Many disease pathologies can be understood through the elucidation of localized biomolecular networks, or microenvironments. To this end, enzymatic proximity labeling platforms are broadly applied for mapping the wider spatial relationships in subcellular architectures. However, technologies that can map microenvironments with higher precision have long been sought. Here, we describe a microenvironment-mapping platform that exploits photocatalytic carbene generation to selectively identify protein-protein interactions on cell membranes, an approach we term MicroMap (μMap). By using a photocatalyst-antibody conjugate to spatially localize carbene generation, we demonstrate selective labeling of antibody binding targets and their microenvironment protein neighbors. This technique identified the constituent proteins of the programmed-death ligand 1 (PD-L1) microenvironment in live lymphocytes and selectively labeled within an immunosynaptic junction.

Modern proximity labeling techniques have enabled significant advances in understanding biomolecular interactions. However, current tools primarily utilize activation modes that are incompatible with complex biological environments, limiting our ability to interrogate cell- and tissue-level microenvironments in animal models. Here, we report μMap-Red, a proximity labeling platform that uses a red-light-excited SnIV chlorin e6 catalyst to activate a phenyl azide biotin probe. We validate μMap-Red by demonstrating photonically controlled protein labeling in vitro through several layers of tissue, and we then apply our platform in cellulo to label EGFR microenvironments and validate performance with STED microscopy and quantitative proteomics. Finally, to demonstrate labeling in a complex biological sample, we deploy μMap-Red in whole mouse blood to profile erythrocyte cell-surface proteins. This work represents a significant methodological advance toward light-based proximity labeling in complex tissue environments and animal models.

Over half of new therapeutic approaches fail in clinical trials due to a lack of target validation. As such, the development of new methods to improve and accelerate the identification of cellular targets, broadly known as target ID, remains a fundamental goal in drug discovery. While advances in sequencing and mass spectrometry technologies have revolutionized drug target ID in recent decades, the corresponding chemical-based approaches have not changed in over 50 y. Consigned to outdated stoichiometric activation modes, modern target ID campaigns are regularly confounded by poor signal-to-noise resulting from limited receptor occupancy and low crosslinking yields, especially when targeting low abundance membrane proteins or multiple protein target engagement. Here, we describe a broadly general platform for photocatalytic small molecule target ID, which is founded upon the catalytic amplification of target-tag crosslinking through the continuous generation of high-energy carbene intermediates via visible light-mediated Dexter energy transfer. By decoupling the reactive warhead tag from the small molecule ligand, catalytic signal amplification results in unprecedented levels of target enrichment, enabling the quantitative target and off target ID of several drugs including (+)-JQ1, paclitaxel (Taxol), dasatinib (Sprycel), as well as two G-protein-coupled receptors—ADORA2A and GPR40.

Doxorubicin is a highly effective chemotherapy agent used to treat many common malignancies. However, its use is limited by cardiotoxicity, and cumulative doses exponentially increase the risk of heart failure. To identify novel heart failure treatment targets, a zebrafish model of doxorubicin‐induced cardiomyopathy was previously established for small‐molecule screening. Using this model, several small molecules that prevent doxorubicin‐induced cardiotoxicity both in zebrafish and in mouse models have previously been identified. In this study, exploration of doxorubicin cardiotoxicity is expanded by screening 2271 small molecules from a proprietary, target‐annotated tool compound collection. It is found that 120 small molecules can prevent doxorubicin‐induced cardiotoxicity, including 7 highly effective compounds. Of these, all seven exhibited inhibitory activity towards cytochrome P450 family 1 (CYP1). These results are consistent with previous findings, in which visnagin, a CYP1 inhibitor, also prevents doxorubicin‐induced cardiotoxicity. Importantly, genetic mutation of cyp1a protected zebrafish against doxorubicin‐induced cardiotoxicity phenotypes. Together, these results provide strong evidence that CYP1 is an important contributor to doxorubicin‐induced cardiotoxicity and highlight the CYP1 pathway as a candidate therapeutic target for clinical cardioprotection.

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The identification of cellular targets that can be exploited for therapeutic benefit, broadly known as target ID, remains a fundamental goal in drug discovery. In recent years, the application of new chemical and biological technologies that accelerate target ID has become commonplace within drug discovery programs, as a complete understanding of how molecules react in a cellular environment can lead to increased binding selectivity, improved safety profiles, and clinical efficacy. Established approaches using photoaffinity labelling (PAL) are often costly and time-consuming due to poor signal-to-noise coupled with extensive probe optimization. Such challenges are exacerbated when dealing with low abundance membrane proteins or multiple protein target engagement, typically rendering target ID unfeasible. Herein, we describe a general platform for photocatalytic small molecule target ID, which hinges upon the generation of high-energy carbene intermediates via visible light-mediated Dexter energy transfer. By decoupling the reactive warhead from the drug, catalytic signal amplification results in multiple labelling events per drug, leading to unprecedented levels of target enrichment. Through the development of cell permeable photocatalyst conjugates, this method has enabled the quantitative target and off target identification of several drugs including (+)-JQ1, paclitaxel, and dasatinib. Moreover, this methodology has led to the target ID of two GPCRs, ADORA2A and GPR40m, a class of drug target seldom successfully uncovered in small molecule PAL campaigns.

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