis and treatment. Screening large combinatorial libraries against live cells is an effective approach to discover cell-targeting ligands. In the past decade, DNA-encoded chemical library (DEL or DECL) has become a powerful technology in drug discovery and been successfully used in ligand discovery against numerous biological targets. However, nearly all DEL selections had predefined targets, whereas completely unbiased DEL selections interrogating the entire cell surface remain underexplored. In this report, we systematically optimized cell-based DEL selection method to perform unbiased selections against cancer cells without predefined targets. A 104.96-million-member DEL was selected against MDA-MB-231 and MCF7, a pair of breast cancer cell lines with high and low metastatic properties, respectively, and cell-specific small molecule ligands and ligand combinations (“clusters”) have been identified. We further show that the ligand cluster could be optimized to improve the binding affinity and applied in cell-targeting applications including cancer photodynamic therapy and targeted drug delivery. Finally, we leveraged the DNA tag of the DEL compounds and identified the cell surface receptor of an individual ligand targeting MDA-MB-231 cells. Overall, this work provides an efficient method for discovering cell-targeting small molecules and demonstrated the potential of DELs as a tool for cancer biomarker discovery.
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Supporting Information
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Supplementary figures, tables, experimental details
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Custom script for data analysis
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Custom script for data analyis
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